Decentralized Discrete Model Reference Adaptive Control

Modem control theory based on the feedback of all states does not give a design method which tolerates some failure of sensors or actuators. Decentralized control, which stabilizes the interconnected subsystems by means of local feedback control, is considered to have more fault tolerance than centralized control systems do. This paper introduces a mathematical model of a decentralized adaptive control and analyzes the fault tolerance of the decentralized adaptive control system, in which an intelligence is distributed as local adaptive controllers.

Adaptive global coordination of local routing policies for communication networks

This work proposes the framework of dual dynamic triggers to deal with the communication problem of remote control under the event‐triggered scheme for network control systems (NCSs). Compared with the existing NCSs, a local controller is set up at the plant site, which provides the local control input for the plant as a remote controller. The remote controller and the plant measurement have their individual dynamic triggers. Thus it is allowed that the local controller and the remote controller permit asynchronous communication, which is governed by different event conditions. It is proven that the proposed control strategy can drive the closed‐loop system asymptotically to equilibrium. Finally, a numerical example is presented to illustrate the effectiveness of the proposed method.

Integration of fuel cell and electrolyzer on DC bus is a promising alternative to solve voltage fluctuation and balance of power problems in a standalone hybrid renewable power generation systems. The hybrid renewable power generation systems consist of photovoltaic, wind turbine, fuel cell and hydrogen electrolyzer. Each the component integrated on DC bus through the converter DC – DC using local controller to supply the inverter which connected to the islanded load. Local controller in each part will make the system become flexible if there are additional generating units in the future. The local control methods used in this hybrid renewable power generation system is MPPT and constant voltage control. MPPT control applied to photovoltaic and wind turbine converters to maximize power generation from photovoltaic and wind turbine. Constant voltage controller applied to the fuel cell and electrolyzer converters to control the DC bus voltage alternately. This research is a new design system for remote areas by utilizing the potensial of renewable energy in the area. The result show the power quality and continuity of electricity services.

The problem of decentralised robust model following is considered for a class of uncertain large-scale systems with time-varying delay interconnections. It is assumed that the upper bounds of uncertainties and interconnections are unknown. For such a class of uncertain large-scale interconnected time-delay systems, some adaptation laws are introduced to updating the unknown upper bounds, and a class of decentralised local adaptive robust sliding mode controllers is proposed by combining a sliding mode controller with the adaptation law. The proposed decentralised local adaptive robust controller can guarantee that the local tracking error of each subsystem decreases asymptotically to zero in the presence of uncertainties and interconnection terms with time-varying delays. Finally, a numerical example is given to demonstrate the validity of the results.

This paper presents a global stability result on continuous-time indirect totally decentralized adaptive control systems. The algorithms employed in the design of local adaptive controllers are earlier basic conventional adaptive control algorithms subject to parameter projection operation. For the first time, it is shown that without any restriction on signals such as persistence of excitation, global boundedness of the signals in the overall continuous-time feedback system is guaranteed. For implementation, no a priori knowledge on the interactions and unmodeled dynamics is required.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Sector-condition-based results for adaptive control and synchronization of chaotic systems under input saturation

1. Introduction. Control System Design Steps. Adaptive Control. A Brief History. 2. Models for Dynamic Systems. Introduction. State-Space Models. Input/Output Models. Plant Parametric Models. Problems. 3. Stability. Introduction. Preliminaries. Input/Output Stability. Lyapunov Stability. Positive Real Functions and Stability. Stability of LTI Feedback System. Problems. 4. On-Line Parameter Estimation. Introduction. Simple Examples. Adaptive Laws with Normalization. Adaptive Laws with Projection. Bilinear Parametric Model. Hybrid Adaptive Laws. Summary of Adaptive Laws. Parameter Convergence Proofs. Problems. 5. Parameter Identifiers and Adaptive Observers. Introduction. Parameter Identifiers. Adaptive Observers. Adaptive Observer with Auxiliary Input. Adaptive Observers for Nonminimal Plant Models. Parameter Convergence Proofs. Problems. 6. Model Reference Adaptive Control. Introduction. Simple Direct MRAC Schemes. MRC for SISO Plants. Direct MRAC with Unnormalized Adaptive Laws. Direct MRAC with Normalized Adaptive Laws. Indirect MRAC. Relaxation of Assumptions in MRAC. Stability Proofs in MRAC Schemes. Problems. 7. Adaptive Pole Placement Control. Introduction. Simple APPC Schemes. PPC: Known Plant Parameters. Indirect APPC Schemes. Hybrid APPC Schemes. Stabilizability Issues and Modified APPC. Stability Proofs. Problems. 8. Robust Adaptive Laws. Introduction. Plant Uncertainties and Robust Control. Instability Phenomena in Adaptive Systems. Modifications for Robustness: Simple Examples. Robust Adaptive Laws. Summary of Robust Adaptive Laws. Problems. 9. Robust Adaptive Control Schemes. Introduction. Robust Identifiers and Adaptive Observers. Robust MRAC. Performance Improvement of MRAC. Robust APPC Schemes. Adaptive Control of LTV Plants. Adaptive Control for Multivariable Plants. Stability Proofs of Robust MRAC Schemes. Stability Proofs of Robust APPC Schemes. Problems. Appendices. Swapping Lemmas. Optimization Techniques. Bibliography. Index. License Agreement and Limited Warranty.

