不确定非线性系统的鲁棒自适应输出反馈控制

基于自适应非线性阻尼,提出一种鲁棒自适应输出反馈控制方法。该方法适用于带有未建模动态、未知非线性、有界扰动、未知非线性参数和不确定控制系数的多输入多输出非线性系统。理论证明,在一定的假设条件下,该方法能保证闭环系统所有动态信号有界;不论有多少不确定非线性参数、多高阶的非线性系统,只需要一个自适应控制参数和观察参数;而且通过选择适当的控制器和观测器参数,能使控制误差和估计误差达到任意小。仿真结果表明了所提出方法的有效性。     

基于神经网络MIMO非线性系统自适应输出反馈控制

针对一类具有对象不确定和外部干扰的MIMO(多输入多输出)非线性系统提出了自适应鲁棒输出跟踪控制方案.使用了高斯径向基神经网络自适应补偿对象非线性,高增益观测器被用来估计不能直接测量的输出导数.此方法所设计的控制器不仅保证闭环系统稳定,而且所有状态有界以及跟踪误差一致终值有界.仿真结果充分表明了该方案的有效性和可行性.     

冷带轧机厚控系统自适应鲁棒输出反馈动态控制器设计

冷带轧机厚控系统可被认为是一个受外界干扰的线性不确定时滞系统.本文首先设计了标称系统下的鲁棒输出反馈动态控制器,以改善闭环系统的动静态性能;其次,在系统不需要满足不确定性匹配条件的情况下,将参数和外部扰动不确定性综合考虑.应用Lyapunov稳定性理论设计了系统不确定性上界参数的自适应估计器和系统的自适应控制器,保证了闭环系统的渐近稳定性,减小了设计的保守性;两者结合实现了板带出口厚度的有效控制.最后通过一个仿真实例说明本文所提出的自适应鲁棒控制器的有效性.     

Output‐feedback robust adaptive backstepping control for a class of multivariable nonlinear systems with guaranteed tracking performance

This paper is devoted to output‐feedback adaptive control for a class of multivariable nonlinear systems with both unknown parameters and unknown nonlinear functions. Under the Hurwitz condition for the high‐frequency gain matrix, a robust adaptive backstepping control scheme is proposed, which is able to guarantee the tracking performance and needs only one parameter to be updated online regardless of the system order and input–output dimension. To cope with the unknown nonlinear functions and improve the tracking performance, a kind of high‐gain K‐filters is introduced. It is proved that all signals of the closed‐loop system are globally uniformly bounded. Simulation results on coupled inverted double pendulums are presented to illustrate the effectiveness of the proposed scheme. Copyright © 2012 John Wiley & Sons, Ltd.     

Robust adaptive output feedback control for uncertain nonlinear systems with quantized input

In this paper, we study the input quantization problem for a class of uncertain nonlinear systems. The quantizer adopted belongs to a class of sector‐bounded quantizers, which basically include all the currently available static quantizers. Different from the existing results, the quantized input signal, rather than the input signal itself, is used to design the state observers, which guarantees that the state estimation errors will eventually converge to zero. Because the resulting system may be discontinuous and non‐smooth, the existence of the solution in the classical sense is not guaranteed. To cope with this problem, we utilize the non‐smooth analysis techniques and consider the Filippov solutions. A robust way based on the sector bound property of the quantizers is used to handle the quantization errors such that certain restrictive conditions in the existing results are removed and the problem of output feedback control with input signal quantized by logarithmic (or hysteresis) quantizers is solved for the first time. The designed controller guarantees that all the closed‐loop signals are globally bounded and the tracking error exponentially converges towards a small region around zero, which is adjustable. Copyright © 2016 John Wiley & Sons, Ltd.     

Insensitive and robust control design via output feedback eigenstructure assignment

Insensitive and robust control design using output‐feedback eigenstructure assignment for linear multivariable systems is considered in this paper. A parametric expression of closed‐loop eigenvectors and generalized eigenvectors is developed. It can cope with the case where the closed‐loop eigenvalues are multiple and/or the same as the open‐loop ones so that the system to be designed can be uncontrollable and/or unobservable. The controller designed via output‐feedback eigenstructure assignment is expressed by proposed parameter vectors. The freedom provided by output‐feedback eigenstructure assignment is used to optimize some performance functions which are used to measure the sensitivity of the closed‐loop matrix and the robustness of the closed‐loop system. Copyright © 2000 John Wiley & Sons, Ltd.     

基于自适应Backstepping设计的TCSC非线性鲁棒控制器

电力系统是强非线性的动态大系统,在运行中总要受到外部干扰和内部干扰的影响,从而对其稳定运行造成严重威胁.本文针对带有TCSC单机无穷大母线系统的三阶鲁棒模型,在考虑阻尼系数未知及系统受外部扰动的情况下,将自适应backstepping方法与非线性L₂增益干扰抑制理论融合,构造出系统的存贮函数,并获得非线性自适应鲁棒控制器及参数替换律.所得控制器不仅能够保证系统状态有界,而且能够有效抑制干扰对系统输出的影响.通过对单机系统的仿真结果表明采用该方法的控制器优于传统的控制器.     

