一类不确定非线性系统的鲁棒自适应控制

针对一类具有一般不确定性和未知参数的非线性系统,设计出一种适用于输出跟踪 的鲁棒自适应控制器.该控制器对系统的参数和状态的不确定性具有鲁棒性,能保证闭环系 统的全局稳定性,并解决了ε-跟踪问题.仿真实例表明,所设计的鲁棒自适应控制器具有良好 的跟踪性能.     

一类非线性不确定系统的鲁棒跟踪

讨论一类含有时变不确定性的非线性不确定系统的鲁棒跟踪问题，其中的未知参数变量以非线性形式出现。通过构造适当的Ｌｙａｐｕｎｏｖ函数，给出了该类系统的鲁棒跟踪控制器的设计。     

控制方向未知的非线性系统的自适应输出跟踪控制

针对一类含有未知控制方向和时变不确定性的本质非线性系统,应用Nussbaum-type增益技术和Adding a power integrator递推设计方法,设计了一种鲁棒自适应状态反馈拉制器．所设计的控制器能保证闭环系统所有信号全局一致有界,特别是通过适当调整控制器设计参数,可使输出跟踪误差在有限时间后变得适当小．最后通过仿真实例对算法进行验证.     

具有参数不确定性的非线性系统的鲁棒输出跟踪

研究具有非线性参数化的非线性系统的输出跟踪问题.采用时变状态反馈控制律, 指数镇定输出跟踪误差,并保证非线性系统的所有状态是有界的.为了实现时变状态反馈控 制律,设计高增益鲁棒观测器观测构造该控制律所需要的状态,使得整个闭环系统的输出能 渐近跟踪期望输出,且该闭环系统中所有信号都是有界的.     

一类不确定非线性系统的鲁棒自适应控制

针对一类输入带有一定的不确定性的非线性系统 ,设计了一种鲁棒自适应控制器。该控制器作用与系统 ,能保证闭环系统信号的全局有界性 ,又能使闭环系统输出任意小。     

时变输出约束非线性系统的量化反馈 自适应终端滑模控制

针对一类复杂非线性系统,提出一种新型自适应快速非奇异终端滑模控制(IAFNTSMC)方法,用以解决其在输出时变约束及量化输入情形下的轨迹跟踪问题;利用鲁棒自适应方法处理扰动不确定性,并结合反演策略和终端滑模策略设计控制器;构造一种新型的时变约束障碍Lyapunov函数,用于实现对系统的输出误差进行随时间变化的幅值约束;为提高闭环系统的误差收敛速度,提出一种新型的滑模面构造方案.所提控制方法能够保证闭环系统的输出跟踪误差快速收敛到约束边界内,并确保闭环系统所有信号有界.数值仿真验证了所提方法的有效性.     

不确定非线性系统的鲁棒输出反馈自适应控制

针对一类具有一般不确定性的非线性系统,设计一种新的鲁棒输出反馈自适应控制器。在较弱条件下,该控制器不仅能保证闭环系统全局稳定,且能使跟踪误差以指数速度收敛到零的小领域内。仿真结果验证了所给控制方案的有效性。     

一类不确定非线性系统的指数鲁棒输出跟踪

研究一类不确定非线性系统的鲁棒输出跟踪控制问题。应用输入／输出反馈线性化法和李亚普诺夫方法,提出一种基于不确定项上界的连续型鲁棒输出跟踪控制器设计方法。该控制器不仅可确保闭环系统的状态一致最终有界,使系统输出按指数规律跟踪期望输出,而且计算简单,更易实现。仿真结果证明了该方法的可行性与有效性。     

输入具有齿隙非线性特性的周期系统的自适应控制

针对一类输入含齿隙非线性动态特性的周期时变系统, 在周期不确定性可时变参数化的条件下设计自适应控制器. 对周期时变参数进行傅里叶级数展开, 并采用微分自适应律估计未知傅里叶系数和齿隙动态特性参数, 通过鲁棒方法消除截断误差和齿隙模型的有界误差项对系统性能的影响. 采用双曲函数替代符号函数确保控制器可微, 同时能有效抑制颤振. 引入Δ函数, 避免参数估计发散, 并保证系统输出渐近跟踪理想轨迹. 理论分析与仿真结果表明, 闭环系统所有信号有界.     

基于反馈线性化同步伺服电机鲁棒跟踪控制

为了保证具有不确定非线性的PM同步伺服电机驱动系统的稳定性,确保闭环系统的输出准确跟踪期望输出并减少不确定项对该驱动系统的影响,利用Lyapunov稳定性理论,设计了一种基于反馈线性化的鲁棒跟踪控制器,并作了相应的仿真研究。仿真结果表明,该控制器不仅确保闭环系统的输出按指数规律跟踪期望输出,而且保证闭环系统状态的一致最终有界。该控制器设计简单,易于实现,具有很好的实用性。     

Robust‐decentralized tracking control for a class of uncertain MIMO nonlinear systems with time‐varying delays

A new control design method based on signal compensation is proposed for a class of uncertain multi‐input multi‐output (MIMO) nonlinear systems in block‐triangular form with nonlinear uncertainties, unknown virtual control coefficients, strongly coupled interconnections, time‐varying delays, and external disturbances. By this method, the controller design is performed in a backstepping manner. At each step of backstepping procedure, a nominal virtual controller is first designed to get desired output tracking for the nominal disturbance‐free subsystem, and then a robust virtual compensator is designed to restrain the effect of the uncertainties, delays involved in the subsystem, and the couplings among the subsystems. The designed controller is linear and time‐invariant, so the explosion of complexity in the control law is avoid. It is proved that robust stability and robust practical tracking property of the closed‐loop system can be ensured, and the tracking errors can be made as small as desired. Copyright © 2013 John Wiley & Sons, Ltd.     

