Anti‐disturbance control for nonlinear system via adaptive disturbance observer

This paper addresses the problems of disturbance estimation and anti‐disturbance control for nonlinear system with exogenous disturbance, which is generated from an unknown exogenous system. The state observer and the adaptive disturbance observer are designed, simultaneously. Compared with the existing methods, which assumed that the exogenous system parameter matrix was known, our disturbance observer is more applicable in practice. Utilizing the estimation information, an observer‐based dynamic output feedback controller is designed, which avoids the influence of output disturbance on the closed‐loop system, and contains a disturbance compensation term to compensate the input disturbance. Finally, simulations are provided to demonstrate the effectiveness of the proposed approach. Copyright © 2016 John Wiley & Sons, Ltd.     

基于扰动观测器的水面无人船自适应模糊控制器设计

为了使水面无人船(USV)获得更好的跟踪性能,本文设计了基于扰动观测器和命令滤波器的自适应模糊控制器.对于该系统存在建模不确定性和外部环境的扰动,采用模糊逻辑系统(FLS)和一个新的扰动观测器对其进行逼近和补偿.在扰动观测器和控制器中加入了一个新的自适应参数,用来改善控制精度.基于此,本文设计了命令滤波反步控制方法,可以保证系统在所有状态下都是有界的,且跟踪误差在有限时间内小于规定的精度.仿真结果显示该方法有效,且可以满足给定的控制精度.     

Time forward observer based adaptive controller for a teleoperation system

This paper presents a design of a teleoperation system using time forward observer-based adaptive controller. The controller is robust to the time-variant delays and the environmental uncertainties while assuring the stability and the transparent performance. A novel theoretical framework and algorithms for this teleoperation system have been built up with neural network-based multiple model control and time forward state observer. Conditions for stability and transparency performance are also investigated.     

直线伺服系统非线性自适应鲁棒控制器的优化设计

对永磁直线电动机伺服系统提出了非线性自适应鲁棒控制器的优化设计方法.在系统非线性数学模型的基础上,建立了误差系统的动态模型.将跟踪和干扰抑制归结为非线性自适应鲁棒控制器的设计问题,通过构造存储函数得到自适应鲁棒控制器的定理,以及电阻和电感的辨识算法.证明了定理给出的控制器能满足干扰抑制和系统渐近稳定,并用遗传算法对控制器的参数进行优化.仿真结果验证了该方法是有效的.     

PMSM伺服系统线性自抗扰控制器的参数整定

当自抗扰控制器在工程中应用时,控制器性能和参数整定难易决定了其可推广性.本文阐述了一种将PI控制器改造为线性自抗扰控制器(LADRC)的方法,并给出了参数整定规则.首先,本文对于永磁同步(PMSM)伺服系统位置–速度–电流三闭环控制建立了P+P/I+P/I结构的控制模型,并通过极点配置的方法将控制器参数整定转换...     

Robust adaptive observer for nonlinear systems with unmodeled dynamics

Unmodeled dynamics exist in almost all applications of observers due to the impossibility of using exact and detailed models. It is highly desired that the observers can dominate the effects of unmodeled dynamics independently to prevent the state estimations from diverging and to get the precise estimations. Based on adaptive nonlinear damping, this paper presents a robust adaptive observer for multiple-input multiple-output nonlinear systems with unknown parameters, uncertain nonlinearities, disturbances and unmodeled dynamics. The observer only has one adaptive parameter no matter how high the order of the system is and how many unknown parameters there are. With the proposed observer, neither estimating the unknown parameters or solving linear matrix inequalities is needed. It is shown that the state estimation error is uniformly bounded and can be made arbitrarily small.     

基于NDO的ROV变深自适应终端滑模控制器设计

针对ROV的深度控制问题, 提出基于非线性干扰观测器的自适应终端滑模控制方法. 详细叙述了控制器的设计过程, 并利用Lyapunov 稳定性判据, 验证了存在模型参数不确定性和外干扰时, 系统的全局渐近稳定性和跟踪误差的收敛性. 仿真实验表明, 所提出的控制器不仅能够很好地估计并克服外干扰和模型不确定性等因素, 具有很好的鲁棒性能, 而且还可以实现在任意规定时刻变深运动的快速收敛.

