一类不确定非线性系统的鲁棒自适应控制

针对一类MIMO不确定非线性系统的输出跟踪问题, 基于自适应反步法和滑模控制为其设计了鲁棒自适应控制器. 模型包含3种不确定性: 1) 参数不确定性; 2) 输入增益的不确定性; 3) 代表系统未建模动态和干扰的不确定函数, 该函数有界. 以非完整移动机械臂的输出跟踪控制为目标, 对其进行仿真实验, 实验结果表明所提出的控制算法是正确有效的.     

一类结构不确定采样系统的鲁棒控制

针对一类结构不确定性线性采样系统，在时域中用Lyapunov方法研究采样系统的鲁棒控制及最优鲁棒控制，给出了系统鲁棒稳定的充分条件以及相应的鲁棒控制律，控制律的求取借助于求解一类线性矩阵不等式（LMI），或求解满足特定线性不等式条件下的优化问题，算例结果表明，采样周期是一个关键性的设计参数。     

一类不确定广义时滞系统的鲁棒耗散控制

将耗散不确定性引入到不确定广义系统中,在状态空间下,通过线性矩阵不等式(LMI)的方法,研究了一类不确定广义时滞系统的鲁棒耗散控制问题.给出了此类不确定广义系统严格耗散的充分条件,然后设计了此类不确定广义系统的鲁棒耗散控制器,最后通过数值算例验证了定理的可行性.     

一类非匹配不确定非线性系统的鲁棒跟踪控制制

针对一类半严格反馈型不确定非线性系统,提出一种鲁棒反演滑模变结构控制方法.采用反演控制方法设计了使前n-1阶子系统稳定的虚拟控制律,抑制非匹配不确定性的影响;在第n步设计了一种连续可导的滑模变结构控制律,消除控制抖振,实现了对存在未知不确定性及扰动系统的鲁棒输出跟踪.通过Lyapunov定理证明了闭环系统所有信号最终有界.仿真结果验证了该方法的有效性.     

惯性参数大范围变化机械伺服系统鲁棒跟踪控制

机械伺服系统在执行不同任务时,要求能适应不同质量或惯量的工作负载.而工作负载的改变会导致伺服系统惯性参数的大范围变化,目前常见的运动控制方法,如PD控制,基于干扰观测器的鲁棒控制等,对上述情况表现为系统不稳定或跟踪性能变差.对上述问题,本文假定惯性参数变化范围已知,提出一种新型的非线性控制方法,用滑模技术实现了系统对惯性参数变化和外部扰动的鲁棒稳定性,和跟踪性能,引入边界层技术避免了控制切换产生的抖振现象.用Lyapunov直接法对系统的全局稳定性给出了证明,并分析了系统的暂态响应.以直流电机高精度位置伺服系统为例的仿真结果表明算法的有效性.     

不确定Delta算子系统的鲁棒H∞重构控制

讨论一类含有参数不确定和执行器故障的Delta算子系统鲁棒H_∞ 重构控制设计问题. 通过利用故障检测与隔离(FDI)技术, 在考虑不可检测故障执行器输入为能量有界的干扰信号情形下, 基于H_∞ 干扰抑制的思想, 给出了系统可鲁棒H_∞ 镇定的充分条件. 所设计的控制器可使闭环系统鲁棒稳定, 而且对可允许的不确定性和执行器故障具有一定的H_∞ 性能. 数值例子说明了本文设计方法的有效性.     

Robust adaptive control for mobile manipulators

This paper addresses the trajectory tracking control of a nonholonomic wheeled mobile manipulator with parameter uncertainties and disturbances. The proposed algorithm adopts a robust adaptive control strategy where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. A kinematic controller is first designed to make the robot follow a desired end-effector and platform trajectories in task space coordinates simultaneously. Then, an adaptive control scheme is proposed, which ensures that the trajectories are accurately tracked even in the presence of external disturbances and uncertainties. The system stability and the convergence of tracking errors to zero are rigorously proven using Lyapunov theory. Simulations results are given to illustrate the effectiveness of the proposed robust adaptive control law in comparison with a sliding mode controller.     

