Decentralized Control

Purpose -This paper aims to identify and compare the nature of decentralization that has emerged in three important Asian societies after a decade of their involvement in the decentralization movement. Design/methodology/approach -Data from the first cycle of the program for international student assessment were analyzed to investigate educational decentralization in three Asian societies: Hong Kong, Japan, and Korea. Cluster analysis was used to reveal the nature and extent of decentralization of the schooling systems in the three societies. Findings -The results revealed four models of decentralization: highly centralized, school-driven, teacher-driven, and highly decentralized. Whilst the school-driven model was dominant in Hong Kong, indicating that the school itself is largely responsible for making school-related decisions, the centralized model was dominant in both Japan and Korea, indicating that authorities outside the school are largely responsible for making school-related decisions.

The autonomous polygeneration microgrid topology has been developed in order to cover holistically needs in a remote area such as electrical energy, space heating and cooling, potable water through desalination and hydrogen as fuel for transportation. The existence of an advanced energy management system is essential for the operation of an autonomous polygeneration microgrid. So far, energy management systems based on a centralized management and control have been developed for the autonomous polygeneration microgrid topology based on computational intelligence approaches. A decentralized management and control energy management system can have important benefits, when taking into consideration the autonomous character of these microgrids. This paper presents the design and investigation of a decentralized energy management system for the autonomous polygeneration microgrid topology. The decentralized energy management system gives the possibility to control each unit of the microgrid independently. The most important advantage of using a decentralized architecture is that the managed microgrid has much higher chances of partial operation in cases when malfunctions occur at different parts of it, instead of a complete system breakdown. The designed system was based on a multi-agent system and employed Fuzzy Cognitive Maps for its implementation. It was then compared through a case study with an existing centralized energy management system. The technical performance of the decentralized solution performance is on par with the existing centralized one, presenting improvements in financial and operational terms for the implementation and operation of an autonomous polygeneration microgrid.

Convex conditions, expressed as linear matrix inequalities (LMIs), for stability analysis and robust design of uncertain discrete-time systems with time-varying delay are presented in this paper. Delaydependent and delay-independent convex conditions are given. This paper is particularly devoted to the synthesis case where convex conditions are proposed to consider maximum allowed delay interval. It is also presented some relaxed LMIs that yield less conservative conditions at the expense of increasing the computational burden. Extensions to cope with decentralized control and output feedback control are discussed. Numerical examples, including real world motivated models, are presented to illustrate the effectiveness of the proposed approach. (V.J.S. Leite). constant delay. The problem of robust filtering for discrete-time uncertain systems with delayed states is considered in some papers. Delayed state systems with norm-bounded uncertainties are studied in and with polytopic uncertainties in . In the last case the delay is time-invariant. Recently, the problem of output feedback has attracted attention and can be cited as examples of on going research. In special, presents results for precisely known systems with time-varying delay including both static output feedback (SOF) and dynamic output feedback. The conditions, however, are presented as an interactive method that relax some matrix inequalities. In time-varying delay is assumed and a nonlinear algorithm is proposed to obtain a stabilizing controller. In [24] the results of [11] are extended, including polytopic uncertainties and constant Lyapunov-Krasovskii matrices. An interesting application can be found in the context of network control system: although most of the studies in the literature on this subject deal with continuous-time models, nowadays there are some approaches using discrete-time models with delayed states . See also for a robust adaptive sliding mode control scheme applied to discrete-time systems with time-varying delay in the state and subject to norm-bounded uncertainties. In the context of discrete-time-varying systems with time-varying delay in the state, see for convex approaches to the dynamic output feedback controller design problem.

A comparison between two machine learning approaches viz., Genetic Fuzzy Methodology and Q-learning, is presented in this paper. The approaches are used to model controllers for a set of collaborative robots that need to work together to bring an object to a target position. The robots are fixed and are attached to the object through elastic cables. A major constraint considered in this problem is that the robots cannot communicate with each other. This means that at any instant, each robot has no motion or control information of the other robots and it can only pull or release its cable based only on the motion states of the object. This decentralized control problem provides a good example to test the capabilities and restrictions of these two machine learning approaches. The system is first trained using a set of training scenarios and then applied to an extensive test set to check the generalization achieved by each method.

