基于未知高频增益的非线性系统自适应迭代学习控制

针对一类单输入单输出不确定非线性重复跟踪系统，提出一种基于完全未知高频反馈增益的自适应迭代学习控制，与普通迭代学习控制需要复习增益稳定性前提条不同，自适应迭代学习控制通过不断修改Nussbaum形式的高频学习增益达到收敛，经证明当迭代次数i→∞时，重复跟踪误差可一致收敛到任意小界δ。仿真结果表明了该控制方法的有效性。     

基于未知高频增益的非线性系统自适应迭代学习控制

针对一类单输入单输出不确定非线性重复跟踪系统,提出一种基于完全未知高频反馈增益的自适应迭代学习控制.与普通迭代学习控制需要学习增益稳定性前提条件不同,自适应迭代学习控制通过不断修改Nussbaum形式的高频学习增益达到收敛.经证明当迭代次数i→∞时,重复跟踪误差可一致收敛到任意小界δ.仿真结果表明了该控制方法的有效性.     

控制增益未知的船舶航向非线性自适应跟踪控制

针对参数不确定的船舶运动非线性控制系统控制方向未知的困难,将逆推算法与Nussbaum增益方法相结合,提出一种新的自适应非线性控制策略,从而实现船舶运动航向跟踪控制.首先,从理论上证明了所设计的自适应控制器保证最终的控制系数符号未知的参数不确定船舶运动非线性系统中所有信号一致有界,船舶的实际航向全局自适应地渐近跟踪期望的参考航向.对两条船舶数学模型的仿真实验结果表明,所设计的自适应非线性跟踪控制器具有良好的适应性及鲁棒性.     

基于未知控制增益的非线性系统自适应迭代反馈控制

针对一类单输入单输出不确定非线性重复跟踪系统, 提出一种基于完全未知控制增益的自适应迭代反馈控制. 与普通迭代学习控制需要学习增益稳定性前提条件不同, 所提自适应迭代反馈控制律通过不断修改Nuss baum形式的反馈增益达到收敛. 证明当迭代次数i→δ时, 重复跟踪误差可一致收敛到任意小界δ. 仿真显示了所提控制方法的有效性.     

具有未知高频增益的鲁棒自适应反推控制器

在高频增益未知的情况下,对一类带有未建模动态和输入、输出干扰的系统,给出了一种基于反推技术的鲁棒自适应控制器的设计方法.通过修正传统鲁棒自适应控制中的动态规范化信号和切换-σ算法,证明了闭环系统的所有信号都有界,同时可以取得较好的跟踪性能.仿真结果表明了该方法的有效性.     

高频增益符号未知时的变结构模型参考自适应控制

解决了对象相对阶大于1、高频增益符号未知时的变结构模型参考自适应控制(VS-MRAC)问题．提出了一种基于监控函数的控制信号切换律, 证明只需要对首个辅助误差构造监控函数, 就可决定控制信号的切换时间;进而, 在监控函数的管理下, 控制信号经至多有限次切换后将停止切换, 闭环系统所有信号一致有界, 跟踪误差将收敛到一个残集内, 且该残集可通过减小某些设计参数而变得任意小．特别地, 我们证明, 若系统的某些初始条件为零, 则至多只需要一次切换．     

一类函数完全未知的随机非线性系统自适应H∞跟踪控制

针对一类函数完全未知的严格反馈随机非线性系统,提出了一种基于backstepping技术的鲁棒H_∞自适应神经跟踪控制器设计的新方法.该方法可在随机非线性系统是依概率一致最终有界的情况下,保证随机非线性系统H_∞性能指标,且H_∞踪踪控制器容易获得.同时该方法去除了一些文献中神经网络逼近误差需要平方可积的假设.文中使用径向基函数(radial basis function, RBF)神经网络逼近打包的未知非线性函数.所设计的控制器能够保证闭环系统跟踪误差及其它所有信号都是依概率有界的,且对外界干扰具有鲁棒H∞抑制作用.最后,仿真结果验证了所提方法的有效性和正确性.     

