Decentralized adaptive output‐feedback control for stochastic interconnected systems with stochastic unmodeled dynamic interactions

In this paper, we consider the problem of decentralized adaptive output‐feedback regulation for stochastic nonlinear interconnected systems with unknown virtual control coefficients, stochastic unmodeled dynamic interactions. The main contributions of the paper are as follows: (1) This paper presents the first result on decentralized output‐feedback control for stochastic nonlinear systems with unknown virtual control coefficients; (2) For stochastic interconnected systems with stochastic integral input‐to‐state stable unmodeled dynamics, and more general nonlinear uncertain interconnections which depend upon the outputs of subsystems and the stochastic unmodeled dynamics, a decentralized output‐feedback controller is designed to drive the outputs and states to the origin almost surely. Copyright © 2011 John Wiley & Sons, Ltd.     

Dual high‐gain‐based adaptive output‐feedback control for a class of nonlinear systems

We propose an adaptive output‐feedback controller for a general class of nonlinear triangular (strict‐feedback‐like) systems. The design is based on our recent results on a new high‐gain control design approach utilizing a dual high‐gain observer and controller architecture with a dynamic scaling. The technique provides strong robustness properties and allows the system class to contain unknown functions dependent on all states and involving unknown parameters (with no magnitude bounds required). Unlike our earlier result on this problem where a time‐varying design of the high‐gain scaling parameter was utilized, the technique proposed here achieves an autonomous dynamic controller by introducing a novel design of the observer, the scaling parameter, and the adaptation parameter. This provides a time‐invariant dynamic output‐feedback globally asymptotically stabilizing solution for the benchmark open problem proposed in our earlier work with no magnitude bounds or sign information on the unknown parameter being necessary. Copyright © 2007 John Wiley & Sons, Ltd.     

Decentralized adaptive control of nonlinear large‐scale pure‐feedback interconnected systems with time‐varying delays

In this paper, an adaptive decentralized neural control problem is addressed for a class of pure‐feedback interconnected system with unknown time‐varying delays in outputs interconnections. By taking advantage of implicit function theorem and the mean‐value theorem, the difficulty from the pure‐feedback form is overcome. Under a wild assumption that the nonlinear interconnections are assumed to be bounded by unknown nonlinear functions with outputs, the difficulties from unknown interconnections are dealt with, by introducing continuous packaged functions and hyperbolic tangent functions, and the time‐varying delays in interconnections are compensated by Lyapunov–Krasovskii functional. Radial basis function neural network is used to approximate the unknown nonlinearities. Dynamic surface control is successfully extended to eliminate ‘the explosion of complexity’ problem in backstepping procedure. To reduce the computational burden, minimal learning parameters technique is successfully incorporated into this novel control design. A delay‐independent decentralized control scheme is proposed. With the adaptive neural decentralized control, only one estimated parameter need to be updated online for each subsystem. Therefore, the controller is more simplified than the existing results. Also, semiglobal uniform ultimate boundedness of all of the signals in the closed‐loop system is guaranteed. Finally, simulation studies are given to demonstrate the effectiveness of the proposed design scheme. Copyright © 2013 John Wiley & Sons, Ltd.     

Decentralized robust adaptive load frequency control using interactions estimation

In this paper, a new model reference decentralized adaptive output feedback controller is proposed for load-frequency control (LFC) of large-scale power systems with unknown parameters. The main problem with a decentralized robust LFC is that the interactions are treated as disturbances. This results in a conservative control action to maintain stability in the worst-case scenario. Furthermore, to improve the performance of the decentralized LFC, the proposed method estimates the interactions from other subsystems to modify the adaptive controller so that the interactions are effectively neutralized. The other important features of the proposed controller are: (1) no prior information about the system parameters is required, (2) random changes in the operating conditions are traced, (3) only the local input–output data are needed, (4) the robustness of the overall system against the system parameter uncertainties is guaranteed. To show the effectiveness of the proposed controller, a three-area power system is studied. The simulation results are promising and highlight the remarkable performance of the controller even in the presence of both plant parameter changes and high interactions.     