This paper describes the development and testing of OPAC (Optimization Policies for Adaptive Control), a computational strategy for demand-responsive decentralized traffic signal control. The strategy has the following features: (1) it calculates controls that approach the theoretical optimirnum; (2) it only requires on-line data that can be obtained from upstream link detectors; and (3) it forms a building block for demand-responsive decentralized control in a network. Performance of the strategy was tested by simulation as well as in practice.

I n fluidized-bed gas-phase polymerization reactors, several grades of polyethylene are produced in the same equipment by changing the operating conditions. Transitions between the different grades are rather slow and result in the production of a considerable amount of off-specification polymer. Grade transition improvement is viewed here as a dynamic optimization problem, for which numerous approaches exist. Numerical optimization based on a nominal process model is typically insufficient due to the presence of uncertainty in the form of model mismatch and process disturbances. This paper proposes to implement optimal grade transition using a measurement-based approach instead. It is based on tracking the necessary conditions of optimality (NCO tracking) using a decentralized control scheme. For this, the nominal input profiles are dissected into arcs and switching times that are assigned to the various parts of the NCO. These input elements are then adapted using appropriate measurements. NCO tracking is used to determine optimal grade transition in polyethylene reactors. The problem of minimizing the transition time from a steady state of low melt index to that of high melt index is studied, with the feeds of hydrogen and inert and the output flow rate considered as manipulated variables. In the optimal solution, all arcs are determined by path constraints, and all switching times are determined by path and terminal constraints, which significantly eases the adaptation. The on-line and run-to-run adaptation of these parameters is illustrated in simulation.

The widely used pairing criteria involving the Niederlinski index and the steady-state relative gain array (RGA) used for evaluating integrity under decentralized control are extended to open-loop unstable plants it will in some cases be preferable to choose pairings giving negative Niederlinski index and/or RGA. The relationship between the two measures is also clarified.

This paper presents a relatively new method for achieving better welding results of gas metal arc welding (GMAW) system by using a decentralized control method. The GMAW system is an arc welding process which incorporates the power source of GMAW (PS-GMAW) with the ...

Prior research shows that third-party agents are necessary to promote cooperation when groups are large and spatially diffuse. I explore whether this proposition holds in the self-governing sport of Ultimate. While the size of the community and spatial diffusion of the sport theoretically suggests limited decentralized control, the widespread implementation of a refereed system has not yet emerged. Instead, I find with qualitative methods that cooperation in Ultimate is the result of the sport being federally controlled and embedded within tiers of organizational constraint that promote informal regulation of competitions through norms, reputations, and self-discipline. for helpful comments on earlier versions of this article. I gratefully acknowledge the Ultimate community for making this project possible and the Mallards for not only providing a compelling case to study, but for years of fellowship and camaraderie.

This paper presents the development and implementation of a communication and coordination strategy among multiple mobile robotic devices, so that they can work together becoming a collaborative. This strategy will enable a group of several autonomous agents (mobile robots) to exhibit cooperative and/or coordinate behaviors, so that they can work both independently to achieve local objectives, as well as collectively to achieve overall objectives, exploring or modifying its operating environment. For the development of the proposed strategy, agents will be distributed taking into consideration a decentralized command configuration, so the integrated system can adapt dynamically to internal or external disturbances that may occur. For validation of the proposed strategy it will be used heterarchical command architecture (decentralized) in order to coordinate agents or holons with associate physical resources. The strategy discussed in this work will enable a collaborative system to a...

This work describes the modeling, simulation and decentralized control of a Coupled Three Tank System. The system is modeled mathematically using Bernoulli's law, mass balance and energy balance. Then the model is simulated in MATLAB using script file and in Simulink using S-functions. This system is linearized using Control and Estimation Tool Manager from Simulink model and using Jacobian method form mathematical model. The model is analyzed using step response, eigen values, real part of poles, number of Right Half Plane (RHP) zeros, Relative Gain Array (RGA) and controllability. The controllers are designed and tuned iteratively using Sequential Loop Closing (SLC). Controllers for flow are designed by specifying the closed-loop response while PI controllers for temperature are tuned iteratively. These controllers are also applied to nonlinear Simulink model where they give a good stability remarkable performance.

Purpose-Objective of this paper is to analyze, how different factors related to organizational structure named as decentralization, formalization, and specialization impacts innovation capability of an organization in its logistics services. Methodology-Proposed conceptual model consists of combination of Strategy-Structure-Performance (SSP) and Resource Based View (RBV) of the firm. Data were collected from textile sector of Pakistan and structure equation modeling was performed to check the hypothesized relationships.