一类具有未知增长率非线性系统全局输出反馈实际跟踪

本文研究了一类仅跟踪误差可量测不确定非线性系统的全局输出反馈实际跟踪问题.不同于现有文献,该控制系统具有依赖于不可测状态的增长且增长率为未知常数,并且只要求被跟踪信号及其一阶导数有未知界,因此直接推广现有结果难以解决上述控制问题.受相关镇定结果的启发,并通过灵活运用广义控制(universal control)和死区(dead zone)的方法与技巧,本文设计了自适应输出反馈控制器.主要结果表明,所设计的控制器能够确保跟踪误差经有限时间后收敛于设定的原点的任意小邻域,同时闭环系统的所有信号皆有界.仿真算例验证了理论结果的有效性.     

控制方向未知的全状态约束非线性系统的鲁棒自适应跟踪控制

针对一类控制方向未知的含有时变不确定参数和未知时变有界扰动的全状态约束非线性系统,本文提出了一种基于障碍Lyapunov函数的反步自适应控制方法.障碍Lyapunov函数保证了系统状态在运行过程中始终保持在约束区间内;Nussbaum型函数的引入解决了系统控制方向未知的问题;光滑投影算法确保了不确定时变参数的有界性.障碍Lyapunov函数、Nussbaum型函数及光滑投影算法与反步自适应方法的有效结合首次解决了控制方向未知的全状态约束非线性系统的跟踪控制问题.所设计的自适应鲁棒控制器能在满足状态约束的前提下确保闭环系统的所有信号有界.通过恰当地选取设计参数,系统的跟踪误差将收敛于0的任意小的邻域内.仿真结果表明了控制方案的可行性.     

高频增益未知的受扰非线性系统输出反馈控制

针对一类具有未知定常参数,包括未知高频增益的受扰非线性最小相位系统,给出了一种鲁棒自适应输出反馈控制策略．系统所受的干扰假设有界,但其界值是未知的．通过采用自适应策略来对其界值进行在线估计,控制算法并不需要高频增益符号的先验知识．同时,系统中的非线性项并不要求满足增长性条件和匹配条件．算法使得估计参数量达到了最小,保证了闭环系统所有信号的有界性,同时使得跟踪误差渐近收敛于零．     

Adaptive fuzzy backstepping output feedback control of nonlinear time-delay systems with unknown high-frequency gain sign

In this paper, an adaptive fuzzy robust feedback control approach is proposed for a class of single-input and single-output (SISO) strict-feedback nonlinear systems with unknown nonlinear functions, time delays, unknown high-frequency gain sign, and without the measurements of the states. In the backstepping recursive design, fuzzy logic systems are employed to approximate the unknown smooth nonlinear functions, K-filters is designed to estimate the unmeasured states, and Nussbaum gain functions are introduced to solve the problem of unknown sign of high-frequency gain. By combining adaptive fuzzy control theory and adaptive backstepping design, a stable adaptive fuzzy output feedback control scheme is developed. It has been proven that the proposed adaptive fuzzy robust control approach can guarantee that all the signals of the closed-loop system are uniformly ultimately bounded and the tracking error can converge to a small neighborhood of the origin by appropriately choosing design parameters. Simulation results have shown the effectiveness of the proposed method.     

Adaptive quantised fault-tolerant tracking control of uncertain nonlinear systems with unknown control direction and the prescribed accuracy

In this paper, the problem of adaptive fault-tolerant tracking control for a class of uncertain nonlinear systems in the presence of input quantisation and unknown control direction is considered. By choosing a class of particular Nussbaum functions, an adaptive fault-tolerant control scheme is designed to compensate actuator faults and input quantisation while the control direction is unknown. Compared with the existing results, the proposed controller can directly compensate for the nonlinear term caused by actuator faults and the nonlinear decomposition on the quantiser without estimating its bound. Furthermore, via Barhalant's Lemma, it is proven that all the signals of the closed-loop system are globally uniformly bounded and the tracking error converges into a prescribed accuracy in prior. Finally, an illustrative example is used for verifying effectiveness of the proposed approach.     

