基于自适应AGBFN的不确定非线性系统的跟踪控制

针对一类具有未知不确定性的非线性系统,提出了一种基于观测器的自适应不对称高斯基函数网络(AGBFN)跟踪控制方案.当系统只有输出可以测量时,通过设计观测器对其进行在线状态估计,进而构造反馈控制律和自适应控制律.所提出的完全自适应AGBFN,可以在线更新网络所有参数,克服了传统RBF网络对称性约束,提高了网络的适应性和学习能力,可以有效地对消系统未知不确定项的影响.证明了闭环系统所有误差信号最终一致有界,且系统输出较好地跟踪参考模型输出.仿真结果表明了所提出方法的有效性.     

基于神经网络的一类非线性系统自适应输出跟踪

针对一类未知非线性系统,提出了一种输出反馈控制方法.首先,在假设系统状态已 知情况下设计状态反馈控制器,实现跟踪性能;然后,在系统状态不完全可测的情况下,通过 设计高增益观测器对系统的状态进行估计,实现输出反馈控制器设计,证明了所设计的输出 反馈控制器可以获得状态反馈控制器的性能.     

一类非三性系统的间接自适应输出反馈模糊控制

针对一为未知非线性系统,提出一种输出反馈控制方法。首先在假设系统状态已知的情况下设计状态反馈控制器,实现跟踪性能。然后在系统状态下不完全可测的情况下,通过设计高增益观测器对系统的状态进行估计,实现输出反馈控制器设计。最后证明所设计的输出反馈控制器可获得状态反馈控制器所取得的最大最小问题的跟踪性能。     

一类非线性系统的间接自适应输出反馈模糊控制

针对一类未知非线性系统,提出一种输出反馈控制方法。首先在假设系统状态已知的情况下设计状态反馈控制器,实现跟踪性能。然后在系统状态不完全可测的情况下,通过设计高增益观测器对系统的状态进行估计,实现输出反馈控制器设计。最后证明所设计的输出反馈控制器可获得状态反馈控制器所取得的最大最小问题的跟踪性能。     

带有未知虚拟控制增益符号的自适应输出反馈控制

针对带有未知虚拟控制增益符号的一类非线性系统。采用基于参数的坐标变换和参数重定义。将该系统转化为参数输出反馈形式。从而将未知的虚拟控制增益归入高频控制增益中．由于该高频控制增益符号未知。将Nussbaum增益技术融入自适应Backstepping方法中设计自适应输出反馈控制器．采用调节函数法设计参数自适应律以避免过参数估计．该方法所设计的自适应输出反馈控制器可确保闭环系统的所有信号一致有界。且跟踪误差渐近收敛．仿真研究表明了该设计方法的有效性．     

离散时间部分状态反馈模型参考自适应控制

本文针对线性不确定性系统, 给出了部分状态反馈直接模型参考自适应控制设计方案以及详细的系统稳 定性、输出跟踪性能分析. 控制器设计基于降维观测器和参数化方法. 此方案采用反馈控制, 反馈信号不仅仅依赖 全状态信息或者输出信号, 而是任意不超过系统维数的可测信号. 因此, 部分状态反馈控制是包含状态反馈、输出 反馈控制的新的控制方案, 缓解了状态反馈对状态信息的限制, 降低了输出反馈控制结构的复杂性. 通过引入辅助 信号, 本文证明了输出匹配条件的存在性、所有闭环系统信号的有界性以及渐近输出跟踪性能. 仿真结果验证了该 方案的有效性.     

多变量非线性系统的间接模糊输出反馈自适应控制

针对一类多输入多输出非线性不确定系统，提出一种基于观测器的模糊间接自适应控制方法，并基于李亚普诺夫函数方法，导出了输出反馈控制律以及参数的自适应律，证明了整个控制方案不但能保证闭环系统稳定，而且取得了良好的跟踪控制性能。     

含执行机构未知动态的液压伺服系统输出反馈控制

针对含有未知动态(如:执行机构、负载等)液压伺服系统,提出一种基于未知系统动态估计器的输出反馈控制方法.该方法不依赖于函数逼近器和传统反步控制设计,且无需难以测量的系统内部状态.首先,为避免反步控制和系统全部状态,引入等价变换,将含液压执行机构的伺服系统高阶严格反馈模型转化为Brunovsky标准型,进而运用高阶滑模微分器观测转化后的系统未知状态.控制器设计中引入描述收敛速率、最大超调量和稳态误差的性能函数,保证预设控制系统稳态和瞬态控制性能.为补偿系统集总未知动态影响,设计一种仅含一个调节参数并保证指数收敛的未知系统动态估计器.该输出反馈控制器可以实现对系统输出的精确跟踪控制.最后,通过数值仿真结果表明了所提出算法的有效性.     

