基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统设计

为了保证机器人能够在保持稳定的情况下,按照规划轨迹执行工作任务,从硬件和软件两个方面,设计了基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统。装设机器人传感器与状态观测器,改装机器人鲁棒滑模跟踪控制器,完成系统硬件设计。综合机器人结构、运动机理和动力机制三个方面,构建机器人数学模型。根据状态数据采集结果与规划轨迹之间的偏差,计算机器人跟踪控制量。依据滑模运动与切换方程,利用Sigmoid函数生成机器人鲁棒滑模控制律,将生成控制指令作用在机器人执行元件上,实现系统的鲁棒滑模跟踪控制功能。实验结果表明,所设计控制系统的机器人移动轨迹与设定轨迹目标基本重合,其机器人姿态角跟踪控制误差较小,具有较好的鲁棒滑模跟踪控制效果,能够有效提高机器人鲁棒滑模跟踪控制精度。     

Trajectory tracking control of farm vehicles in presence of sliding

In automatic guidance of agriculture vehicles, lateral control is not the only requirement. Much research work has been focused on trajectory tracking control which can provide high longitudinal-lateral control accuracy. Satisfactory results have been reported as soon as vehicles move without sliding. But unfortunately pure rolling constraints are not always satisfied especially in agriculture applications where working conditions are rough and not predictable. In this paper the problem of trajectory tracking control of autonomous farm vehicles in the presence of sliding is addressed. To take sliding effects into account, three variables which characterize sliding effects are introduced into the kinematic model based on geometric and velocity constraints. With a linearized approximation, a refined kinematic model is obtained in which sliding effects appear as additive unknown parameters to the ideal kinematic model. By an integrating parameter adaptation technique with a backstepping method, a stepwise procedure is proposed to design a robust adaptive controller in which time-invariant sliding is compensated for by parameter adaptation and time-varying sliding is corrected by a Variable Structure Controller (VSC). It is theoretically proven that for farm vehicles subjected to sliding, the longitudinal-lateral deviations can be stabilized near zero and the orientation errors converge into a neighborhood near the origin. To be more realistic for agriculture applications, an adaptive controller with projection mapping is also proposed. Both simulation and experimental results show that the proposed (robust) adaptive controllers can guarantee high trajectory tracking accuracy regardless of sliding.     

电液伺服系统的多滑模鲁棒自适应控制

针对一类参数与外负载非匹配不确定的非线性高阶系统,提出了一种基于逐步递推方法的多滑模鲁棒自适应控制策略.应用逐步递推的多滑模控制方法简化了高阶系统的控制问题,同时在自适应控制中加入鲁棒控制的方法,以消除不确定性对控制性能的影响.首先利用逐步递推方法与状态反馈精确线性化理论,得出确定系统的多滑模控制器设计方法;然后基于Lyapunov稳定性分析方法,给出不确定系统的参数自适应律,及鲁棒自适应控制器的设计方法.本文把该控制策略应用到电液伺服系统的位置跟踪控制中,仿真结果显示,该控制方法具有较强的鲁棒性及良好的跟踪效果.     

Trajectory Tracking Control of Multi-DOF Robot without Considering System Dynamics

In this study, two different control logics have been designed for the position control of a robot with five degrees of freedom (DOFs). First, a sliding mode control with a sliding perturbation observer (SMCSPO) has been proposed. The SMCSPO is robust against perturbation, which is the sum of nonlinearities, parametric uncertainties, and external disturbances. To implement the SMCSPO, linear parameters of the system are required; however, these are difficult to identify. Moreover, it is exigent to derive the equation of motion for the multi-DOF robot. Accordingly, an integral sliding mode control (ISMC) has been designed for the position control of this multi-DOF robot. The ISMC controller does not require a mathematical model of the system. The ISMC control input applies a switching gain to compensate for the perturbation and system dynamics. In comparison with the SMCSPO, the ISMC has improved the tracking performance of the system because of its unique characteristics. Both control schemes have been implemented in MATLAB/Simulink. It has been observed that the tracking error of each ISMC joint is lower than that of the SMCSPO.

     

挖掘机轨迹跟踪的滑模变结构控制

对液压挖掘机工作装置的轨迹跟踪进行了研究。在分析了液压挖掘机工作装置的动力学方程的基础上,针对其复杂的非线性,提出了一种新的液压挖掘机工作装置轨迹跟踪方法,即应用机器人学理论,建立了三自由度液压挖掘机工作装置的拉格朗日动力学模型,设计了带低通滤波器的滑模控制器,利用低通滤波器的滤除高频信号的功能,消除控制信号的抖动,给出沿规划轨迹工作所需的控制量,并给出了控制系统的设计方法。对三自由度工作装置进行了仿真研究,其结果表明,所设计的控制器对设定轨迹的跟踪具有良好的动态特性,对系统的不确定性具有较强的鲁棒性,在存在模型误差和外部扰动的情况下,该方案既能达到高精度快速跟踪的目的,又能消除滑模控制的抖动问题。     