     

带有干扰观测器的线控转向系统复合自适应神经网络控制

考虑车辆线控转向(SbW)系统存在不确定动态特性以及外界干扰影响.本文提出一种带有干扰观测器的复合自适应神经网络实现SbW系统的精确建模与稳定控制.首先,利用神经网络在线逼近系统不确定动态,避免控制器设计中使用到系统模型的先验知识.然后,结合系统的跟踪误差与建模误差提出一种新的复合自适应学习率来更新神经网络的权值,从而...     

Robust adaptive tracking control for servo mechanisms with continuous friction compensation

In this paper, a robust adaptive tracking control scheme is developed for servo mechanisms with nonlinear friction dynamics. A continuously differentiable friction model is used to capture the friction behaviors (e.g. Stribeck effect, Coulombic friction and Viscous friction). The robust integral of the sign of the error (RISE) feedback term is employed to design an innovative adaptive controller to compensate nonlinear friction and bounded disturbances. To reduce the effect of noise pollution, the desired trajectory is employed to replace the output signal in controller design. The developed adaptive controller can guarantee the asymptotic tracking performance for nonlinear servo mechanisms in the presence of nonlinear friction and bounded disturbances. Comparative experimental results are used to validate the effectiveness of the developed control algorithm.     

Robust adaptive observer design for uncertain systems with bounded disturbances.

This paper presents a robust adaptive observer design methodology for a class of uncertain nonlinear systems in the presence of time-varying unknown parameters with absolutely integrable derivatives, and nonvanishing disturbances. Using the universal approximation property of radial basis function (RBF) neural networks and the adaptive bounding technique, the developed observer achieves asymptotic convergence of state estimation error to zero, while ensuring boundedness of parameter errors. A comparative simulation study is presented by the end.     

Neural network-based adaptive controller design of roboticmanipulators with an observer

A neural network (NN)-based adaptive controller with an observer is proposed for the trajectory tracking of robotic manipulators with unknown dynamics nonlinearities. It is assumed that the robotic manipulator has only joint angle position measurements. A linear observer is used to estimate the robot joint angle velocity, while NNs are employed to further improve the control performance of the controlled system through approximating the modified robot dynamics function. The adaptive controller for robots with an observer can guarantee the uniform ultimate bounds of the tracking errors and the observer errors as well as the bounds of the NN weights. For performance comparisons, the conventional adaptive algorithm with an observer using linearity in parameters of the robot dynamics is also developed in the same control framework as the NN approach for online approximating unknown nonlinearities of the robot dynamics. Main theoretical results for designing such an observer-based adaptive controller with the NN approach using multilayer NNs with sigmoidal activation functions, as well as with the conventional adaptive approach using linearity in parameters of the robot dynamics are given. The performance comparisons between the NN approach and the conventional adaptation approach with an observer is carried out to show the advantages of the proposed control approaches through simulation studies     

Robust adaptive controller with zero residual tracking errors

The adaptive control of a plant whose dominant part has transfer function with relative degreen^{ast} = 1has been considered in the presence of parasitics and disturbances. A new adaptive law is proposed which guarantees the existence of a large region of attraction from which all signals are bounded and the tracking error converges to a small residual set. In contrast to the adaptive law used in [1], [2] the new adaptive law guarantees a smaller residual set for the tracking error, which reduces to zero when the parasitics and disturbances disappear.     

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.     

非仿射系统的自适应观测器自抗扰控制

研究了一类单输入单输出(SISO)非仿射非线性系统的控制问题,通过微分同胚变换以及自抗扰思想将该类形式转化成含有未知非线性且控制增益未知的仿射形式.引入扩展状态自适应观测器以及Nussbaum-type增益技术,利用积分反演和调节函数技术,设计了自抗扰控制器.从理论上证明了所设计的控制器能够保证闭环系统所有信号全局一致有界,并且证明了跟踪误差渐近收敛到零点的残集内.仿真例子验证了算法的有效性.     