高阶不确定非线性系统的线性自抗扰控制

针对一类具有内部动态和外部扰动未知的SISO高阶非线性系统,提出一种通用的线性自抗扰控制方案.该方案基于单参数调节的高增益观测器思想,分别设计线性跟踪微分器、线性扩张状态观测器和线性状态误差反馈控制律.利用Lagrange中值定理和Cauchy-Schwarz不等式将系统总扰动的微分值转化为关于系统估计和跟踪误差的函数,可以解决因系统控制增益未知所导致的控制量微分值难以预先确定的问题.在此基础上,基于Lyapunov稳定性定理证明闭环系统误差信号有界,并进一步分析得到系统估计和跟踪误差与控制器参数的定量关系,即都可以随观测器增益的增大而达到无限小.仿真比较结果验证了所提出方案的有效性,与韩式自抗扰控制方案相比,该方案结构简单,调节参数少,易于工程实现.     

一类非线性系统的模糊自适应滑模输出反馈控制

针对一类非线性系统，提出一种新的模糊自适应滑模输出反馈控制方法，该方法不需要非线性系统的状态可测的假设。基于李亚普诺夫函数方法，给出了模糊自适应输出反馈控制律以及在线调节的参数自适应律，证明了模物闭环系统的稳定性和跟踪误差的收敛性。     

随机Marino-Tomei系统的输出反馈鲁棒自适应跟踪

研究了一类Marino-Tomei非线性模型在不确定噪声干扰下的输出反馈鲁棒自适应跟 踪问题.通过滤波变换,采用随机控制Lyapunov设计方法,对于受方差未知的Wiener噪声干 扰的Marino-Tomei非线性系统,给出了参数自适应律和控制律,使得闭环系统成为噪声--状 态稳定的,并且跟踪误差的4次均方值在时间平均意义下收敛到一个足够小的区域内.     

Global adaptive output-feedback control of nonlinear systems. I.Linear parameterization

The problem of designing global adaptive output-feedback tracking controls for single-input single-output nonlinear systems which are linear with respect to the input and an unknown constant parameter vector is addressed. A class of systems which can be globally controlled by adaptive observer-based output-feedback compensators is identified by geometric coordinate-free conditions. The nonlinearities depend on the output only: growth conditions are not required. Each system in the class admits observers with linear error dynamics and is minimum phase, i.e., it has linear asymptotically stable zero dynamics. When the parameters are known, new sufficient conditions for global output-feedback tracking control are obtained as a special case. For linear systems the result recovers a well-known fundamental adaptive result. Three examples are discussed     

Robust adaptive output-feedback control for a class of nonlinear systems with general uncertainties

This paper investigates the robust adaptive output-feedback control for a class of nonlinear systems with general uncertainties and unknown parameters. First, a stable state observer is constructed and the system state is observed, and then the adaptive output-feedback controller is constructively designed for tracking the given reference signal. It is proven that the constructed controller is robust to the uncertainties of both the unknown parameters and the system states. These results show that the global stability of the resulting closed-loop systems has been guaranteed and the ε-tracking problem has been solved. Meanwhile, it is also proven that the tracking error tends to a ‘steady state’ at the negative exponential attenuating rate. Simulation examples show that the tracking effects of the designed adaptive control systems are good, and the control quantities used in the simulation examples are always within the range of the admissible control.     

