含结构不确定系统的变结构鲁棒自适应控制

讨论了含结构不确定SISO系统的变结构模型参考鲁棒自适应控制问题,提出了 一种新的变结构控制方法,使得:1)系统在同时含参数及结构不确定性时,跟踪误差仍能在有 限时间内收敛到零;2)无须假设参考模型为SPR(严格正实)函数.理论分析与数值仿真结果 是一致的.     

Robust backstepping output tracking control for SISO uncertain nonlinear systems with unknown virtual control coefficients

The output tracking controller design problem is dealt with for a class of nonlinear strict-feedback form systems in the presence of nonlinear uncertainties, external disturbance, unmodelled dynamics and unknown time-varying virtual control coefficients. A new method based on signal compensation is proposed to design a linear time-invariant robust controller, which consists of a nominal controller and a robust compensator. It is shown that the closed-loop control system with a controller designed by the proposed method has robust asymptotical practical tracking property for any bounded initial conditions and robust tracking transient property if all initial states are zero.     

Output feedback tracking control by additive state decomposition for a class of uncertain systems

Besides parametric uncertainties and disturbances, unmodelled dynamics and time delay at the input are often present in practical systems, and cannot always be ignored. This paper aims to solve the problem of output feedback tracking control for a class of non-linear uncertain systems subject to unmodelled high-frequency gains and time delay in the input. By additive state decomposition, the uncertain system is transformed to an uncertainty-free system, in which the uncertainties, disturbances and effects of unmodelled dynamics along with time delay are lumped into a new disturbance at the output. Subsequently, additive state decomposition is used to decompose the transformed system to simplify the tracking controller design. The proposed control scheme is applied to three benchmark examples to demonstrate its effectiveness.     

Model reference robust control of a class of SISO systems

A new control design technique, model reference robust control (MRRC), is introduced for a class of SISO systems which contain unknown parameters, possible nonlinear uncertainties, and additive bounded disturbances. The design methodology is a natural, nontrivial extension of model reference adaptive control (MRAC) which is essential to achieving robust stability and performance for linear time-invariant systems. The methodology also represents an important step toward achieving robust stability for time-varying and nonlinear systems. MRRC requires only input and output measurements of the system, rather than the full state feedback and structural conditions on uncertainties required by existing robust control results. MRRC is developed from existing model reference control (MRC) in a manner similar to MRAC. An intermediate result gives conditions under which MRRC yields exponentially asymptotic stability. The general result yielding uniformly ultimately bounded stability is then developed. A scalar example provides intuition into why the control works against a wide class of uncertainties and reveals the implicit learning capability of MRRC     

Robust adaptive control of strict-feedback nonlinear systems with unmodelled dynamics and time-varying delays

This paper presents a novel robust adaptive neural control scheme which can be taken as a robustification of the adaptive backstepping design. The considered class of uncertainties contains unknown non-symmetric dead-zone inputs, time-varying delay uncertainties, unknown dynamic disturbances and unmodelled dynamics. The radial basis function neural networks (RBFNNs) are employed to approximate the unknown nonlinear functions obtained by Young’s inequality. By constructing exponential Lyapunov-Krasovskii functionals, the upper bound functions of the time-varying delay uncertainties are compensated for. Using Young’s inequality and RBFNNs, the assumptions with respect to unmodelled dynamics are relaxed. It is demonstrated that the proposed controller guarantees that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error eventually converges to a neighbourhood of zero.     

A model reference robust control with unknown high‐frequency gain sign

In this paper, we discuss the model reference robust control (MRRC) for plants with unknown high‐frequency gain sign. Based on an appropriate monitoring function, a switching scheme is proposed so that after a finite number of switching, for plants with relative degree one, the tracking error converges to zero exponentially, while for plants with relative degree greater than one, it converges exponentially to a residual set that can be made arbitrarily small by properly choosing some design parameters. Copyright © 2009 John Wiley & Sons, Ltd.     

Robust Adaptive Output‐Feedback Dynamic Surface Control of a Class of Nonlinear Systems with Unmodeled Dynamics

This paper presents a robust adaptive output‐feedback dynamic surface control (DSC) for a class of nonlinear systems with unmodeled dynamics or/and uncertain time‐varying disturbances. Based on traditional K‐filters, the proposed adaptive DSC scheme is able to guarantee semi‐global stability of the closed‐loop system without applying any approximation techniques. The adaptive law is necessary only at the first design step, which, together with the introduction of a first‐order filter at each design step, makes the control law easy to implement. Moreover, it is shown that the tracking error can converge to an arbitrarily small residual set by adjusting only one design parameter.     