Observer‐based adaptive neural control of uncertain MIMO nonlinear systems with unknown control direction

This paper investigates adaptive neural network output feedback control for a class of uncertain multi‐input multi‐output (MIMO) nonlinear systems with an unknown sign of control gain matrix. Because the system states are not required to be available for measurement, an observer is designed to estimate the system states. In order to deal with the unknown sign of control gain matrix, the Nussbaum‐type function is utilized. By using neural network, we approximated the unknown nonlinear functions and perfectly avoided the controller singularity problem. The stability of the closed‐loop system is analyzed by using Lyapunov method. Theoretical results are illustrated through a simulation example. Copyright © 2012 John Wiley & Sons, Ltd.     

Accommodation of unknown actuator faults using output feedback‐based adaptive robust control

In this paper, we solve the problem of output tracking for linear uncertain systems in the presence of unknown actuator failures using discontinuous projection‐based output feedback adaptive robust control (ARC). The faulty actuators are characterized as unknown inputs stuck at unknown values experiencing bounded disturbance and actuators losing effectiveness at unknown instants of time. Many existing techniques to solve this problem use model reference adaptive control (MRAC), which may not be well suited for handling various disturbances and modeling errors inherent to any realistic system model. Robust control‐based fault‐tolerant schemes have guaranteed transient performance and are capable of dealing with modeling errors to certain degrees. But, the steady‐state tracking accuracy of robust controllers, e.g. sliding mode controller, is limited. In comparison, the backstepping‐based output feedback adaptive robust fault‐tolerant control (ARFTC) strategy presented here can effectively deal with such uncertainties and overcome the drawbacks of individual adaptive and robust controls. Comparative simulation studies are performed on a linearized Boeing 747 model, which shows the effectiveness of the proposed scheme. Copyright © 2011 John Wiley & Sons, Ltd.     

Decentralized prescribed performance adaptive tracking control for Markovian jump uncertain nonlinear systems with input saturation

A decentralized prescribed performance adaptive tracking control problem is investigated for Markovian jump uncertain nonlinear interconnected large‐scale systems. The considered interconnected large‐scale systems contain unknown nonlinear uncertainties, unknown control gains, actuator saturation, and Markovian jump signals, and the Markovian jump subsystems are in the form of triangular structure. First, by defining a novel state transformation with the performance function, the prescribed performance control problem is transformed to stabilization problem. Then, introducing an intermediate control signal into the control design, employing neural network to approximate the unknown composite nonlinear function, and based on the framework of the backstepping control design and adaptive estimation method, a corresponding decentralized prescribed performance adaptive tracking controller is designed. It is proved that all the signals in the closed‐loop system are bounded, and the prescribed tracking performances are guaranteed. A numerical example is provided to illustrate the effectiveness of the proposed control strategy. Copyright © 2016 John Wiley & Sons, Ltd.     

Output‐feedback co‐ordinated decentralized adaptive tracking: The case of MIMO subsystems with delayed interconnections

Exact decentralized output‐feedback Lyapunov‐based designs of direct model reference adaptive control (MRAC) for linear interconnected delay systems with MIMO subsystems are introduced. The design process uses a co‐ordinated decentralized structure of adaptive control with reference model co‐ordination which requires an exchange of signals between the different reference models. It is shown that in the framework of the reference model co‐ordination zero residual tracking error is possible, exactly as in the case with SISO subsystems. We develop decentralized MRAC on the base of a priori information about only the local subsystems gain frequency matrices without additional a priori knowledge about the full system gain frequency matrix. To achieve a better adaptation performance we propose proportional, integral time‐delayed adaptation laws. The appropriate Lyapunov–Krasovskii type functional is suggested to design the update mechanism for the controller parameters, and in order to prove stability. Two different adaptive DMRAC schemes are proposed, being the first asymptotic exact zero tracking results for linear interconnected delay systems with MIMO subsystems. Copyright © 2005 John Wiley & Sons, Ltd.     

Decentralized stabilization of large‐scale systems with interval time‐varying delays in interconnections

This paper considers decentralized stabilization problem for a class of large‐scale systems with interval time‐varying delays in interconnections. The time delay is assumed to be a continuous function belonging to a given interval but not necessary to be differentiable. On the basis of constructing a set of improved Lyapunov–Krasovskii functionals, new sufficient conditions for the existence of decentralized state feedback controller are established in terms of linear matrix inequalities. The decentralized control design guarantees the system exponential stability. An illustrative example is given to show the validity of the results obtained in this paper. Copyright © 2012 John Wiley & Sons, Ltd.     