This study compares PI and MPC controls via a computer simulation for a gas recovery unit (GRU), which consists of three distillation columns operated in series: a de-ethanizer, a depropanizer and a debutanizer. In addition, the de-ethanizer feed is preheated by the bottoms product from the de-ethanizer, which causes additional process coupling. Rigorous models are developed for the columns including column pressure dynamics and heat transfer dynamics. The process is a highly coupled system and has interactive constraints that determine the feasible operating regions. A decentralized PI control system with override controls for the constraints was designed and implemented on the GRU simulator and was compared with an industrial MPC controller. The MPC controller was observed to outperform the decentralized control system due to its multivariable constraint control capability. Since the simulator is available to other university researchers, it can serve as a challenge problem for multivariable control and identification. Three MPC controllers with different strategies for controlling the bottom level of the first column were implemented on the GRU process. The first MPC controller does not directly control the level, the second one moves the setpoint to the PI level controller, and the third one controls the level directly by manipulating the flow. The results show that including level into the MPC controller improves composition control for cases in which the manipulated variable for the level control has a significant impact on compositions. #

A microgrid is hard to control due to its reduced inertia and increased uncertainties. To overcome the challenges of microgrid control, advanced controllers need to be developed. In this paper, a distributed, two-level, communication-economic control scheme is presented for multiple-bus microgrids with each bus having multiple distributed generators (DGs) connected in parallel. The control objective of the upper level is to calculate the voltage references for one-bus subsystems. The objectives of the lower control level are to make the subsystems' bus voltages track the voltage references and to enhance load current sharing accuracy among the local DGs. Firstly, a distributed consensus-based power sharing algorithm is introduced to determine the power generations of the subsystems. Secondly, a discrete-time droop equation is used to adjust subsystem frequencies for voltage reference calculations. Finally, a Lyapunov-based decentralized control algorithm is designed for bus voltage regulation and proportional load current sharing. Extensive simulation studies with microgrid models of different levels of detail are performed to demonstrate the merits of the proposed control scheme.

This paper addresses the low-frequency relative stability problem in paralleled inverter-based distributed generation (DG) units in microgrids. In the sense of the small-signal dynamics of a microgrid, it can be shown that as the demanded power of each inverter changes, the low-frequency modes of the power sharing dynamics drift to new locations and the relative stability is remarkably affected, and eventually, instability can be yielded. To preserve the power sharing stability, an adaptive decentralized droop controller of paralleled inverter-based DG units is presented in this paper. The proposed power sharing strategy is based on the static droop characteristics combined with an adaptive transient droop function. Unlike conventional droop controllers, which yield 1-DOF tunable controller, the proposed droop controller yields 2-DOF tunable controller. Subsequently, the dynamic performance of the power sharing mechanism can be adjusted, without affecting the static droop gain, to damp the oscillatory modes of the power sharing controller. To account for the power modes immigration at different loading conditions, the transient droop gains are adaptively scheduled via small-signal analysis of the power sharing mechanism along the loading trajectory of each DG unit to yield the desired transient and steady-state response. The gain adaptation scheme utilizes the filtered active and reactive powers as indices; therefore, a stable and smooth power injection performance can be obtained at different loading conditions. The adaptive nature of the proposed controller ensures active damping of power oscillations at different operating conditions, and yields a stable and robust performance of the paralleled inverter system. Index Terms-Adaptive control, decentralized control, distributed generation (DG), microgrid, parallel operation, power sharing stability.

The renewable energy resources provide us with green
energy and flexible integration into power grids, but due to their
variable nature, they cause significant frequency, voltage and
power fluctuation for power system so that a sophisticated
control strategy is needed to cope with these challenges. In this
paper, the proposed control strategy consists of inner voltage and
current controller and outer power loop. In this study, at first,
coefficients of conventional PI controllers are obtained by a
proposed objective function, and then it is shown that this PI
controller with constant parameters doesn’t work properly over
wide range of load variation, and the system is likely to be
unstable. To obtain better performance, gain scheduling tuning
approach is proposed to adjust PI coefficients for resistive,
inductive and capacitive loads. This approach is applied to an
autonomous three bus ac microgrid using Particle Swarm
Optimization.