降阶的鲁棒分散自适应反推控制

针对一类含有未建模动态的关联系统,考虑了降阶的鲁棒分散自适应反推控制问题.首先通过一系列坐标变换,将原系统重新参数化,然后引入降阶观测器,得到一个误差系统.基于该系统,给出了一种降阶自适应反推控制器的设计方案.证明了自适应控制系统的所有信号全局一致有界,调节误差渐近收敛到零.控制器阶次的降低使得本文的设计方案更具应用价值.     

Robust adaptive tracking of uncertain nonlinear systems by output feedback

We investigate the problem of robust adaptive tracking by output feedback for a class of uncertain nonlinear systems. Based on the high‐gain scaling technique and a new adaptive law, a linear‐like output feedback controller is constructed. Only one dynamic gain is designed, which makes the controller easier to implement. Furthermore, by modifying the update law, the adaptive controller is robust to bounded external disturbance and is able to guarantee the convergence of the output tracking error to an arbitrarily small residual set. A numerical example is used to illustrate the effectiveness of the proposed method. Copyright © 2015 John Wiley & Sons, Ltd.     

Constraint adaptive output regulation of output feedback systems with application to electrostatic torsional micromirror

This paper studies a constraint adaptive output regulation design for a class of nonlinear systems with an unknown exosystem by output feedback control. First, by introducing an internal model with some known design parameter, our concerned problem may be formulated as a specific regulation problem with output constraint. Then, the barrier Lyapunov function technique is further integrated to approach the problem. It is shown that such a constraint adaptive output regulation problem is solvable without constraint violation. In particular, the constructed regulator cannot only keep the boundedness of the closed‐loop system signals but also guarantees the parameter convergence for the unknown parameter vector in the exosystem. As an application, it is illustrated that our result is applicable in tracking the control of an electrostatic torsional micromirror with physical geometry constraint. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive neural output feedback finite-time command filtered backstepping control for nonlinear systems with full-state constraints

In this paper, an adaptive neural finite-time control method via barrier Lyapunov function, command filtered backstepping, and output feedback is proposed to solve the tracking problem of uncertain high-order nonlinear systems with full-state constraints and input saturation. By utilizing the neural network (NN) to approximate unknown nonlinear functions, the finite-time command filters are used to filtering the virtual control signals and get the intermediate control signals in a finite time in the backstepping process. Because there are errors between the output of finite-time command filters and the virtual control signals, the error compensation signals are added to eliminate the influence of filtering errors. Based on the proposed control scheme, the states of the system can be constrained in the predetermined region, all signals in the system are bounded in finite time, and the tracking error can converge to the desired region in finite time. At last, a simulation example is given to show the effectiveness of the proposed control method.     

Global robust practical output regulation for nonlinear systems in output feedback form by output‐based event‐triggered control

In this paper, we study the event‐triggered global robust practical output regulation problem for a class of nonlinear systems in output feedback form with any relative degree. Our approach consists of the following three steps. First, we design an internal model and an observer to form the so‐called extended augmented system. Second, we convert the original problem into the event‐triggered global robust practical stabilization problem of the extended augmented system. Third, we design an output‐based event‐triggered control law and a Zeno‐free output‐based event‐triggered mechanism to solve the stabilization problem, which, in turn, leads to the solvability of the original problem. Finally, we apply our result to the controlled hyperchaotic Lorenz systems.     

基于扩张观测器的欠驱动船舶轨迹跟踪低频学习自适应动态面输出反馈控制

针对速度不可测的三自由度欠驱动船舶轨迹跟踪控制问题,考虑船舶存在模型参数不确定项以及外界环境干扰未知情况,提出一种基于扩张观测器的欠驱动船舶轨迹跟踪低频学习自适应动态面输出反馈控制策略.该策略构造扩张观测器估计船舶速度向量,利用神经网络算法逼近模型参数不确定项,然后采用动态面控制技术避免对虚拟控制律直接求导,简化控制律计算过程,并引入低频增益学习技术消除外界扰动导致控制信号产生高频振荡,最后选取李雅普诺夫函数证明该控制律能够保证船舶跟踪闭环系统中所有误差信号一致最终有界.仿真结果表明,本文所设计控制器对船舶模型参数不确定项及外界环境干扰具有较强的鲁棒性,能够实现对船舶轨迹的有效跟踪.     

