输入受限的非线性系统模型预测控制

基于模糊T—S模型对输入受限的非线性离散系统,提出了模型预测控制,导出了预测控制性能指标上界,将稳定性约束、输入约束变换成容易求解的线性矩阵不等式(LMIs)形式。采用了状态反馈控制器和并行补偿分布控制器(PDC),基于李雅普诺夫函数和线性矩阵不等式方法给出滚动时域优化的充分条件,证明了闭环系统的稳定性。仿真结果验证了所提方法的有效性。     

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.     

Decentralized output feedback controller design for nonlinear interconnected systems with unknown control direction and time‐varying delays

The decentralized output feedback control problem is considered for a class of large‐scale systems with unknown time‐varying delays. The uncertain interconnections are bounded by general nonlinear functions with unknown coefficients. The control direction parameters are unknown for each subsystem, which brings a challenging issue for decentralized controller design. To deal with this problem, we propose a new decentralized control scheme with the help of Nussbaum function. The decentralized filter is designed at first. By constructing Lyapunov–Krasovskii functional, we design the dynamic output feedback controller. It is rigorously proved that the closed‐loop system is asymptotically stable. Finally, the simulation is performed, and the results verify the effectiveness of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

A small‐gain approach for adaptive output‐feedback NN control of switched pure‐feedback nonlinear systems

This paper investigates the problem of adaptive output‐feedback neural network (NN) control for a class of switched pure‐feedback uncertain nonlinear systems. A switched observer is first constructed to estimate the unmeasurable states. Next, with the help of an NN to approximate the unknown nonlinear terms, a switched small‐gain technique‐based adaptive output‐feedback NN control scheme is developed by exploiting the backstepping recursive design scheme, input‐to‐state stability analysis, the common Lyapunov function method, and the average dwell time (ADT) method. In the recursive design, the difficulty of constructing an overall Lyapunov function for the switched closed‐loop system is dealt with by decomposing the switched closed‐loop system into two interconnected switched systems and constructing two Lyapunov functions for two interconnected switched systems, respectively. The proposed controllers for individual subsystems guarantee that all signals in the closed‐loop system are semiglobally, uniformly, and ultimately bounded under a class of switching signals with ADT, and finally, two examples illustrate the effectiveness of theoretical results, which include a switched RLC circuit system.     

Adaptive backstepping control for a class of time delay systems with nonlinear perturbations

The sliding mode control method has been extensively employed to stabilize time delay systems with nonlinear perturbations. Although the resulting closed‐loop systems have good transient and steady‐state performances, the designed controllers are dependent on the time delays. But one knows that it is difficult to obtain the precise delay time in practical systems, especially when it is time varying. In this paper, we revisit the problem and use the backstepping method to construct the state feedback controller. First, a coordinate transformation is used to obtain a cascade time delay system. Then, a linear virtual control law is designed for the first subsystem. The memoryless controller is further constructed based on adaptive method for the second subsystem with the uncertainties bounded by linear function. By choosing new Lyapunov–Krasovskii functional, we show that the system state converges to zero asymptotically. Via the proposed approach, we also discuss the case that the uncertainties are bounded by nonlinear functions. Finally, simulations are done to verify the effectiveness of the main results obtained. Copyright © 2007 John Wiley & Sons, Ltd.     

Adaptive backstepping neural control of state‐delayed nonlinear systems with full‐state constraints and unmodeled dynamics

In this paper, the problem of adaptive neural control is discussed for a class of strict‐feedback time‐varying delays nonlinear systems with full‐state constraints and unmodeled dynamics, as well as distributed time‐varying delays. The considered nonlinear system with full‐state constraints is transformed into a nonlinear system without state constraints by introducing a one‐to‐one asymmetric nonlinear mapping. Based on modified backstepping design and using radial basis function neural networks to approximate the unknown smooth nonlinear function and using a dynamic signal to handle dynamic uncertainties, a novel adaptive backstepping control is developed for the transformed system without state constraints. The uncertain terms produced by state time delays and distributed time delays are compensated for by constructing appropriate Lyapunov‐Krasovskii functionals. All signals in the closed‐loop system are proved to be semiglobally uniformly ultimately bounded. A numerical example is provided to illustrate the effectiveness of the proposed design scheme.     

Wind energy conversion system regulation via LMI fuzzy pole cluster approach

This paper addresses the design of fuzzy state feedback controller that has not only the ability to stabilize the fuzzy model/system but also to control the transient behavior and closed loop poles location for wind energy conversion system (WECS) that presents interesting control demands and exhibits intrinsic non-linear characteristics. The proposed fuzzy controller is employed to regulate indirectly the power flow in the grid connected WECS by regulating the DC current flows in the interconnected DC link. First, a Takagi–Sugeno fuzzy model is employed to represent the non-linear WECS. Then a model-based fuzzy controller design utilizing the concept of parallel-distributed compensation is developed. Satisfactory time response and closed loop damping over wide operating range are achieved by forcing the closed loop poles into a suitable sub-region of the complex frequency plane. Sufficient stability conditions are expressed in terms of linear matrix inequalities (LMI’s) which can be solved very efficiently using convex optimization techniques. The design procedures are applied to a dynamic model of a typical wind energy conversion system to illustrate the feasibility and the effectiveness of the proposed control techniques via simulation example.     

