不确定性大系统的分散变结构自适应控制

提出一种适用于存在变化的子系统关联、系统参数摄动和外界干扰的不确定性线性大系统的分散变结构自适应控制方法。在控制律中引入一种对系统不确定扰动与关联的界的简单自适应算法，增强了控制系统对不可知系统不确定扰动的鲁棒性。所提出的控制方法具有较强的工程实用性。     

一类不确定动态系统的输出反馈模糊变结构控制*

对于一类具有非线性不确定性及外加干扰的系统，本文提出了一种模糊变结构控制方案，控制中只利用系统输出信号和一些辅助信号。利用李亚普诺夫方法，证明了闭环系统全局ＢＩＢＯ稳定，仿真表明该控制方案可回避通常滑控制中不可避免的颤动，且系统具有很强的鲁棒性。     

含时变不确定线性系统的自适应鲁棒跟踪控制

针对系统的不确定性和扰动满足匹配条件,不确定性界和扰动界未知的情形,讨论含时变不确定性线性系统的鲁棒跟踪问题。自适应控制器的设计不涉及确定性界和扰动界,运用变结构方法,可使带扰系统实现渐近跟踪。该方法适合一类较广泛的不确定系统,鲁棒性较强。仿真例子表明了该方法的有效性。     

基于云模型的变桨距系统积分滑模控制

针对具有参数变化和外加干扰的变桨距风力发电系统,提出了一种基于云模型的积分滑模控制。在滑模控制中引入误差项的积分,并用状态量代替误差的导数,消除传统滑模控制需要期望输出信号导数已知的假设;利用云模型的不确定性推理方法,动态地调节切换增益;利用积分的方法对切换增益进行估计,估计出系统中不确定因素的界,有效地削弱系统的抖振。仿真结果表明:该控制器用于风速高于额定风速以上的变桨距控制系统中,具有较好的控制品质,对系统参数的不确定和外部干扰具有很强的鲁棒性。     

具有不确定性的非线性系统的变结构控制

本文研究了具有不确定性非线性系统的鲁棒输出跟踪控制问题，考虑了对参数、建模不确定性及干扰的鲁棒性。这里的不确定性不需满足通常的匹配条件。通过构造一个Ｌｙａｐｕｎｏｖ函数，我们得到一个变结构控制器，并且证明了输出跟踪误差的收敛性。最后，给出了计算机仿真，结果表明本文提出的方法是有效的。     

转炉炉口微差压滑模变结构控制技术

针对宝钢梅山炼钢厂转炉煤气回收系统（OG系统）的工作现状以及转炉炉口微差压控制系统对象的非线性、时变、不确定性和干扰大的特点,采用具有强鲁棒性的滑模变结构控制策略,以克服系统的不确定性和增强抗干扰能力。对滑模变结构控制算法中存在的“抖振”问题,探讨了基于干扰观测补偿的滑模控制器的设计解决方案,通过仿真研究表明滑模变结构控制方法具有很强的鲁棒性,可有效地改善控制系统的动态响应品质。     

转炉炉口微差压滑模变结构控制技术

针对宝钢梅山炼钢厂转炉煤气回收系统(OG系统)的工作现状以及转炉炉口微差压控制系统对象的非线性、时变、不确定性和干扰大的特点,采用具有强鲁棒性的滑模变结构控制策略,以克服系统的不确定性和增强抗干扰能力.对滑模变结构控制算法中存在的"抖振"问题,探讨了基于干扰观测补偿的滑模控制器的设计解决方案,通过仿真研究表明滑模变结构控制方法具有很强的鲁棒性,可有效地改善控制系统的动态响应品质.     