Robust adaptive output feedback control of a class of discrete‐time nonlinear systems with nonlinear uncertainties and unknown control directions

In this paper, robust adaptive output feedback control is studied for a class of discrete‐time nonlinear systems with functional nonlinear uncertainties of the Lipschitz type and unknown control directions. In order to construct an output feedback control, the system is transformed into the form of a nonlinear autoregressive moving average with eXogenous inputs (NARMAX) model. In order to avoid the noncausal problem in the control design, future output prediction laws and parameter update laws with the dead‐zone technique are constructed on the basis of the NARMAX model. With the employment of the predicted future outputs, a constructive output feedback adaptive control is proposed, where the discrete Nussbaum gain technique and the dead‐zone technique are used in parameter update laws. The effect of the functional nonlinear uncertainties is compensated for, such that an asymptotic tracking performance is achieved, whereas other signals in the closed‐loop systems are guaranteed to be bounded. Simulation studies are performed to demonstrate the effectiveness of the proposed approach. Copyright © 2012 John Wiley & Sons, Ltd.     

基于LMI的输出反馈鲁棒完整性控制器设计

完整性是容错控制的一个重要研究方向,不确定系统的鲁棒完整性研究具有很强的实际意义.本文基于[0,σ]故障模型和线性矩阵不等式(LMI)方法,提出了参数不确定系统的输出反馈鲁棒完整性控制器存在的充分条件,通过求解两个矩阵不等式获得控制器,使闭环系统在传感器发生故障时仍然保持二次稳定,并对参数不确定性具有鲁棒性.数值示例说明了该方法的有效性.     

一类非线性系统的微分平滑反步自适应输出反馈控制

研究了一类含不确定参数且存在未知扰动的严反馈非线性系统输出反馈控制问题,设计了一种新型的反步递推(Backstepping)自适应控制器.为实现输出反馈,设计过程引入了虚拟的全维状态观测器.由于Backstepping的虚拟控制量与未知参数逼近值及其高阶导数有关,为此通过微分平滑算法对原系统进行相应的动态扩展.在稳定性分析中,利用Lyapunov定理,得到了系统全局一致有界稳定的条件,并求出系统的稳态跟踪误差.最后给出的仿真算例验证了本文方法的有效性和可行性.     

线性不确定系统经动态输出反馈的分层次控制策略

利用李雅谱诺夫稳定理论及线性矩阵不等式(LMI)方法, 研究了具有非结构摄动的不确定连续系统经动态输出反馈的二次鲁棒能稳定问题. 推导出这类控制器存在的充分条件, 即一个拟线性矩阵不等式(Q-LMI)的形式, 给出了Q-LMI问题的基于LMI方法的求解步骤. 为了使得Q-LMI问题有解, 可引入一些LMI约束, 提高了Q-LMI问题的可解性. 基于Q-LMI条件, 揭示了系统不确定参数界与系统控制规模的关系, 提出了“不同的摄动实施不同规模的控制”的鲁棒能稳定的分层次控制策略. 最后, 通过一个例子说明了     

Adaptive backstepping output feedback control for SISO nonlinear system using fuzzy neural networks

In this paper, a new fuzzy-neural adaptive control approach is developed for a class of single-input and single-output （SISO） nonlinear systems with unmeasured states. Using fuzzy neural networks to approximate the unknown nonlinear functions, a fuzzy- neural adaptive observer is introduced for state estimation as well as system identification. Under the framework of the backstepping design, fuzzy-neural adaptive output feedback control is constructed recursively. It is proven that the proposed fuzzy adaptive control approach guarantees the global boundedness property for all the signals, driving the tracking error to a small neighbordhood of the origin. Simulation example is included to illustrate the effectiveness of the proposed approach.     

Distributed adaptive output feedback tracking control for a class of uncertain nonlinear multi-agent systems

This paper addresses the distributed output feedback tracking control problem for multi-agent systems with higher order nonlinear non-strict-feedback dynamics and directed communication graphs. The existing works usually design a distributed consensus controller using all the states of each agent, which are often immeasurable, especially in nonlinear systems. In this paper, based only on the relative output between itself and its neighbours, a distributed adaptive consensus control law is proposed for each agent using the backstepping technique and approximation technique of Fourier series (FS) to solve the output feedback tracking control problem of multi-agent systems. The FS structure is taken not only for tracking the unknown nonlinear dynamics but also the unknown derivatives of virtual controllers in the controller design procedure, which can therefore prevent virtual controllers from containing uncertain terms. The projection algorithm is applied to ensure that the estimated parameters remain in some known bounded sets. Lyapunov stability analysis shows that the proposed control law can guarantee that the output of each agent synchronises to the leader with bounded residual errors and that all the signals in the closed-loop system are uniformly ultimately bounded. Simulation results have verified the performance and feasibility of the proposed distributed adaptive control strategy.     

基于状态观测器的迟滞非线性系统输出反馈控制

利用Preisach模型与其边界线之间的映射关系建立了容易在线更新的迟滞模型．将模型和径向基网络相结合，针对一类动态多映射迟滞非线性系统设计了输出反馈控制器．应用LyaPunov定理得到系统控制律和神经网络权值更新律，从而保证了闭环系统的跟踪误差及网络权值偏差收敛到原点的某个有界邻域内．