The purpose of this inquiry is to explore how the a/r/tographic model of shared inquiry led to deeper insights about learner-centered pedagogy. Invited to teach and redesign a very large undergraduate “Art and Society: Visual Arts” course, the author’s commitment as a constructivist teacher led to a more active, non-lecture, art-as-experience approach. The author also sought to understand how learner-centered practices enhance students’ balanced thinking and perceptions about their abilities as creative learners. Arts-based methods of inquiry highlighted both students’ and researcher’s lived experiences, informed praxis, and resulted in new art forms. The author’s Mixed Parallaxic Praxis method emerged from this study. Key findings indicate students’ increased openness to other perspectives, increased engagement, increased creative and critical thinking, a personal desire/thirst to create art, and a personal confidence to analyze art—despite most students’ lack of former experience with art making or art instruction in high school.

In this study, a novel sensor/actuator network approach for scalable automated facility logistics systems is presented. The approach comprises (1) a new sensor combination (cameras and few RFID scanners) for distributed detection, localization and identification of parcels and bins and (2) a novel middleware approach based on a service oriented architecture tailored towards the utilization in sensor/actuator networks. The latter enables a more flexible deploying of automated facility logistics system, while the former presents a novel departure for the detection and tracking of bins and parcels in automated facility logistics systems: light barriers and bar code readers are substituted by low-cost cameras, local conveyor mounted embedded evaluation units and few RFID readers. By combining visionbased systems and RFID systems, this approach can compensate for the drawbacks of each respective system. By utilizing a stateof-the-art middleware for connecting all computer systems of an automated facility logistics system the costs for deployment and reconfiguring the system can be decreased.

In this paper we have done a survey over control and management challenges in modern power systems today in terms of emerging distributed power generation (DG), microgrid management, electricity marketing and power quality control toward smart grid. Intelligent agent and multiagent systems (MAS) technology are introduced, then properties and more potential benefits of MAS for power systems such as scalability, expertise and grid-computing are discussed to address MAS is a appropriate solution for power engineering challenges.

The objective is to control a web transport system with winder and unwinder for elastic material. A physical modeling of this plant is made based on the general laws of physics. For this type of control problem, it is extremely important to prevent the occurrence of web break or fold by decoupling the web tension and the web velocity. Due to the wide-range variation of the radius and inertia of the rollers the system dynamics change considerably during the winding/unwinding process. Different strategies for web tension control and linear transport velocity control are presented in this paper. First, a H robust control strategy which reduces the coupling between tension and velocity, is compared to the decentralized control strategy with proportional integral derivative

A strategy for adaptive control and energetic optimization of aerobic fermentors was implemented, with both air flow and agitation speed as manipulated variables. This strategy is separable in its components: control, optimization, estimation. We optimized parameter’s estimation (from the usual KLa correlation) using sinusoidal excitation of air flow and agitation speed. We have implemented parameter’s estimation trough recursive least squares algorithm with forgetting factor. We carried separate essays on control, optimization and estimation algorithms. We carried our essays using an original computational simulation environment, with noise and delay generating facilities for data sampling and filtering.

Our results show the convergence and robustness of the estimation algorithm used, improved with use of both forgetting factor and KLa dead-band facilities. Control algorithm used in our work compares favorably with PID using the integrated area criteria for deviation between oxygen molarity and critical molarity (set point). Optimization algorithm clearly reduces energetic consumption, respecting critical molarity. Integration of control, optimization and adaptive algorithms was implemented, but future work is needed for stability. Methods were defined and implemented for stability improvement. We have implemented data acquisition and computer manipulation of air flow and agitation speed for actual fermentors.

This paper presents a relatively new method for achieving better welding results of gas metal arc welding (GMAW) system by using a decentralized control method. The GMAW system is an arc welding process which incorporates the power source of GMAW (PS-GMAW) with the wire feed unit (WFU). In this paper, the GMAW system is considered as two separated subsystems, those are PS-GMAW and the WFU. The mathematical modeling of PS-GMAW and WFU are presented. Based on two subsystems, a sliding mode controller is designed and applied to control the WFU meanwhile a proportional controller is designed and applied to control the PS-GMAW. Furthermore, two decentralized controllers have to be designed to control the welding arc of GMAW, be stable and control the output welding current and welding voltage for tracking the constant setting values accurately during the welding process, respectively. The simulation and experimental results are presented to show the effectiveness of the proposed controllers.

