基于Backstepping的倒立摆鲁棒跟踪控制

针对内部参数不确定及存在外部干扰的非线性倒立摆系统,提出了基于Backstepping方法的滑模变结构控制律,并且采用RBF神经网络逼近系统不确定非线性函数,同时引入滑模误差对其神经网络权值进行在线自适应调整,使神经网络的逼近速度加快,改善了动态性能.该控制律能保证倒立撰轨迹跟踪误差的快速收敛性以及对外部扰动和内部参数不确定的不敏感性,最后给出的仿真实例证明了该理论分析结果的正确性,控制效果良好.     

磁悬浮系统的基于RBF 网络的自适应反推控制

针对一类磁悬浮系统,研究了基于RBF网络的自适应反推控制器的设计和分析问题.首先在较弱的条件下,通过引入一监督控制,保证了闭环系统的状态落入一紧集中;然后通过RBF网络的逼近性质和反推设计技术,给出了一种鲁棒自适应控制器的设计;最后利用Lyapunov稳定性理论,严格地分析了这种自适应控制系统的稳定性和跟踪性能.     

一类二阶时变非线性系统的混合自适应重复学习控制

针对含有时变和时不变未知参数的二阶非线性系统,结合Backstepping方法．提出了一种新的自适应重复学习控制方法,可处理参数在一个未知紧集内周期性快时变的非线性系统．通过引入参数周期自适应律．设计出的自适应控制策略．使跟踪误差平方在一个周期上的积分范敷渐近收敛于零．通过构造Lyapunov函数．给出了闭环系统收敛的一个充分条件．     

Robust decentralized adaptive stabilization for a class of interconnected systems

The robust decentralized adaptive output-feedback stabilization for a class of interconnected systems with static and dynamic interconnections by using the MT-filters and backstepping design method is studied. By introducing a new filtered tramfomnation, the adaptive laws were derived for measurement. Under the assurnption of the nonlinear growth conditions imposed on the nonlinear interconnections and by constructing the error system and using a new proof method, the global stability of the closed-loop system was effectively analyzed, and the exponential convergence of all the signals except for parameter estimates were guaranteed.     

Adaptive L2 control of nonlinear systems using neural networks

An adaptive neural network controller is developed to achieve output-tracking of a class of nonlinear systems. The global L2 stability of the closed-loop system is established. The proposed control design overcomes the limitation of the conventional adaptive neural control design where the modeling error brought by neural networks is assumed to be bounded over a compact set.Moreover,the generalized matching conditions are also relaxed in the proposed L2 control design as the gains for the external disturbances entering the system are allowed to have unknown upper bounds.     

基于反步法的一类非线性切换系统控制器设计

研究一类子系统是纯反馈非线性系统的切换系统控制器设计问题．基于多Lyapunov函数和反步法,提出一种状态反馈控制律及切换规则设计方法。通过递推设计可得到使非线性切换系统稳定的反馈控制律和切换规则．将所提出的方法应用于该类非线性切换系统含有不确定性的情形,仿真算例结果表明了所提出方法的有效性．     

Buck 型直流变换器的自适应动态面控制研究

基于脉冲宽度调制(PWM)原理工作的Buck 型直流变换器的平均模型, 利用非线性自适应动态面控制方法设计控制器, 用来驱动一类Buck 型直流变换器工作, 使其输出电压能准确地跟踪参考电压, 以及对负载参数的不确定性具有很强的鲁棒性和自适应性。非线性自适应动态面控制是非线性系统自适应反步控制的一种简化算法, 设计过程中引入n - 1 个一阶滤波器, 克服了反步方法对虚拟控制求导而引起的方程项数的膨胀问题和对模型非线性求导的问题。只要滤波时间足够小(现代的计算机完全能够满足), 选择合适的表面增益, 该方法设计的控制器, 简单且易于实现, 并可保证系统是半全局稳定的, 完全能够满足工程上的要求。该控制器的有效性, 通过仿真实例获得验证。     

Robust adaptive output stabilization using dynamic normalizing signal

For a class of nonlinear systems with dynamic uncertainties, robust adaptive stabilization problem is considered in this paper. Firstly, by introducing an observer, an augmented system is obtained. Based on the system, we construct an exp-ISpS Lyapunov function for the unmodeled dynamics, prove that the unmodeled dynamics is exp-ISpS, and then obtain a dynamic normalizing signal to counteract the dynamic disturbances. By the backstepping technique, an adaptive controller is given, it is proved that all the signals in the adaptive control system are globally uniformly ultimately bounded, and the output can be regulated to the origin with any prescribed accuracy. A simulation example further demonstrates the efficiency of the control scheme.