Adaptive neural tracking control for a class of stochastic nonlinear systems

This paper investigates the problem of adaptive neural control design for a class of single‐input single‐output strict‐feedback stochastic nonlinear systems whose output is an known linear function. The radial basis function neural networks are used to approximate the nonlinearities, and adaptive backstepping technique is employed to construct controllers. It is shown that the proposed controller ensures that all signals of the closed‐loop system remain bounded in probability, and the tracking error converges to an arbitrarily small neighborhood around the origin in the sense of mean quartic value. The salient property of the proposed scheme is that only one adaptive parameter is needed to be tuned online. So, the computational burden is considerably alleviated. Finally, two numerical examples are used to demonstrate the effectiveness of the proposed approach. Copyright © 2012 John Wiley & Sons, Ltd.     

Adaptive tracking H-infinity control for switched nonlinear systems with unknown control gain sign

This paper addresses the adaptive tracking control scheme for switched nonlinear systems with unknown control gain sign. The approach relaxes the hypothesis that the upper bound of function control gain is known constant and the bounds of external disturbance and approximation errors of neural networks are known. RBF neural networks (NNs) are used to approximate unknown functions and an H-infinity controller is introduced to enhance robustness. The adaptive updating laws and the admissible switching signals have been derived from switched multiple Lyapunov function method. It’s proved that the resulting closed loop system is asymptotically Lyapunov stable such that the output tracking error performance and H-infinity disturbance attenuation level are well obtained. Finally, a simulation example of Forced Duffing systems is given to illustrate the effectiveness of the proposed control scheme and improve significantly the transient performance.     

Adaptive fuzzy dynamic surface control with prespecified tracking performance for a class of nonlinear systems

This paper aims at exploring an adaptive fuzzy dynamic surface control (DSC) with prespecified tracking performance for a class of nonlinear systems in strict‐feedback form. Incorporating DSC technique into fuzzy logic systems (FLSs), it is shown that the design procedure and the computational burden can be greatly reduced. Moreover, by introducing a performance function in controller design, the prespecified tracking performance, i.e. the convergence rate, the allowed maximum overshoot and the steady state error, can be achieved. Simulation results are presented to demonstrate the efficiency of the proposed scheme. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Adaptive output feedback control for a class of nonlinear systems with quantised input and output

This paper aims at addressing the problem of global adaptive stabilisation by output feedback for a class of nonlinear systems, in which both the input and output are logarithmically quantised. The nonlinear functions of the systems are not necessary to be completely known and contain time-varying parameters that belong to an unknown bounded set. Based on dynamic high-gain technique, a linear-like quantised controller computed from quantised output is constructed and a guideline is derived to select the parameters of the quantisers. It is proved that, with the proposed scheme, all the states of the system can be globally steered to the origin while keeping the other signals of the closed-loop system bounded.     

Adaptive output feedback control for a class of nonlinear uncertain systems with quantized input signal

In this paper, adaptive output feedback control for a class of nonlinear systems with quantized input is investigated. The nonlinearities of the nonlinear systems under consideration are assumed to satisfy linear growth condition on the unmeasured states multiplied by unknown growth rate and output polynomial function. By developing a dynamic high‐gain observer, a linear‐like output feedback controller is constructed, with which it is proved that the output of the quantized control system can be steered to within an arbitrarily small residual set while keeping all the other closed loop states bounded. In particular, if the growth rate is known, it is proved that all the states of the system can be steered to within an arbitrarily small neighborhood of the origin. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive fuzzy control for pure-feedback stochastic nonlinear systems with unknown dead-zone input

This paper is concerned with the problem of adaptive fuzzy output tracking control for a class of nonlinear pure-feedback stochastic systems with unknown dead-zone. Fuzzy logic systems in Mamdani type are used to approximate the unknown nonlinearities, then a novel adaptive fuzzy tracking controller is designed by using backstepping technique. The control scheme is systematically derived without requiring any information on the boundedness of dead-zone parameters (slopes and break-points) and the repeated differentiation of the virtual control signals. The proposed adaptive fuzzy controller guarantees that all the signals in the closed-loop system are bounded in probability and the system output eventually converges to a small neighbourhood of the desired reference signal in the sense of mean quartic value. Simulation results further illustrate the effectiveness of the proposed control scheme.