This paper presents the development of a new robust optimal decentralized PI controller based on nonlinear optimization for liquid level control in a coupled tank system. The proposed controller maximizes the closed-loop bandwidth for specified gain and phase margins, with constraints on the overshoot ratio to achieve both closed-loop performance and robustness. In the proposed work, a frequency response fitting model reduction technique is initially employed to obtain a first order plus dead time (FOPDT) model of each higher order subsystem. Furthermore, based on the reduced order model, a proposed controller is designed. The stability and performance of the proposed controller are verified by considering multiplicative input and output uncertainties. The performance of the proposed optimal robust decentralized control scheme has been compared with that of a decentralized PI controller. The proposed controller is implemented in real-time on a coupled tank system. From the obtained results, it is shown that the proposed optimal decentralized PI controller exhibits superior control performance to maintain the desired level, for both the nominal as well as the perturbed case as compared to a decentralized PI controller.

Social facilitation occurs when an animal is more likely to behave in a certain way in response to other animals engaged in the same behaviour. For example, an individual returning to the nest with food stimulates other ants to leave and to forage. In the present study we demonstrate the existence of new facets in the colony organization of Dinoponera quadriceps: a positive feedback between the incoming food and the activation of new foragers, and the occurrence of incipient task partitioning during the food sharing. Lower-ranked workers located inside the nest process protein resources and higher-ranked workers handle smaller pieces and distribute them to the larvae. In conclusion, D. quadriceps has a decentralized pattern of task allocation with a double regulatory mechanism, which can be considered a sophisticated aspect of division of labour in ponerine ants.

Swarm intelligence is a relatively novel field. It addresses the study of the collective behaviors of systems made by many components that coordinate using decentralized controls and self-organization. A large part of the research in swarm intelligence has focused on the reverse engineering and the adaptation of collective behaviors observed in natural systems with the aim of designing effective algorithms for distributed optimization. These algorithms, like their natural systems of inspiration, show the desirable properties of being adaptive, scalable, and robust. These are key properties in the context of network routing, and in particular of routing in wireless sensor networks. Therefore, in the last decade, a number of routing protocols for wireless sensor networks have been developed according to the principles of swarm intelligence, and, in particular, taking inspiration from the foraging behaviors of ant and bee colonies. In this paper, we provide an extensive survey of these protocols. We discuss the general principles of swarm intelligence and of its application to routing. We also introduce a novel taxonomy for routing protocols in wireless sensor networks and use it to classify the surveyed protocols. We conclude the paper with a critical analysis of the status of the field, pointing out a number of fundamental issues related to the (mis) use of scientific methodology and evaluation procedures, and we identify some future research directions. include the cases in which individual sensor nodes send their readings towards: (i) a global monitoring node (commonly indicated as a sink), that performs full data aggregation and inference, (ii) intermediate sink nodes, that can individually or cooperatively process the data before sending the results to the global sink or locally trigger the appropriate actions, and (iii) a global sink, but with partial data aggregation being performed on the way as data packets are forwarded hop by hop from sensor nodes towards the sink. Cases (ii)-(iii) are commonly referred to as in-network aggregation, and are meant to optimize energy and bandwidth resources.

This paper investigates a method for decentralized stabilization of vehicle formations using techniques from algebraic graph theory. The vehicles exchange information according to a pre-specified communication digraph, G. A feedback control is designed using relative information between a vehicle and its in-neighbors in G. We prove that a necessary and sufficient condition for an appropriate decentralized linear stabilizing feedback to exist is that G has a rooted directed spanning tree. We show the direct relationship between the rate of convergence to formation and the eigenvalues of the (directed) Laplacian of G. Various special situations are discussed, including symmetric communication graphs and formations with leaders. Several numerical simulations are used to illustrate the results.

In this paper, we present a decentralized dynamic control algorithm for a robot collective consisting of multiple nonholonomic wheeled mobile manipulators (NH-WMMs) capable of cooperatively transporting a common payload. In this algorithm, the high level controller deals with motion/force control of the payload, at the same time distributes the motion/force task into individual agents by grasp description matrix. In each individual agent, the low level controller decomposes the system dynamics into decoupled task space (end-effector motions/forces) and a dynamically-consistent null-space (internal motions/forces) component. The agent level control algorithm facilitates the prioritized operational task accomplishment with the end-effector impedance-mode controller and secondary null-space control. The scalability and modularity is guaranteed upon the decentralized control architecture. Numerical simulations are performed for a 2-NH-WMM system carrying a payload (with/without uncertainty) to validate this approach.