Optimality in discrete model-following systems in the presence of unmodelled dynamics.

The problem of optimal model-following linear control of discrete stochastic adaptive systems is studied in the presence of unmodelled dynamics. The controller complexity is restricted to that corresponding to the perfectly modelled situation. The key for a control design to be robust in the presence of unmodelled dynamics is closely related to some parametrical conditions that ensure a certain linear filter (involving parametrical uncertainties related to unmodelled dynamics) maintains the output stationarity of any stationary random input signal, as in the nominal situation. Partial results concerning robustness are obtained from stability considerations. In any case, a priori knowledge on the unmodelled dynamics is not available for the implementation of the control law.     

A global robust iterative learning position control for current-fed permanent magnet step motors

The tracking control problem via state feedback for uncertain current-fed permanent magnet step motors with non-sinusoidal flux distribution and uncertain position-dependent load torque is addressed: a periodic reference signal (of known period) for the rotor position is required to be tracked. A robust iterative learning control algorithm is designed which, for any motor initial condition and without requiring any resetting procedure, guarantees, despite system uncertainties: exponential convergence of the rotor position tracking error to a residual ball (centered at the origin) whose radius can be made arbitrarily small by properly setting the learning gain; asymptotic convergence of the rotor position tracking error to zero. A sufficient condition for the asymptotic estimation of the uncertain reference input achieving, for compatible initial conditions, perfect tracking is derived. Robustness with respect to a finite memory implementation of the control algorithm based on the piecewise linear approximation theory is shown to be guaranteed; satisfactory performances of a discrete-time implementation of the control algorithm are obtained in realistic simulations for the full-order voltage-fed motor.     

A robust adaptive dynamic surface control for linear systems

In this article, a robust output-feedback adaptive dynamic surface control (DSC) is proposed for linear time-invariant single-input single-output plants with unmodelled dynamics and unmeasurable output disturbance. With the proposed adaptive DSC scheme, the ‘explosion of terms’ problem inherent in backstepping control is eliminated and the adaptive law is necessary only at the first design step, which significantly reduces the design procedure. More importantly, it is proved that with an initialisation technique, the ?_∞ performance of the tracking error can be guaranteed even with unmodelled dynamics, bounded output disturbance exists and the plant high-frequency gain is unknown.     

Finite-dimensional decentralized VS-MRAC of non-linear interconnected distributed parameter systems

We propose a design method for finite-dimensional decentralized VS-MRAC of a class of large-scale non-linear interconnected distributed parameter systems with bounded input and output disturbances. Each equivalent control is approximated by each average control and the norm of the output error vector can be made asymptotically arbitrarily small without the ?-matrix condition, independently of the reference inputs and in spite of the presence of non-linear interconnections, unmodelled dynamics and disturbances. Furthermore, it is assured that all signals in the closed-loop system are globally ultimately uniformly bounded. Finally, we show the effectiveness of the proposed method by using a numerical example.     

Adaptive decentralized finite‐time output tracking control for MIMO interconnected nonlinear systems with output constraints and actuator faults

In this work, we present a novel adaptive decentralized finite‐time fault‐tolerant control algorithm for a class of multi‐input–multi‐output interconnected nonlinear systems with output constraint requirements for each vertex. The actuator for each system can be subject to unknown multiplicative and additive faults. Parametric system uncertainties that model the system dynamics for each vertex can be effectively dealt with by the proposed control scheme. The control input gain functions of the nonlinear systems can be not fully known and state dependent. Backstepping design with a tan‐type barrier Lyapunov function and a new structure of stabilizing function is presented. We show that under the proposed control scheme, with the use of graph theory, finite‐time convergence of the system output tracking error into a small set around zero is guaranteed for each vertex, while the time‐varying constraint requirement on the system output tracking error for each vertex will not be violated during operation. An illustrative example on 2 interacting 2‐degree‐of‐freedom robot manipulators is presented in the end to further demonstrate the effectiveness of the proposed control scheme.     