It is now known that the complexity of network topology has a great impact on the stabilization of complex dynamical networks. In this work, we study the control of random networks and scale-free networks. Conditions are investigated for globally or locally stabilizing such networks. Our strategy is to apply local feedback control to a small fraction of network nodes. We propose the concept of virtual control for microscopic dynamics throughout the process with different pinning schemes for both random networks and scale-free networks. We explain the main reason why significantly less local controllers are required by specifically pinning the most highly connected nodes in a scale-free network than those required by the randomly pinning scheme, and why there is no significant difference between specifically and randomly pinning schemes for controlling random dynamical networks. We also study the synchronization phenomenon of controlled dynamical networks in the stabilization process, both analytically and numerically.

In an active power distribution system, Volt-VAR optimization (VVO) methods are employed to achieve network-level objectives such as minimization of network power losses. The commonly used model-based centralized and distributed VVO algorithms perform poorly in the absence of a communication system and with model and measurement uncertainties. In this paper, we proposed a model-free local Volt-VAR control approach for network-level optimization that does not require communication with other decision-making agents. The proposed algorithm is based on extremum-seeking approach that uses only local measurements to minimize the network power losses. To prove that the proposed extremum-seeking controller converges to the optimum solution, we also derive mathematical conditions for which the loss minimization problem is convex with respect to the control variables. Local controllers pose stability concerns during highly variable scenarios. Thus, the proposed extremum-seeking controller is integrated with an adaptive-droop control module to provide a stable local control response. The proposed approach is validated using IEEE 4-bus and IEEE 123-bus systems and achieves the loss minimization objective while maintaining the voltage within the pre-specific limits even during highly variable DER generation scenarios.

We present a scalable, hierarchical control system for the dynamic resource management of a distributed real-time embedded (DRE) system. This DRE is inspired by the DARPA adaptive and reflective middleware systems (ARMS) program. The goal of the control system is to simultaneously manage multiple resources and QoS concerns using a utility-driven approach for decision making and performance evaluation. At each level of the control hierarchy there are multiple local controllers which autonomously make decisions to optimize their local utility. The controllers in the hierarchy can use different, localized resource control algorithms and the system's user can tune the operations of the local controllers. We discuss how the selections of local control algorithms affect the behavior of the overall system. The control system is designed to be easily adaptable to other multi-tiered DRE systems.

This paper presents a hierarchical structure for fault detection and fault-tolerant control of distributed energy resources (DERs). The structure consists of distributed monitoring and control systems that perform local fault diagnosis and control system reconfiguration, together with a supervisor that communicates with the local controllers and provides high-level oversight and contingency measures in the event that local fault recovery is not possible. To realize this structure, an observer-based output feedback controller is initially designed for each DER to regulate its output in the absence of faults. The design accounts explicitly for practical implementation issues such as measurement sampling and plant-model mismatch. Fault detection is performed by comparing the output of the observer with that of the DER, and using the discrepancy as a residual. An explicit characterization of the minimum allowable sampling rate that guarantees both closed-loop stability and residual convergence in the absence of faults is obtained and used as the basis for deriving (1) a time-varying threshold on the residual which can be used to detect faults for a given sampling period, and (2) controller reconfiguration laws that determine the feasible fall-back control configurations that preserve stability. Finally, the design and implementation of the fault detection and fault-tolerant control architecture are demonstrated using a simulated model of a solid oxide fuel cell plant.

A novel strategy for optimal placement of locally controlled voltage regulators in traditional distribution systems

• Equivalent circuit of GFM-converter system is derived by the analogy-based method, which shows control loop interactions. • Control loop interaction and their impact on small-signal synchronization stability are visualized by equivalent circuits. • It uncovers that AC voltage control brings about negative damping and deteriorates small-signal synchronous stability. • Instructions for improvements of small-signal synchronous stability are given by parameter analyses of AC voltage control. For grid-forming (GFM) converter-based power grids, the impacts of AC voltage control (ACVC) loops on small-signal synchronization stability are rarely discussed in literature. To present the interactions between the synchronization control loop and the ACVC loop in an intuitive and clear approach, this paper establishes the equivalent circuit model of multi-GFM-converter based power systems, and analyzes the impacts of control loop interactions on small-signal synchronization stability. Firstly, the model of multi-GFM converter-based power grids has been established that incorporates the ACVC loop. Then, for the further visualization of control loop interactions, equivalent circuits of the whole systems are derived by the analogy-based method. This analysis allows us to assess the impacts of the ACVC on small-signal synchronization stability. This paper illustrates that ACVC can be equivalently represented as a negative impedance in parallel with the filter inductor. In this case, the ACVC brings about negative damping effects and deteriorates small-signal synchronization stability. Furthermore, the control parameters of the ACVC on small-signal synchronization stability are also quantitatively evaluated. Additionally, interactions between different GFM converters on small-signal synchronization stability are also investigated. Finally, the modified IEEE 10-GFM-converter 39-bus system is built in MATLAB/Simulink platform to validate analyzes and the proposed method.

Decentralized control is a longstanding challenge in systems theory. A decentralized controller may consist of multiple local controllers, connected to disjoint or overlapping sets of sensors and actuators, and where each local controller has limited ability to communicate directly with the remaining local controllers and, in addition, may lack global knowledge of the plant and operation of the remaining local controllers. In the present paper we apply adaptive control to investigate the ability of the local controllers to cooperate globally despite uncertainty, communication constraints, and possibly conflicting performance objectives. The approach we apply in this paper is based on retrospective cost adaptive control (RCAC). The development of RCAC assumes a centralized controller structure; the goal of the present paper is to investigate the stability and performance of RCAC in a decentralized setting.Copyright © 2012 by ASME