基于模糊神经网络的滑模控制

研究了一类不确定性非线性系统的滑模变结构控制,提出了一种基于模糊神经网络（Ｆｕｚｚｙ Ｎｅｕｒａｌ Ｎｅｔｗｏｒｋｓ）的滑模变结构设计方法,设计了控制器的结构,利用动态反向传播算法实现滑模控制,这种方法与一般变结构控制相比不但具有强的鲁棒性而且还能有效地消除抖动现象,同时在设计中不需要知识系统中不确定性和扰动的上界,另外还运用Ｌｙａｐｕｎｏｖ函数从理论上分析上了系统的稳定性。仿真结果说明了本文所提     

一类不确定线性切换系统的鲁棒H∞滑模控制

对一类含有非匹配不确定性且有外部干扰的线性切换系统,研究了H∞滑模变结构控制问题.利用LMI技术和单Lyapunov函数方法,设计单H∞滑模面,切换律以及子系统的变结构控制器,确保了切换系统的闭环系统为鲁棒稳定,且具有H∞扰动衰减度γ.系统状态到达滑模面后,该滑模面成为切换系统的全局鲁棒滑模面,可提高系统的暂态性能和鲁棒性.仿真例子说明所提出设计方法的有效性.     

一类不确定线性系统的鲁棒自适应控制

针对一类同时具有匹配不确定性和不匹配政治面目 确定性的线性系统,首先采用李雅普诺夫稳定性定理,结合基于矩阵不等式的鲁棒控制器设计方法和变结构控制方法,设计鲁棒控制器,使得闭环系统是二次渐近稳定的,然后,利用自适应参数估计方法,设计具有匹配不确定性范数界估计能力的鲁棒自适应控制器,保证闭环系统的一致终结有界,在此基础上,进一步考虑系统中可能的未知不确定性,分析闭环系统的鲁棒性,并得到了相应的控制器设计方法。     

用于刚性机械手的无抖振快速终端滑模控制

提出一种用于刚性机械手的无抖振动终端滑模鲁棒控制器。快速终端滑模综合了终端滑模和传统线性滑模的优，能在有限时间内到达平衡点，并降低系统稳态误差。采用优化方法推导出系统的跟踪精度和用于消除抖振的饱和函数和函数宽度之间的数学关系。利用系统的参数化模型，可将参数的不确定部分从回归矩阵中分离出来.根据每个参数不确定范围设计鲁棒控制器。仿真结果证明了该方法的有效性。     

An adaptive full order sliding mode controller for mismatched uncertain systems

In this paper, an adaptive full order sliding mode (FOSM) controller is proposed for strict feedback nonlinear systems with mismatched uncertainties. The design objective of the controller is to track a specified trajectory in presence of significant mismatched uncertainties. In the first step the dynamic model for the first state is considered by the desired tracking signal. After the first step the desired dynamic model for each state is defined by the previous one. An adaptive tuning law is developed for the FOSM controller to deal with the bounded system uncertainty. The major advantages offered by this adaptive FOSM controller are that advanced knowledge about the upper bound of the system uncertainties is not a necessary requirement and the proposed method is an effective solution for the chattering elimination from the control signal. The controller is designed considering the full-order sliding surface. System robustness and the stability of the controller are proved by using the Lyapunov technique. A systematic adaptive step by step design method using the full order sliding surface for mismatched nonlinear systems is presented. Simulation results validate the effectiveness of the proposed control law.     

Adaptive backstepping sliding mode control with tuning functions for nonlinear uncertain systems

An adaptive backstepping tuning functions sliding mode controller is proposed for a class of strict-feedback nonlinear uncertain systems. In this control design, adaptive backstepping is used to deal with unknown or uncertain parameters and the matching condition restricting the Lyapunov based design. The main drawback of the Lyapunov based adaptive backstepping which is the overparametrisation is eliminated by the tuning functions. The adaptive backstepping tuning functions design is combined with the sliding mode control in order to overcome quickly varying parametric and unstructured uncertainties, and to obtain chattering free control. The proposed controller not only provides robustness property against uncertainty but also copes with the overparametrisation problem. Experimental results of the proposed controller are compared with those of the standard sliding mode controller. The proposed controller exhibits satisfactory transient performance, good estimates of the uncertain parameters, and less chattering.     

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.     