不确定性R¨ossler 系统的自适应鲁棒跟踪控制

研究具有外部不确定性R¨ossler 混沌系统的鲁棒跟踪控制问题. 基于动态面控制原理设计自适应鲁棒控制器, 给出了系统参数的自适应更新律, 使得被控闭环系统的各误差变量一致有界. 系统输出曲线渐近跟踪任意期望轨道, 且跟踪误差能被控制在任意小的范围内, 而无须知道系统的参数及外部不确定性的界限. 基于稳定理论给出了具体的稳定性分析, 并通过数值仿真验证了该方法的有效性及鲁棒性.

     

具有一般不确定性的非线性系统的鲁棒输出反馈控制

为将文献「１」中结果推广到具有一般不确定性的系统并降低在过渡阶段所需要的控制量,通过引入新的正则信号和一些正光滑设计函数来处理状态估计误差和不确定性,设计了鲁棒输出反馈控制器,它能保证闭环系统信号的全局有界性,并使输出跟踪误差任意小,仿真说明,应用本文控制器,获得的性能更好,所需控制量要小。     

Adaptive finite‐time fault‐tolerant tracking control for a class of MIMO nonlinear systems with output constraints

In this work, we present a novel adaptive finite‐time fault‐tolerant control algorithm for a class of multi‐input multi‐output nonlinear systems with constraint requirement on the system output tracking error. Both parametric and nonparametric system uncertainties can be effectively dealt with by the proposed control scheme. The gain functions of the nonlinear systems under discussion, especially the control input gain function, can be not fully known and state‐dependent. Backstepping design with a tan‐type barrier Lyapunov function and a new structure of stabilizing function is presented. We show that under the proposed control scheme, finite‐time convergence of the output tracking error into a small set around zero is guaranteed, while the constraint requirement on the system output tracking error will not be violated during operation. An illustrative example on a robot manipulator model is presented in the end to further demonstrate the effectiveness of the proposed control scheme. Copyright © 2016 John Wiley & Sons, Ltd.     

带有未建模动态的船舶减摇鳍的鲁棒自适应控制

针对船舶减摇鳍非线性数学模型,提出一种鲁棒自适应控制器,可以用于存在非线性不确定、未知有界扰动和未建模动态的情况。应用Lyapunov稳定性理论证明,所提出的鲁棒自适应控制器可保证整个非线性系统的稳定性,且通过适当选择设计参数,可使跟踪误差达到任意精度。仿真结果表明了所提方法的有效性。     

Adaptive learning control of linear systems by output error feedback

This paper addresses the problem of designing an output error feedback tracking control for single-input, single-output uncertain linear systems when the reference output signal is smooth and periodic with known period T. The considered systems are required to be observable, minimum phase, with known relative degree and known high frequency gain sign. By developing in Fourier series expansion a suitable unknown periodic input reference signal, an output error feedback adaptive learning control is designed which ‘learns’ the input reference signal by identifying its Fourier coefficients: bounded closed-loop signals and global exponential tracking of both the input and the output reference signals are obtained when the Fourier series expansion is finite, while global exponential convergence of the input and output tracking errors into arbitrarily small residual sets is achieved otherwise. The structure of the proposed controller depends only on the relative degree, the reference signal period, the high frequency gain sign and the number of estimated Fourier coefficients.     

带前置滤波器的MRAC系统的变结构控制

变结构控制对参数不确定性,外部干扰和未建模动态具有鲁棒性,并被应用到鲁棒模型参考自适应系统.其缺点是易产生抖振.本文设计一种带有前置滤波器的变结构控制器,改善系统动态性能并消除了抖振.前置滤波器使带有符号函数的控制切换产生连续可测信号,实际控制律是光滑的.控制器设计和不确定性估计中引入辅助信号和带有记忆功能的正规化信号,适当选取控制器参数,所设计的控制器保证了闭环系统稳定性和任意小的跟踪误差.仿真结果表明该算法是有效的.     

Sliding mode control of singularly perturbed systems and its application in quad-rotors

This paper presents a sliding mode control scheme for tracking control of nonlinear singularly perturbed systems in the presence of model errors and external disturbances. A dual-loop feedback control is developed to provide accurate tracking capability and sufficient robustness to system uncertainties. A sliding mode controller is proposed in the outer-loop feedback design such that the plant states are stabilised for given reference trajectories, while an additional robust controller is designed in the inner loop to increase the adaptability to uncertainties, and reduce the effect of unmodelled high-frequency dynamics on plant dynamics. An appealing feature of the control scheme is the attenuation of chattering. The effectiveness and merits of the new control scheme developed are shown via a verification example of velocity control of a quad-rotor.