非线性严格反馈系统自适应非反步输出反馈控制

针对传统反步控制器设计方法存在复杂度爆炸、参数收敛难、控制奇异、需全系统状态已知等问题,提出一种新的可保证参数收敛的未知系统动态辨识和非反步输出反馈自适应控制方法.首先,通过定义新的状态变量和系统等价变换,将严格反馈系统状态反馈控制转化为标准系统的输出反馈控制,进而设计包含高阶微分器的自适应单步控制器,避免反步递推设计的问题;然后,采用两个神经网络对系统集总未知动态进行估计,避免传统控制方法在未知控制增益在线估计过零引发的奇异问题;最后,构造一种新的自适应算法在线更新神经网络权值确保其收敛到真实值,进而实现对未知系统动态的精准辨识.基于Lyapunov定理的分析表明,跟踪误差和估计误差均可收敛到零点附近紧集.基于液压伺服系统模型的对比仿真验证了所提出方法的有效性和优越性.     

Quasi-min-max output-feedback model predictive control for LPV systems with input saturation

In the research field of model predictive control (MPC), an output-feedback-type MPC method is consistently required for controlling a wide range of constrained systems. In this paper, we propose a two-stage control strategy for polytopic linear parameter varying (LPV) systems subject to input constraints. This strategy consists of a modified quasi-min-max output-feedback MPC method and a novel terminal output-feedback robust control technique. The proposed control mechanism involves the system states to be first controlled via the MPC method to be driven into a prescribed neighborhood of the origin, and then, the terminal output-feedback robust control method guaranteeing the input constraints is applied to make such states converge to the origin. It is also verified that our control method guarantees the closed-loop stability and feasibility in the presence of model uncertainties and input constraints. Finally, a numerical example is given to demonstrate its effectiveness.     

Global adaptive output-feedback control of nonlinear systems. II.Nonlinear parameterization

For pt.I, see ibid., p.17-32 (1993). The problem of designing global output-feedback robust stabilizing controls for a class of single-input single-output minimum-phase uncertain nonlinear systems with known and constant relative degree is addressed. They are assumed to be linear with respect to the input and nonlinear with respect to an unknown constant parameter vector. The nonlinearities depend on the output only. The nonlinearities may be uncertain and are only required to be bounded by known smooth functions. The order of the robust compensator is equal to the relative degree minus one and is static when the relative degree is one. A self-tuning version of the robust control capable of achieving set point regulation is developed in which the control gains are tuned by an output-feedback adaptive algorithm. When the parameter vector enters linearly, the self-tuning regulator does not require the knowledge of parameter bounds and guarantees set point regulation for the same class of systems considered in Part I     

Simple robust output-feedback controller for uncertain nonlinearsystems

A robust output-feedback controller is designed by using an observer plus backstepping procedure to solve the tracking problems of a class of uncertain nonlinear systems. In the design procedure, three techniques are applied: a) a single filter whose dynamic order is the same as the system order is constructed; b) a normalization signal is introduced; c) positive nonlinear functions that are used to generate the normalization signal and to construct nonlinear damping terms can be chosen freely. The designed controller has a very simple structure and can be applied to track much broader classes of reference signals. It can guarantee the global boundness of all closed-loop signals and make the output tracking error arbitrarily small. Technique c) may provide the designer with the possibility to find a better choice of positive nonlinear functions for our controller to achieve similar tracking performance with less control effort     

An adaptive variable structure control for a class of nonlinear systems

Motivated by the recent advance in adaptive output-feedback control for a class of nonlinear systems which can be transformed into the so-called output-feedback form [7,10,11], an adaptive structure controller is proposed in this paper to solve the nonlinear model reference adaptive control problem. It is shown that an asymptotic output tracking performance can be achieved for this class of nonlinear system even if some nonlinearity is not available or some unknown parameters are fast time-varying.     

Global output feedback tracking for nonlinear systems in generalized output-feedback canonical form

A global output feedback dynamic compensator is proposed for stabilization and tracking of a class of systems that are globally diffeomorphic into systems which are in generalized output-feedback canonical form. This form includes as special cases the standard output-feedback canonical form and various other forms considered previously in the literature. Output-dependent nonlinearities are allowed to enter both additively and multiplicatively. Under the assumption that a constant matrix can be found to achieve a certain property, it is shown that a reduced-order observer and a backstepping controller can be designed to achieve asymptotic tracking. For the special case of linear systems, the designed dynamic controller reduces to the standard reduced-order observer and linear controller. This is the first global output-feedback tracking results for this class of systems.