Event-triggered sliding mode control for a class of nonlinear systems

ABSTRACT

Event-triggering strategy is one of the real-time control implementation techniques which aims at achieving minimum resource utilisation while ensuring the satisfactory performance of the closed-loop system. In this paper, we address the problem of robust stabilisation for a class of nonlinear systems subject to external disturbances using sliding mode control (SMC) by event-triggering scheme. An event-triggering scheme is developed for SMC to ensure the sliding trajectory remains confined in the vicinity of sliding manifold. The event-triggered SMC brings the sliding mode in the system and thus the steady-state trajectories of the system also remain bounded within a predesigned region in the presence of disturbances. The design of event parameters is also given considering the practical constraints on control execution. We show that the next triggering instant is larger than its immediate past triggering instant by a given positive constant. The analysis is also presented with taking delay into account in the control updates. An upper bound for delay is calculated to ensure stability of the system. It is shown that with delay steady-state bound of the system is increased than that of the case without delay. However, the system trajectories remain bounded in the case of delay, so stability is ensured. The performance of this event-triggered SMC is demonstrated through a numerical simulation.     

Reduction of matched and unmatched uncertainties for a class of nonlinear perturbed systems via robust control

The aim of this paper is to design a robust control for stabilization of a class of nonlinear perturbed system subject to matched and unmatched disturbances. Here, the concept of dynamic sliding mode control and the attractive ellipsoid method advantages are used to design a robust nonlinear control algorithm, which reduces considerably the perturbation effects. Hence, in finite time, the dynamic sliding mode control brings the system trajectory to a specific configuration. After this time, the controller reduces the perturbation effects by using the high‐gain control obtained in the attractive ellipsoid method. Thus, based on the solution of a specific matrix inequality, the feedback control of the system guarantees that the trajectory will be stabilized in the ultimate uniform bounded sense. To illustrate the theoretical results, a numerical example with a comparative study is introduced. Finally, the performance of the controller designed in this paper is tested on an electromechanical real‐time system.     

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.     

Robust output tracking of constrained perturbed linear systems via model predictive sliding mode control

A robustifying strategy for constrained linear multivariable systems is proposed. A combination of tracking model predictive control with output integral sliding mode techniques is used to completely reject bounded matched perturbations. It can be guaranteed that all constraints on inputs, states, and outputs are satisfied although only output information is used. Finally, real‐world experiments with an unstable plant are presented in order to demonstrate the validity and the effectiveness of the proposed approach.     

Sliding mode control for a class of nonlinear It ô stochastic systems with state and input delays

This paper deals with the problem of sliding mode control (SMC) for a class of nonlinear stochastic systems. The nonlinear uncertainties are unknown and unmatched. There exist state and input delays. A special switching function is designed such that the insensitivity of the system can be guaranteed throughout the entire response of the system from the initial time instance. Both the sliding surface and the sliding mode controller exist if a set of matrix inequalities is feasible. A simulation example is given to illustrate the proposed method. Recommended by Editorial Board member Poo Gyeon Park under the direction of Editor Young Il lee. The research was partially supported by NNSF under Grant (60674015, 60674089), the Technology Innovation Key Foundation of Shanghai Municipal Education Commission (09ZZ60), Shanghai Leading Academic Discipline Project (B504), China. Yugang Niu received the Ph.D. degree in Control Theory and Control Engineering Automation from Nanjing University of Science and Technology in 2001. His research interests include nonlinear control, stochastic control systems, sliding mode control and network congestion control. Bei Chen received the B.S. degree in Automation from East China University of Science & Technology in 2008. Her current research areas are sliding mode control, and networked control systems. Xingyu Wang received the Ph.D. degree in Industrial Automation from the East China Chemical Institute in 1984. His current research areas primarily cover control theory and applications, intelligent control, and brain control with its wide range of applications.     

关于《模型不确定性系统的鲁棒预测控制》一文中的问题

指出了《模型不确定性系统的鲁棒预测控制》一文在控制器的设计过程中所出现的零极点对消而导致的在实际中无法实现的问题,并给出了改正结果.     

基于模型参考和内模原理的线性系统鲁棒控制设计

不确定性因素会使系统性能恶化,它包括系统不确定性参数和各种外部干扰等.本文针对这种不确定性线性系统,利用模型参考和内模原理,建立鲁棒控制系统结构,分析了其能控性条件,通过选择参考模型和内模实现系统能控,在此条件下,将鲁棒控制设计转换为控制系统的LQR问题进行研究,并运用最优控制理论,计算其反馈控制律.仿真结果表明该设计方法将"模型参考"与"内模原理"有机结合起来,提高了系统的鲁棒稳定性,有效抑制干扰,并实现系统性能的改善.     