Decentralized bounded input bounded output stabilization of perturbed interconnected time-delay power systems with energy storages

This paper presents a new decentralized bounded input bounded output (BIBO) stabilization problem for a class of interconnected time-delay systems and its application to power systems with energy storages. We first provide conditions for the derivation of an ellipsoid that bounds a given linear functions of the state vector. Then, a design procedure is proposed to synthesize decentralized static output feedback controllers. The designed controllers guarantee that a given linear functions of the state vector, starting from any initial condition, converges exponentially to its prescribed zones. To deal with the time-delay issue, we use an improved weighted integral inequality recently reported in the literature to derive less conservative exponential stability conditions. Then, our presented control approach is applied to an interconnected power system integrated energy storages with multiple time delays. We synthesis decentralized static output feedback load frequency controllers to guarantee that the system frequency and interchanged power converge to their prescribed zones exponentially from any initial conditions. The controller’s construction is simpler and easier for implementation due to only the local output measurements are required. In order to systematically obtain the controller gains, an effective procedure using linear matrix inequality based stabilisation criteria, which can be solved by various computation tools, is provided. Finally, the effectiveness of the proposed control scheme is verified by comprehensive simulations.     

Global adaptive regulation control for a class of nonlinear systems with unknown control coefficients

This paper is concerned with the global asymptotic regulation control problem for a class of nonlinear uncertain systems with unknown control coefficients. The allowed class of uncertainties include unmeasured input‐to‐state stable (ISS) and/or weaker integral ISS (iISS) inverse dynamics, parametric uncertainties, and uncertain nonlinearities. By using the Nussbaum‐type gain technique and changing the ISS/integral ISS inverse dynamics supply rates, we design a dynamic output feedback controller which could guarantee that the system states are asymptotically regulated to the origin from any initial conditions, and the other signals are bounded in closed‐loop systems. The numerical example of a simple pendulum with all unknown parameters and without velocity measurement illustrates our theoretical results. The simulation results demonstrate its efficacy. Copyright © 2015 John Wiley & Sons, Ltd.     

Decentralized adaptive controller for synchronization of nonlinear dynamical heterogeneous networks

For a network of interconnected nonlinear dynamical systems, an adaptive leader–follower output feedback synchronization problem is considered. The proposed structure of decentralized controller and adaptation algorithm is based on speed gradient and passivity. Sufficient conditions of synchronization for one class of heterogeneous networks are established. An example of synchronization of the network of nonidentical Chua systems is analyzed. The main contribution of the paper is adaptive controller design and analysis under conditions of incomplete measurements, incomplete control, and uncertainty. Copyright © 2012 John Wiley & Sons, Ltd.     

Decentralized adaptive command following and disturbance rejection for subsystems with local full‐state feedback

We present a decentralized model reference adaptive control method, where each local controller uses full‐state feedback from the local subsystem. The controller is strictly decentralized, meaning that no information (including reference‐model trajectories) is shared between local controllers. This decentralized controller achieves stabilization, command following, and disturbance rejection provided that the reference‐model commands and the disturbances are sinusoidal with known spectrum. The controller is effective for multi‐input subsystems with arbitrarily large subsystem interconnections. Copyright © 2014 John Wiley & Sons, Ltd.     

Robust adaptive control for uncertain time‐delay systems

The problem of robust stabilization for uncertain dynamic time‐delay systems is considered. Firstly a class of time‐delay systems with uncertainties bounded by high‐order polynomials and unknown coefficients are considered. The corresponding controller is designed by employing adaptive method. It is shown that the controller designed can render the closed‐loop system uniformly ultimately bounded stable based on Lyapunov–Krasovskii method and Lyapunov stability theory. Then the proposed adaptive idea is applied to stabilizing a class of large‐scale time‐delay systems with strong interconnections. A decentralized feedback adaptive controller is designed which guarantees the closed‐loop large‐scale systems uniformly ultimately bounded stable. Finally, numerical examples are given to show the potential of the proposed techniques. Copyright © 2005 John Wiley & Sons, Ltd.     