A robust adaptive voltage and speed regulator for multimachine power systems

In this paper, the transient stability and voltage regulation of multimachine power systems are simultaneously addressed in a multivariable and nonlinear framework. Power systems are nonlinear, large-scale and made of highly coupled generators having a wide range of operating points. Decentralized nonlinear adaptive controllers which continuously update their parameters to compensate for changes in operating points are proposed. The design method is based on a new power system model recently introduced by the authors. The main characteristic of the new model is that interactions between generators and changes in operating conditions are represented by time-varying parameters. The parameters have fixed parts, which depend on the steady-state active and reactive power delivered by each generator, and time-varying parts modelling the interactions between generators, which are treated as disturbances. More importantly, the new model permits the formulation of a control design scheme, which consists of applying the input-output linearization method and stabilizing the resulting partially linear system by a linear control law. The fixed linear gains are computed from an algebraic Riccati equation and considerably attenuate the disturbance effects. An adaptive law derived from the Lyapunov stability method ensures that the controller parameters are bounded and that the generator signals converge asymptotically to steady-state values. The robustness of the controller is used to compensate for the disturbances, while its adaptive nature is used to compensate for load variations that induce operating-point variations. A four-machine power system is used to assess the effectiveness of the multivariable regulator. Simulation results show that good performance in closed loop is achieved.     

Nonlinear excitation control of a synchronous generator with implicit terminal voltage regulation

The objective of this paper is to design nonlinear excitation controllers for single-machine infinite-bus power systems. Because of the nonlinear nature of such systems, nonlinear controllers are more effective in providing larger stability margins than their linear counterparts. To take advantage of well-developed linear control techniques, the concept of feedback linearization is used. A characterization of the region over which the linearizing state transformation is guaranteed to be diffeomorphic is provided. Also, a new formulation for the linear controller design is provided to solve the problem of the terminal voltage regulation. Simulation results of a single-machine infinite-bus power system indicate that in the presence of major disturbances the proposed controller outperforms existing linear and nonlinear controllers in maintaining the system's stability, in damping the rotor angle oscillations, and in reaching the desired performance during postfault operations.     

一种新型非线性时变模型:模糊变参数系统

为了研究非线性时变模型,提出了模糊变参数系统。它是一种集T-S模糊系统和线性变参数系统诸多优点为一体的新型非线性时变模型,它继承了T-S模糊模型能有效处理非线性系统的优点,又保持了线性变参数模型处理时变系统的优势。模糊变参数系统不仅克服了传统T-S模糊模型在处理时变系统时模糊规则剧增的弱点,也扩展了线性变参数系统理论的适用范围,为解决非线性时变系统的控制问题提供了新思路。在以上模型的基础上,给出了零平衡点全局渐进稳定的一个充分条件以及设计一种T-S全状态反馈控制律的充分条件,数值仿真验证了结果的有效性。     

Inverse optimal adaptive control for non‐linear uncertain systems with exogenous disturbances

A Lyapunov‐based inverse optimal adaptive control‐system design problem for non‐linear uncertain systems with exogenous ℒ︁₂ disturbances is considered. Specifically, an inverse optimal adaptive non‐linear control framework is developed to explicitly characterize globally stabilizing disturbance rejection adaptive controllers that minimize a nonlinear‐nonquadratic performance functional for non‐linear cascade and block cascade systems with parametric uncertainty. It is shown that the adaptive Lyapunov function guaranteeing closed‐loop stability is a solution to the Hamilton–Jacobi–Isaacs equation for the controlled system and thus guarantees both optimality and robust stability. Additionally, the adaptive Lyapunov function is dissipative with respect to a weighted input–output energy supply rate guaranteeing closed‐loop disturbance rejection. For special integrand structures of the performance functionals considered, the proposed adaptive controllers additionally guarantee robustness to multiplicative input uncertainty. In the case of linear‐quadratic control it is shown that the operations of parameter estimation and controller design are coupled illustrating the breakdown of the certainty equivalence principle for the optimal adaptive control problem. Finally, the proposed framework is used to design adaptive controllers for jet engine compression systems with uncertain system dynamics. Copyright © 2000 John Wiley & Sons, Ltd.     

不确定互联电力系统的分散鲁棒控制

针对不确定互联电力系统,提出了一种分散鲁棒输出反馈控制器的设计方法.为了使参数不确定性符合工程实际和简化控制器的求解,引入数值界的形式对不确定性进行描述.该方法将控制器的设计归结为一组矩阵不等式的求解问题,采用同伦迭代算法,通过固定不同的变量,将非线性矩阵不等式转化为两组线性矩阵不等式并交替求解.仿真结果表明所获得的控制器使得互联电力系统鲁棒稳定,阻尼转矩充足,满足给定的性能指标,并且具有良好的抑制大扰动的能力.     