Robust Sliding Control of Robotic Manipulators Based on a Heuristic Modification of the Sliding Gain

A task space robust trajectory tracking control is developed for robotic manipulators. A second order linear model, which defines the desired impedance for the robot, is used to generate the reference position, velocity and acceleration trajectories under the influence of an external force. The control objective is to make the robotic manipulator’s end effector track the reference trajectories in the task space. A sliding mode based robust control is used to deal with system uncertainties and external perturbations. Thus, a sliding manifold is defined by a linear combination of the tracking errors of the system in the task space built from the difference between the real and the desired position, velocity and acceleration trajectories in comparison with previous works where the sliding manifold was defined by the desired impedance and the external force. Moreover, the ideal relay has been substituted by a relay with a dead-zone in order to fit in with the actual way in which a real computational device implements the typical sign function in sliding mode control. Furthermore, a higher level supervision algorithm is proposed in order to reduce the amplitude of the high frequency components of the output associated to an overestimation of the system uncertainty bounds. Then, the robust control law is applied to the case of a robot with parametric uncertainty and unmodeled dynamics. The closed-loop system is proved to be robustly stable with all signals bounded for all time while the control objective is fulfilled in practice. Finally, a simulation example which shows the usefulness of the proposed scheme is presented.     

Adaptive sliding mode control for discrete-time multi-input multi-output systems

In this paper, robust adaptive sliding mode tracking control for discrete-time multi-input multi-output systems with unknown parameters and disturbance is considered. The robust tracking controller is comprised of adaptive control and sliding mode control design. Bounded motion of the system around the sliding surface and stability of the global system in the sense that all signals remain bounded are guaranteed. If the disturbance and the reference signal are slowly varying with respect to the sampling frequency, the proposed sliding mode controller can reject the disturbance and output tracking can be approximately achieved. Simulation results are presented to illustrate the proposed approach.     

Sliding Mode Neuro Adaptive Control in Trajectory Tracking for Mobile Robots

In this work a neural indirect sliding mode control method for mobile robots is proposed. Due to the nonholonomic property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a kinematics nominal model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate the dynamics of the robot. Using an online adaptation scheme, a neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown nonlinear dynamics. The proposed design simultaneously guarantees the stability of the adaptation of the neural nets and obtains suitable equivalent control when the parameters of the robot model are unknown in advance. The robust adaptive scheme is applied to a mobile robot and shown to be able to guarantee that the output tracking error will converge to zero.     

基于模糊滑模控制器的伺服跟踪控制研究

为了有效地消除精密机床伺服进给系统的参数变化和外部扰动对其跟踪性能的影响,将滑模控制引入其伺服跟踪控制.文章将模糊逻辑与滑模控制相结合提出了一种简捷的模糊滑模控制器设计的方法以减小滑模控制器的颤抖.实验结果表明采用该方法设计的模糊滑模控制器与离散准滑模控制器相比具有较强的鲁棒性和跟踪性能.最后将该控制器用于超精密机床伺服跟踪控制取得了良好的控制效果.     

自适应神经网络四旋翼无人机有限时间轨迹跟踪控制

针对带有模型不确定性和未知外部干扰的四旋翼无人机轨迹跟踪控制问题,提出一种基于径向基(radial basis function, RBF)神经网络的自适应全局快速终端滑模控制方法,确保系统对期望轨迹的有限时间跟踪。该方法考虑到全局快速终端滑模控制在实际应用中的适应性和抖振问题,利用RBF神经网络替代等效控制量,以神经网络的在线学习能力补偿系统内部的不确定性和未知的外部干扰,有效地降低了系统的抖振;根据Lyapunov方法导出的自适应律在线调整神经网络权值,以保证闭环系统的稳定性。通过一系列仿真算例和飞行实验验证了该方法的有效性与可行性,结果表明:该控制方法相对于滑模控制的抖振更小,具有更好的收敛性和抗干扰能力,同时对模型的参数摄动具有更强的鲁棒性。     

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.     

Robust tracking control of nonholonomic dynamic systems with application to the bi-steerable mobile robot

A tracking controller for nonholonomic dynamic systems is proposed which allows global tracking of arbitrary reference trajectories and renders the closed loop system robust with respect to bounded disturbances. The controller is based on [Chwa, D. (2004). Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates. IEEE Transactions on Control Systems Technology, 12(4), 637-644] and shows several generalizations and improvements. The control law for tracking of general nonholonomic systems using inverse kinematic models (IKM) and sliding surfaces is stated. Conditions are proven under which robust tracking is achieved for a specific system. Tracking control is applied to the bi-steerable mobile robot, and simulation results are presented.     