一类不确定非线性系统的鲁棒自适应轨迹线性化控制

针对一类不确定非线性系统,研究了一种新的鲁棒自适应轨迹线性化控制方案.利用径向基神经网络的在线逼近能力以及被控对象分析模型的有用信息设计一种径向基神经网络干扰观测器来估计系统中存在的不确定性.观测器输出用于设计补偿控制律抵消不确定性对系统性能的影响,鲁棒自适应控制律用于克服逼近误差.采用Lyapunov方法严格证明了在自适应调节律作用下闭环系统所有误差信号最终有界.最后利用倒立摆系统验证了新方法的有效性.     

控制增益符号未知的不确定非线性系统鲁棒自适应控制

针对一类控制增益函数及符号均未知的不确定非线性系统,基于反推滑模设计方法,提出一种鲁棒自适应神经网络控制方案.结合Nussbaum增益设计技术和神经网络逼近能力,取消了控制增益函数及符号已知的条件,应用积分型Lyapunov函数避免了控制器奇异性问题,并通过引入神经网络逼近误差和不确定干扰上界的自适应补偿项消除了建模误差和不确定干扰的影响.理论分析证明了闭环系统所有信号半全局一致终结有界,仿真结果验证了该方法的有效性.     

Quasi sliding mode‐based single input fuzzy self‐tuning decoupled fuzzy PI control for robot manipulators with uncertainty

This paper presents a robust adaptive control strategy for robot manipulators, based on the coupling of the fuzzy logic control with the so‐called sliding mode control (SMC) approach. The motivation for using SMC in robotics mainly relies on its appreciable features. However, the drawbacks of the conventional SMC, such as chattering effect and required a priori knowledge of the bounds of uncertainties can be destructive. In this paper, these problems are suitably circumvented by adopting a reduced rule base single input fuzzy self tuning decoupled fuzzy proportional integral sliding mode control approach. In this new approach a decoupled fuzzy proportional integral control is used and a reduced rule base single input fuzzy self‐tuning controller as a supervisory fuzzy system is added to adaptively tune the output control gain of the decoupled fuzzy proportional integral control. Moreover, it is proved that the fuzzy control surface of the single‐input fuzzy rule base is very close to the input/output relation of a straight line. Therefore, a varying output gain decoupled fuzzy proportional integral sliding mode control approach using an approximate line equation is then proposed. The stability of the system is guaranteed in the sense of the Lyapunov theorem. Simulations using the dynamic model of a 3DOF planar manipulator with uncertainties show the effectiveness of the approach in high speed trajectory tracking problems. The simulation results that are compared with the results of conventional SMC indicate that the control performance of the robot system is satisfactory and the proposed approach can achieve favorable tracking performance, and it is robust with regard to uncertainties and disturbances. Copyright © 2011 John Wiley & Sons, Ltd.     

Robust adaptive control of a class of nonlinear strict-feedback discrete-time systems with exact output tracking

In this paper, adaptive control is studied for a class of single-input–single-output (SISO) nonlinear discrete-time systems in strict-feedback form with nonparametric nonlinear uncertainties of the Lipschitz type. To eliminate the effect of the nonparametric uncertainties in an unmatched manner, a novel future states prediction is designed using states information at previous steps to compensate for the effect of uncertainties at the current step. Utilizing the predicted future states, constructive adaptive control is developed to compensate for the effects of both parametric and nonparametric uncertainties such that global stability and asymptotical output tracking is achieved. The effectiveness of the proposed control law is demonstrated in the simulation.     

Robust nonovershooting tracking control for fractional‐order systems

A robust tracking control is proposed for the fractional‐order systems (FOSs) to achieve a tracking response with no overshoot, even in the presence of a class of disturbances. The control proposed makes use of a newly designed integral sliding mode technique for FOSs, which is capable of rejecting the bounded disturbances acting through the input channel. The proposed integral sliding mode control design has two components: a nominal control component and a discontinuous control component. The overshoot in the system response is avoided by the nominal control designed with the use of Moore's eigenstructure assignment algorithm. The sliding mode technique is used for the design of discontinuous part of the control that imparts the desired robustness properties.