Stability analysis and decentralizedcontrol of inverter-based ac microgrid

This work considers the problem of decentralized control of inverter-based ac micro-grid in different operation modes. The main objectives are to (i) design decentralized frequency and voltage controllers, to gather with power sharing, without information exchange between microsources (ii) design passive dynamic controllers which ensure stability of the entire microgrid system (iii) capture nonlinear, interconnected and large-scale dynamic of the micro-grid system withmeshed topology as a port-Hamiltonian formulation (iv) expand the property of shifted-energy function in the context of decentralized control of ac micro-grid (v) analysis of system stability in large signal point of view. More precisely, to deal with nonlinear, interconnected and large-scale structure of micro-grid systems, the port-Hamiltonian formulation is used to capture the dynamic of micro-grid components including microsource, distribution line and load dynamics as well as interconnection controllers. Furthermore, to deal with large signal stability problem of the microgrid system in the grid-connected and islanded conditions, the shifted-Hamiltonian energy function is served as a storage function to ensure incremental passivity and stability of the microgrid system. Moreover, it is shown that the aggregating of the microgrid dynamic and the decentralized controller dynamics satisfies the incremental passivity. Finally, the effectiveness of the proposed controllers is evaluated through simulation studies. The different scenarios including grid-connected and islanded modes as well as transition between both modes are simulated. The simulation conforms that the decentralized control dynamics are suited to achieve the desired objective of frequency synchronization, voltage control and power sharing in the grid-connected and islanded modes. The simulation results demonstrate the effectiveness of the proposed control strategy.     

Model reference adaptive control for nonlinear switched systems under asynchronous switching

In this paper, the problem of model reference adaptive control for nonlinear switched systems with parametric uncertainties is investigated. Asynchronous switching between subsystems and adaptive controllers is also considered. Firstly, a state feedback adaptive controller is designed. Then, sufficient conditions ensuring the global practical stability of the error switched system with average dwell time are proposed. The boundedness of all signals in the closed‐loop system is guaranteed by the proposed adaptive controller. Finally, a practical example is given to demonstrate the validity of the main results. Copyright © 2016 John Wiley & Sons, Ltd.     

Improved synergetic excitation control for transient stability enhancement and voltage regulation of power systems

This paper proposes decentralized improved synergetic excitation controllers (ISEC) for synchronous generators to enhance transient stability and obtain satisfactory voltage regulation performance of power systems. Each generator is considered as a subsystem, for which an ISEC is designed. According to the control objectives, a manifold, which is a linear combination of the deviation of generator terminal voltage, rotor speed and active power, is chosen for the design of ISEC. Compared with the conventional synergetic excitation controller (CSEC), a parameter adaptation scheme is proposed for updating the controller parameter online in order to improve the transient stability and voltage regulation performance simultaneously under various operating conditions. Case studies are undertaken on a single-machine infinite-bus power system and a two-area four-machine power system, respectively. Simulation results show the ISEC can provide better damping and voltage regulation performance, compared with the CSEC without parameter adaptation scheme and the conventional power system stabilizer.     

高压直流换流站分散鲁棒自适应控制器的设计

针对高压直流输电系统（HVDC），提出了一种换流站的分散鲁棒自适应控制器的设计方法，设计中引入自适应非线性阻尼项来抑制系统非线性不确定参数和未知有界干扰的影响，同时采用反演设计方法来克服控制器设计的复杂性，最后获得高压直流输电系统换流站的分散鲁棒自适应控制策略的一般表达式，并提供了整个系统的稳定性证明，所得控制器仅利用本地测量量实现，控制策略具有分散性和适应性，通过NETOMAC数字仿真，仿真结果证明该控制器比常规的PI控制器具有更好的控制效果。     

Sequential design of a decentralized control structure for power system stabilizers

In this paper, a new procedure is developed for designing power system stabilizers under the constraint of sequential stability. This constraint is an important feature of a large scale decentralized control and deals with the property of a design technique that allows the controllers to be adjusted one at a time such that the system remains stable at all times. This constraint is due to the impossibility to adjust all decentralized controllers to the power system simultaneously (due to unavoidable delays in the communication system). The procedure adopts a linearized model of the power system in the state space representation. The stabilizing signal requires the linear feedback of the local variables only. The suggested design procedure is tested on the standard New England 39-bus system.     

An augmented automatic choosing control of observer type for nonlinear systems with linear measurement and its application to power systems

This paper deals with a feedback control using automatic choosing functions and the observer-control design procedure for nonlinear systems with linear measurement. A constant term which arises from linearization of a nonlinear equation is treated as a coefficient of a stable zero dynamics. A given nonlinear system is linearized piecewise so as to be able to design the linear optimal controllers with the linear observers. By the automatic choosing functions, these controllers are smoothly united into a single nonlinear feedback controller, which is called an augmented automatic choosing control of observer type. This controller is applied to a transient stability of power systems, whose simulation results show that the new controller enables to expand the stable region well. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

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.     

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.