不确定非线性系统的多模反演滑模控制

对一般形式的仿射非匹配不确定非线性系统,研究了一种具有任意小跟踪误差的稳定控制器的新方法,结合反演（backstepping）设计和变结构控制,提出了反演变结构控制策略,对存在非匹配的不确定性和未知干扰的系统,设计的反演结构控制器实现了鲁棒输出跟踪,闭环系统在有限时间进入滑动模态,仿真算例证实了理论结果。     

不确定线性组合系统的分散镇定与输出跟踪

提出了不确定线性组合系统存在分散鲁棒反馈控制器和输出跟踪吕的充分条件。     

基于调节函数的一类三角结构非线性系统的自适应滑模控制

针对一类三角结构的非线性系统,基于状态参考自适应控制算法和滑模控制技术,研究了其在非匹配未知参数和不确定性干扰下的跟踪控制问题,提出了自适应滑模控制策略,实现了不确定非线性系统的鲁棒输出跟踪.与一般自适应控制相比,允许系统存在非参数化的不确定性和未知扰动,增强了控制系统鲁棒性.仿真算例证明了理论研究成果的正确性和可行性.     

Robust approximation‐based adaptive control of multiple state delayed nonlinear systems with unmodeled dynamics

This paper addresses the problem of tracking control for a class of uncertain nonstrict‐feedback nonlinear systems subject to multiple state time‐varying delays and unmodeled dynamics. To overcome the design difficulty in system dynamical uncertainties, radial basis function neural networks are employed to approximate the black‐box functions. Novel continuous functions that deal with whole states uncertainties are introduced in each step of the adaptive backstepping to make the controller design feasible. The robust problem caused by unmodeled dynamics when constructing a stable controller is solved by employing an auxiliary signal to regulate its boundedness. A novel Lyapunov‐Krasovskii functional is developed to compensate for the delayed nonlinearity without requiring the priori knowledge of its upper bound functions. On the basis of the proposed robust adaptive neural controller, all the closed‐loop signals are semiglobal uniformly ultimately bounded with good tracking performance.     

Globally stable robust tracking of nonlinear systems using variablestructure control and with an application to a robotic manipulator

The globally stable robust output tracking for a class of nonlinear systems is considered. Based only on the knowledge of the bounds on the uncertainties, a variable structure control (VSC) law is developed under the structure matching assumption. It is shown that the outputs of the closed-loop system asymptotically track given output trajectories despite the uncertainties while maintaining the boundedness of all signals inside the loop. All signals inside the loop are shown to be bounded for all time. To illustrate the efficiency of the controller, the approach is applied to the case of a two degree-of-freedom (DOF) robotic manipulator with variable payload. Numerical simulation results are also provided     

具有一般不确定性的非线性系统的鲁棒输出反馈控制

为将文献「１」中结果推广到具有一般不确定性的系统并降低在过渡阶段所需要的控制量,通过引入新的正则信号和一些正光滑设计函数来处理状态估计误差和不确定性,设计了鲁棒输出反馈控制器,它能保证闭环系统信号的全局有界性,并使输出跟踪误差任意小,仿真说明,应用本文控制器,获得的性能更好,所需控制量要小。     

Robust Tracking Controller Design for a Class of Block Lower‐Triangular Systems

A class of multi‐input multi‐output (MIMO) block lower‐triangular systems are considered with the dynamic and static uncertainties related to the states of the former subsystems. A design procedure of robust tracking controller is presented, which avoids the problem of the “explosion of complexity” and can be implemented very simply. The closed‐loop system possesses robust properties that, 1) all signals involved are semi‐global uniformly ultimately bounded for bounded differentiable reference inputs; 2) for given initial tracking errors and uncertainty boundary, controller parameters can be found to guarantee that the tracking errors can be smaller than a specific positive constant after a limited time. Two numerical instances are given at last.     

An Intelligent Robust Tracking Control for a Class of Electrically Driven Mobile Robots

This paper addresses the problem of designing robust tracking control for a class of uncertain wheeled mobile robots actuated by brushed direct current motors. This class of electrically‐driven mechanical systems consists of the robot kinematics, the robot dynamics, and the wheel actuator dynamics. Via the backstepping technique, an intelligent robust tracking control scheme that integrates a kinematic controller and an adaptive neural network‐based (or fuzzy‐based) controller is developed such that all of the states and signals of the closed‐loop system are bounded and the tracking error can be made as small as possible. Two adaptive approximation systems are constructed to learn the behaviors of unknown mechanical and electrical dynamics. The effects of both the approximation errors and the unmodeled time‐varying perturbations in the input and virtual‐input weighting matrices are counteracted by suitably tuning the control gains. Consequently, the robust control scheme developed here can be employed to handle a broader class of electrically‐driven wheeled mobile robots in the presence of high‐degree time‐varying uncertainties. Finally, a simulation example is given to demonstrate the effectiveness of the developed control scheme.