The border gateway protocol (BGP) has become the indispensible infrastructure of the Internet as a typical inter-domain routing protocol. However, it is vulnerable to misconfigurations and malicious attacks since BGP does not provide enough authentication mechanism to the route advertisement. As a result, it has brought about many security incidents with huge economic losses. Exiting solutions to the routing security problem such as S-BGP, So-BGP, Ps-BGP, and RPKI, are based on the Public Key Infrastructure and face a high security risk from the centralized structure. In this paper, we propose the decentralized blockchain-based route registration framework-decentralized route registration system based on blockchain (DRRS-BC). In DRRS-BC, we produce a global transaction ledge by the information of address prefixes and autonomous system numbers between multiple organizations and ASs, which is maintained by all blockchain nodes and further used for authentication. By applying blockchain, DRRS-BC perfectly solves the problems of identity authentication, behavior authentication as well as the promotion and deployment problem rather than depending on the authentication center. Moreover, it resists to prefix and subprefix hijacking attacks and meets the performance and security requirements of route registration.

Necessary and sufficient conditions are presented for the existence of coordinating prices in coupled dynamic systems. The formulation includes a coordinator with a non-separable payoff, and a coupling system with dynamics. New insights are obtained by examining three entities-toprice-the subsystem control, the subsystem output, and the coupling system state.

This paper describes an adaptive fuzzy control strategy for decentralized control for a class of interconnected nonlinear systems with MIMO subsystems. An adaptive robust tracking control schemes based on fuzzy basis function approach is developed such that all the states and signals are bounded. In addition, each subsystem is able to adaptively compensate for disturbances and interconnections with unknown bounds. The resultant adaptive fuzzy decentralized control with multi-controller architecture guarantees stability and convergence of the output errors to zero asymptotically by local output-feedback. An extensive application example of a three-machine power system is discussed in detail to verify the effectiveness of the proposed algorithm.

In this article, an approach for tracking control of robot manipulators is presented. The proposed controller incorporates the approximately known inverse dynamic model output as a model-base portion of the controller; an estimated uncertainty term to compensate for the un-modeled dynamics, external disturbances, and time-varying parameters; and a decentralized PID controller as a feedback portion to enhance closed-loop stability and account for the estimation error of uncertainties. The robustness and capabilities of the proposed approach are investigated in simulation for an example robot.

— The main objective of this paper is to analyze the feasibility of decentralized control approach in providing smart inverter functions for grid-tied AC-stacked PV inverter architecture. Decentralized controller allows fully distributed architecture both in terms of control and physical implementation of a PV system, resulting in higher reliability and potentially lower cost. In this paper, Relative Gain Array concept has been used to determine the best locally measured input-output pairing sets for designing the proposed decentralized controller. Proposed approach by sending supervisory commands to only one inverter minimize the required communications for controlling reactive power and mitigating harmonics. Detailed modeling and analysis are provided to show the feasibility of the proposed decentralized approach. Proposed decentralized control scheme is verified by offline simulation and real-time hardware-in-the-loop setup. Keywords— AC-stacked PV Inverter, PV Inverter Control, Decentralized Control Scheme, Cascaded H-bridge, Relative Gain Array, Grid-tied PV Inverter, Smart Inverter Functions, Harmonic Mitigation, Reactive Power Control.

We describe a framework for cooperative control of a group of nonholonomic mobile robots that allows us to build complex systems from simple controllers and estimators. The resultant modular approach is attractive because of the potential for reusability. Our approach to composition also guarantees stability and convergence in a wide range of tasks. There are two key features in our approach: 1) a paradigm for switching between simple decentralized controllers that allows for changes in formation; 2) the use of information from a single type of sensor, an omnidirectional camera, for all our controllers. We describe estimators that abstract the sensory information at different levels, enabling both decentralized and centralized cooperative control. Our results include numerical simulations and experiments using a testbed consisting of three nonholonomic robots.

This work proposes a control architecture for the consistent motions of a group of nonholonomic robotic vehicles. We present a decentralized control strategy that permits each vehicle to autonomously compute an optimal trajectory by using only locally generated information. In addition, to reach the desired positions in the robot formation, each robot follows a trajectory that is adapted thanks to reactive terms incorporated in the path planning process. This allows the robot to avoid obstacles and to maintain communication with the rest of the formation. We provide the proof of the convergence of this algorithm. Simulation results validate and highlight the efficiency and relevance of this method.