A robust optimal sliding‐mode control approach for magnetic levitation systems

This paper presents a robust optimal sliding‐mode control approach for position tracking of a magnetic levitation system. First, a linear model that represents the nonlinear dynamics of the magnetic levitation system is derived by the feedback linearization technique. Then, the robust optimal sliding‐mode control developed from the linear model is proposed. In the proposed control scheme, the integral sliding‐mode control with robust optimal approach is developed to achieve the features of high performance in position tracking response and robustness to the matched and unmatched uncertainties. Simulation and experimental results from the computer‐controlled magnetic levitation system are illustrated to show the validity of the proposed control approach for practical applications. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

饱和输入下四旋翼无人机滑模轨迹跟踪控制

为解决四旋翼无人机在饱和输入下的轨迹跟踪控制问题,同时兼顾系统存在的参数不确定性和外部风力扰动影响,设计了一种改进的抗干扰自适应鲁棒滑模控制方法;基于六自由度架构,设计四旋翼无人机简化的系统模型,进而降低控制器设计的复杂程度;引入带有误差信号的滑模函数,设计带有误差信号的饱和补偿自适应控制律,同时增加鲁棒控制项,降低由于饱和输入问题带来的抖振影响,并减小参数不确定和外部风力扰动对系统稳定性的影响;系统模型与抗干扰自适应控制律相结合,形成了改进的抗干扰自适应鲁棒滑模控制策略,实现四旋翼无人机的位置轨迹和姿态轨迹的稳定跟踪;最后通过数值仿真与传统PD控制算法进行仿真比较,验证控制方法的有效性和优越性。     

Sliding mode variable structure control for visual servoing system

A visual servoing tracking controller is proposed based on the sliding mode control theory in order to achieve strong robustness against parameter variations and external disturbances. A sliding plane with time delay compensation is presented by the pre-estimate of states. To reduce the chattering of the sliding mode controller, a modified exponential reaching law and hyperbolic tangent function are applied to the design of visual controller and robot joint controller. Simulation results show that the visual servoing control scheme is robust and has good tracking performance.     

Fuzzy sliding mode control for a robot manipulator

This work presents the design of a robust control system using a sliding mode controller that incorporates a fuzzy control scheme. The presented control law superposes a sliding mode controller and a fuzzy logic controller. A fuzzy tuning scheme is employed to improve the performance of the control system. The proposed fuzzy sliding mode control (FSMC) scheme utilizes the complementary cooperation of the traditional sliding mode control (SMC) and the fuzzy logic control (FLC). In other words, the proposed control scheme has the advantages which it can guarantee the stability in the sense of Lyapunov function theory and can ameliorate the tracking errors, compared with the FLC and SMC, respectively. Simulation results for the trajectory tracking control of a two-link robot manipulator are presented to show the feasibility and robustness of the proposed control scheme. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

高阶滑模控制在非完整移动机器人鲁棒输出跟踪中的应用

给出了移动机器人鲁棒输出跟踪的高阶滑模控制器, 它不仅可以削弱滑模控制系统的抖振问题, 还对系统存在的不确定性具有良好的鲁棒性. 数值仿真表明了该控制器的有效性.     

Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design

Combining sliding mode control method with radial basis function neural network (RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle (NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.      

Data‐driven robust backstepping control of unmanned surface vehicles

In this article, a novel data‐driven robust backstepping control (DRBC) approach for tracking of unmanned surface vehicles (USVs) with uncertainties and unknown parametric dynamics has been developed. Main contributions are fourfold: (a) Unlike previous approaches, within the DRBC scheme, backstepping decoupled technique and data‐driven sliding‐mode control (DSMC) can be effectively cohered. (b) Using backstepping philosophy, a new data‐driven PI‐type sliding‐mode surface is devised, such that strong robustness with simple structure can be ensured. (c) Complex unknowns including couplings, uncertainties and parametric dynamics are sufficiently lumped, and are totally compensated by the extended state observer. (d) The entire DRBC scheme eventually achieves accurate tracking of USVs with strong couplings, uncertainties and unknown parametric dynamics. The efficacy and superiority of the proposed DRBC approach is validated on a prototype USV.     

An exponentially convergent adaptive sliding mode control of robot manipulators

A new robust adaptive algorithm for control of robot manipulators is proposed to account for a desired transient response with global exponential convergence of tracking errors without any persistent excitating assumption on the regressor. Its novelty lies in a new dynamic sliding surface that allows a systematic combination of adaptive control and variable structure control to yield a sliding mode inside an adaptive control loop. During sliding mode, parameter uncertainty appears in terms of known variables in such a manner that a new robust parameter estimator with enhanced stability properties is established. On the other hand, if the regressor meets the persistent exciting condition, the global uniform exponential stability of the equilibrium concerning the adaptive closed-loop error equation is easily established. The proposed controller from the VSS viewpoint relaxes the longstanding condition on a priori knowledge of the size of the parametric uncertainty to induce a sliding mode. On the other hand, from the adaptive control viewpoint it relaxes the standard assumption of the persistent excitation on the regressor to obtain the exponential convergence of tracking errors. Also, the stability against time-varying parameters is briefly discussed. Concluding remarks concerning its structural behaviour are given, and computer simulation data show a robust performance.