GBF-CMAC和滑模控制的柔性结构系统控制

针对一类不确定系统的跟踪控制,设计了一种将GBF-CMAC（cerebellar model articulation controller with Gauss basis function）与滑模控制相结合的控制系统。利用符号距离和分层结构减少了神经网络所需存储器的数量,并提出了一种神经网络参数的自适应学习律。将设计的控制器用于含有不确定性和欠驱动结构的高阶柔性直线结构系统的跟踪控制,并与一般滑模控制和积分滑模控制进行了比较。实验结果表明,所设计的控制器不仅具有较好的鲁棒性,而且改善了滑模控制存在的抖振问题。同时通过调整神经网络的参数对抖振进行控制,实现了抖振和跟踪性能之间的最优选择。     

Cascade fuzzy variable structure control of induction motor based on the approach of fuzzy modelling of Ben-Ghalia

In this article, a control design concept using fuzzy sets for an induction motor is presented. The aim of the proposed modelling approach is to provide a fuzzy set-based representation of the cascade sliding mode control of an induction motor fed by PWM voltage source inverter, which operates in a fixed reference frame. For this purpose, a new decoupled and reduced model is first proposed. Then, a set of simple surfaces and associated control laws are synthesised. A piecewise smooth control function with a threshold is adopted. However, the magnitude of this function depends closely on the upper bound of uncertainties, which include parameter variations and external disturbances. This bound is difficult to obtain prior to motor operation. To solve this problem, a fuzzy modelling approach is presented to improve the design and tuning of a fuzzy logic controller using variable structure control theory. The robust fuzzy control design is made feasible without resorting to model simplification or imposing restrictive conditions on the system uncertainty. The fuzzy controller is designed in order to improve the control performances and to reduce the control energy and the chattering phenomenon. Simulation results reveal some very interesting features and show that the proposed fuzzy sliding mode controller could be considered as an alternative to the conventional sliding mode control of induction motors.     

Switched chattering control vs. backlash/friction phenomena in electrical servo-motors

A switched control algorithm is developed to globally stabilize an electrical servo-motor operating under uncertainty conditions in the presence of complex non-linear phenomena such as backlash, stick-slip motion, etc. The controller constructed is referred to as a chattering controller and it does not rely on the generation of sliding motions while providing robustness features similar to those possessed by their sliding mode counterparts. Particularly, the chattering controller ensures robustness against external disturbances with the a priori known norm bounds, thus rejecting the influence of undesired backlash/friction effects on the motor. Stability analysis, given within the Lyapunov functions framework extended to discontinuous dynamic systems, additionally reveals a finite time convergence of the system trajectories to the equilibrium point. Performance issues of the controller are illustrated in a simulation study.     

RETRACTED ARTICLE: Nonlinear backstepping control design of LSM drive system using adaptive modified recurrent Laguerre orthogonal polynomial neural network

The good control performance of the permanent magnet linear synchronous motor (LSM) drive system is very difficult to achieve using linear controller because of uncertainty effects, such as ending-fictitious force. A backstepping approach is proposed to control the motion of the LSM drive system. With the proposed backstepping control system, the mover position of the LSM drive achieves good transient control performance and robustness. Although favorable tracking responses can be obtained by the backstepping control system, the chattering in the control effort is critical because of the large control gain. Because there are many nonlinear and time-varying uncertainties in the LSM drive systems, the nonlinear backsteping control system, which an adaptive modified recurrent Laguerre orthogonal polynomial neural network (NN) is used to estimate uncertainty, is thus proposed to reduce the chattering in the control effort and thereby enhance the robustness of the LSM drive system. In addition, the on-line parameter training methodology of the modified recurrent Laguerre orthogonal polynomial NN is based on the Lyapunov stability theorem. Furthermore, two optimal learning rates of the modified recurrent Laguerre orthogonal polynomial NN are derived to accelerate parameter convergence. Finally, comparison of the experimental results of the present study demonstrates the high control performance of the proposed control scheme.