This dissertation is given in two parts followed by concluding remarks. The first three chapters describe the generalization of optimal foraging theory for the design of solitary task-processing agents. The following two chapters address the coordinated action of distributed independent agents to achieve a desirable global result. The short concluding part summarizes contributions and future research directions.

Supply chain (SC) coordination can be pursued by adopting a centralized or decentralized decision-making approach. The former option occurs when there is a unique decision maker in the SC, the latter when several independent actors make decision at the different SC stages. SC contracts are a useful tool to make the several SC actors of a decentralized setting behave coherently among each other, as if the chain were operated in a centralized fashion.

The paper proposes a combined feedforward and feedback control scheme with nonlinear compensators as a solution for multivariable nonlinear processes. This is developed based on classic decentralized control approach for multivariable processes. The design methods for each structure's component are presented. These are based on experimental tests, classic identification and closed loop pole placement methods. The proposed method is compared to the classic solutions given by the decentralized and static decoupling procedures. An analysis on the advantages and the disadvantages of the proposed structure was made. To solve the disadvantages there have been proposed two additional structures. The applicability of the proposed method and of the two classic methods is proved using a real-time structure based on a RST control algorithm. In the end, its software implementation and the obtained results are also showed and commented.

Presently, decentralized feedback control is the only control strategy used in wet limestone flue gas desulfurization (WLFGD) plants. Proper tuning of this control strategy is becoming an important issue in WLFGD plants because more stringent SO 2 regulations have come into force recently. 3 Controllability analysis is a highly valuable tool for proper design of control systems, but it has not been applied to WLFGD plants so far. In this paper a decentralized control strategy is designed and applied to a WLFGD pilot plant taking into account the conclusions of a controllability analysis. The results reveal that good SO 2 control in WLFGD plants can be achieved mainly because the main disturbance of the process is well-aligned with the plant and interactions between control loops are beneficial to SO 2 control.

We overview our recent research on planetary mobility. Products of this effort include the Field Integrated Design & Operations rover (FIDO), Sample Return Rover (SRR), reconfigurable rover units that function as an All Terrain Explorer (ATE), and a multi-Robot Work Crew of closely cooperating rovers (RWC). FIDO rover is an advanced technology prototype; its design and field testing support NASA's development of long range, in situ Mars surface science missions. Complementing this, SRR implements autonomous visual recognition, navigation, rendezvous, and manipulation functions enabling small object pick-up, handling, and precision terminal docking to a Mars ascent vehicle for future Mars Sample Return. ATE implements on-board reconfiguration of rover geometry and control for adaptive response to adverse and changing terrain, e.g., traversal of steep, sandy slopes. RWC implements coordinated control of two rovers under closed loop kinematics and force constraints, e.g., transport of large payloads, as would occur in robotic colonies at future Mars outposts. RWC is based in a new extensible architecture for decentralized control of, and collective state estimation by multiple heterogeneous robotic platforms-CAMPOUT; we overview the key architectural features. We have conducted experiments with all these new rover system concepts over variable natural terrain. For each of the above developments, we summarize our approach, some of our key experimental results to date, and our future directions of planned development.

This paper presents a discrete-time decentralized neural identification and control for largescale uncertain nonlinear systems, which is developed using recurrent high order neural networks (RHONN); the neural network learning algorithm uses an extended Kalman filter (EKF). The discrete-time control law proposed is based on block control and sliding mode techniques. The control algorithm is first simulated, and then implemented in real time for a two degree of freedom (DOF) planar robot. dynamic behavior changes according to unknown external disturbances or due to plant parameter variations and unmodeled dynamics, complicating the controller design.

In this paper, a novel wireless load-sharing controller for islanding parallel inverters in an ac-distributed system is proposed. This paper explores the resistive output impedance of the parallel-connected inverters in an island microgrid. The control loops are devised and analyzed, taking into account the special nature of a low-voltage microgrid, in which the line impedance is mainly resistive and the distance between the inverters makes the control intercommunication between them difficult. In contrast with the conventional droop-control method, the proposed controller uses resistive output impedance, and as a result, a different control law is obtained. The controller is implemented by using a digital signal processor board, which only uses local measurements of the unit, thus increasing the modularity, reliability, and flexibility of the distributed system. Experimental results are provided from two 6-kVA inverters connected in parallel, showing the features of the proposed wireless control.