Robust adaptive quasi-sliding mode controller for discrete-time systems

In this paper, a discrete robust quasi-sliding mode adaptive controller is presented for the system with model uncertainties, unmodeled dynamics and bounded disturbances. The proposed method is adaptive control in conjunction with a sliding mode based controller design. The bounded motion of the state around the sliding surface and the stability of the global system in the sense that all signals remain bounded are guaranteed. In the proposed adaptive algorithms, the dead-zone method is employed even though the upper and lower bounds of the disturbances are unknown. Simulation results have shown the effectiveness of the proposed algorithms.     

基于干扰观测器的一类不确定非线性系统鲁棒H∞控制

为了降低控制器对干扰的要求,基于干扰观测器提出一类多输入多输出不确定非线性系统的鲁棒H∞控制方法．将系统的内部不确定性和外部干扰组成复合干扰,设计基于小波神经网络的复合干扰观测器,并提出干扰观测器的参数调节方案使观测器能以高精度逼近复合干扰．同时在控制器中引入鲁棒控制项用来抑制观测器误差给系统带来的影响,所设计的控制器能使系统的跟踪误差小于一个给定的性能指标．最后给出一个仿真算例验证了本控制方案的有效性．     

Robust adaptive controller design for flexible joint manipulators

In this paper the control problem for robot manipulators with flexible joints is considered. A reduced-order flexible joint model is constructed based on a singular perturbation formulation of the manipulator equations of motion. The concept of an integral manifold is utilized to construct the dynamics of a slow subsystem. A fast subsystem is constructed to represent the fast dynamics of the elastic forces at the joints. A composite control scheme is developed based on on-line identification of the manipulator parameters which takes into account the effect of certain unmodeled dynamics and parameter variations. Stability analysis of the resulting closed-loop full-order system is presented. Simulation results for a single link flexible joint manipulator are given to illustrate the applicability of the proposed algorithm.     

An adaptive controller based on disturbance attenuation

This paper discusses the control of linear systems with uncertain parameters in the control coefficient matrix, under the influence of both process and measurement noise. A disturbance attenuation approach is used, and from this a multiplayer game problem is generated. First, the minimax formulation is presented, which represents an upper bound on the game cost criterion. Second, a dynamic programming approach is used to solve the game. It is necessary to significantly extend the method over earlier implementations, as the class of problems does not satisfy certain assumptions generally made. It is shown that for this class of problems, the controller determined from the dynamic programming approach is equivalent to the minimax controller. Therefore, the minimax controller is also a saddlepoint strategy for the differential game. Controller development appears to be much simpler from the dynamic programming standpoint. A simple scalar example is presented     

一种基于时变干扰观测器的高超声速飞行器容错控制策略设计

为了提高高超声速再入飞行器(HRV)在执行机构故障情况下的姿态控制效果,提出一种基于时变干扰观测器和参考轨迹重构器(RVG)的滑模容错控制策略.首先,设计一种新型自适应干扰观测器(ADO)来估计系统扰动,在保证估计精度的同时,能够有效削弱传统干扰观测器的初始超调现象;然后,基于反步法设计HRV的滑模控制器,在设计中引入参考轨迹重构器以避免故障突变引起的初始尖峰,并且在滑模面的设计中利用ADO所估计的系统扰动实现干扰的在线补偿.仿真结果表明,所设计的控制策略可以有效解决传统的基于高增益干扰观测器的滑模控制律受故障引起的突变和初始估计误差造成控制系统动态性能恶化的问题.     

一阶不确定系统的固定时间收敛扰动观测器

针对一阶不确定系统中集总扰动的快速估计问题,基于误差放大策略和双极限齐次估计理论设计非递归形式的固定时间收敛扰动观测器,并提出利用幂次函数非线性特性削弱输入信号噪声影响的改进方案.误差放大策略是一种特殊的高增益方法,能够实现修正项中幂次函数支配范围的扩张,进一步提升观测器的收敛速度,并简化参数调试过程;合理选择误差放大系数并忽略修正项中的低阶幂次项,能够简化扰动观测器结构并增强对测量噪声的抑制能力.另外,以广义超螺旋算法为基础,构建固定时间收敛鲁棒扰动观测器.最后,在理论证明分析的基础上,针对是否存在测量噪声的两种情况,对所介绍的3种扰动观测器和一种扩张状态观测器进行对比仿真分析,并总结各类扰动观测器的特点和适用性.