Anti‐windup synthesis for a model predictive control system

In this paper, an anti‐windup design problem for a model predictive control system is studied. The plant is assumed to be stable. First, we propose the structure of an output feedback model predictive controller with an anti‐windup compensator. Then we show a design method of the anti‐windup compensator that guarantees closed‐loop stability and improves the transient response. The design problem of the anti‐windup compensator is reduced to a linear matrix inequality (LMI) optimization problem. Further, it is shown that there always exists an anti‐windup compensator that ensures global asymptotic stability. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Teaching sampled‐data H∞ control theory using arm robot experiment system

This paper explains how to use an arm robot experiment system to teach sampled‐data H_∞ control theory. A design procedure is presented for a digital tracking control system for a continuous plant with structured uncertainties; the target is the positioning control of an arm robot. To guarantee the robust stability of the closed‐loop system and provide the desired closed‐loop performance, the design problem is first formulated as a sampled‐data H_∞ control problem, and is then transformed into an equivalent discrete‐time H_∞ control problem. Finally, linear matrix inequalities are used to obtain a reduced‐order output‐feedback controller and a static state‐feedback controller. In a course, the design procedure is explained and practice is provided through simulations and experiments. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Feedback-linearization and feedback–feedforward decentralized control for multimachine power system

In this paper a decentralized nonlinear controller for large-scale power systems is investigated. The proposed controller design is based on the input–output feedback linearization methodology. In order to overcome computational difficulties in adopting such methodology, the overall interconnected nonlinear system, given as n-order, is analyzed as a cascade connection of an n₁-order nonlinear subsystem and an n₂-order linear subsystem. The controller design is obtained by applying input–output feedback linearization to the nonlinear subsystem and adopting a tracking control scheme, based on feedback–feedforward technique, for the linear subsystem. In the assumed system model, which is characterised by an interconnected structure between generating units, a decentralised adaptive controller is implemented by decentralizing these constraints. The use of a totally decentralised controller implies a system performance decay with respect to performance when the system is equipped with a centralised controller. Fortunately, the robustness of the proposed controller, based on input–output feedback procedure, guarantees good performance in terms of disturbance even when disturbances are caused by decentralization of interconnection constraints.     

Output‐feedback model‐reference adaptive calibration for map‐based anti‐jerk control of electromechanical automotive clutches

It is well known that the map‐based control can reduce the computational burden of the automotive on‐board controller. This paper proposes an output‐feedback model‐reference adaptive control algorithm to calibrate the map‐based anti‐jerk controller for electromechanical clutch engagement. The algorithm can be used to adaptively construct a data‐driven fuzzy rule base without resorting to manual tuning, so that it can overcome the problem of conventional knowledge‐based fuzzy logic design, which involves strenuous parameter‐tuning work in the construction of calibration maps. To accurately define the consequent of each fuzzy rule for anti‐jerk control, an output feedback law for computing the reference trajectory of clutch engagement is developed to eliminate the discontinuous slip‐stick transition, whereas an adaptive controller is designed to track the reference trajectory and compensate the nonlinearity. The convergence of the proposed output‐feedback model‐reference adaptive control algorithm is analyzed. Simulation results indicate that the proposed method can successfully reduce the excessive vehicle jerk and frictional energy dissipation during clutch engagement as compared with the conventional knowledge‐based fuzzy logic controller without fine tuning.     

不确定时滞组合系统基于状态观测器的鲁棒分散可靠控制

研究一类包含状态时滞和参数不确定性的不确定时滞组合系统基于状态观测器的鲁棒分散可靠控制问题。目的是设计分散状态观测器和基于此观测器的线见性动态输出反馈控制器，使得对于任意容许的不确定性以及在每一个子系统中预先指定执行器子集合内执行器的失效，相应的闭环系统渐近稳定。     

考虑信息结构约束的多机系统励磁控制协调

提出了一种考虑信息结构约束时协调设计励磁控制器的新方法。首先基于信息结构的概念,将控制器的设计转化为特定信息结构下的最优控制问题,然后将推广的最小误差激励法用于该问题的求解,从而求出反馈增益矩阵。仿真结果表明,与分散协调励磁控制相比,引入有价值的远方信号所得到的励磁控制策略能够增强阻尼,提高系统稳定性。