Tracking control of robot manipulators via output feedback linearization

This paper presents a robot manipulator tracking controller based on output feedback linearization. A sliding mode perturbation observer (SPO) is designed to estimate unmeasurable states and system perturbations that involve system nonlinearities, disturbances and unmodelled dynamics. The use of SPO allows to input/output linearize and decouple the strongly coupled nonlinear robot manipulator system merely by the feedback of joint angles. The controller design does not need an accurate model of the robot manipulator. Simulation studies are undertaken based on a two-link robot manipulator to evaluate the proposed approach. The simulation results show that the proposed controller has more superior tracking control performance, with payload changing in a wide range, in comparison with a sliding mode controller (SMC) designed based on state feedback linearization with full states available. Selected from Journal of Shenzhen University (Science & Engineering), 2005, 22(3)     

Sliding mode controller with sliding perturbation observer based on gain optimization using genetic algorithm

The Stewart platform manipulator is a closed-kinematics chain robot manipulator that is capable of providing high structural rigidity and positional accuracy. However, this is a complex and nonlinear system, so the control performance of the system is not so good. In this paper, a new robust motion control algorithm is proposed. The algorithm uses partial state feedback for a class of nonlinear systems with modeling uncertainties and external disturbances. The major contribution is the design of a robust observer for the state and the perturbation of the Stewart platform, which is combined with a variable structure controller (VSC). The combination of controller and observer provides the robust routine called sliding mode control with sliding perturbation observer (SMCSPO). The optimal gains of SMCSPO, which is determined by nominal eigenvalues, are easily obtained by genetic algorithm. The proposed fitness function that evaluates the gain optimization is to put sliding function. The control performance of the proposed algorithm is evaluated by the simulation and experiment to apply to the Stewart platform. The results showed high accuracy and good performance.     

船体除锈机械手的干扰抑制轨迹跟踪控制

船体外壁除锈喷漆过程中需要控制机械手臂的变幅和伸缩油缸协调动作,以保证机械手臂末端在垂直轨迹方向上的匀速直线运动。针对运动过程中存在的机械手臂的柔性变形不确定性等干扰以及比例阀油缸系统内部状态量的不可测性,运用Lyapunov稳定性理论设计了基于降维观测器的干扰抑制轨迹跟踪控制器,并将所设计控制器对干扰的鲁棒性与传统PID控制进行了仿真对比。同时,应用所设计的控制算法对样机进行了相关测试,验证了所设计的控制器对机械臂外部干扰的抑制作用。     

漂浮基柔性两杆空间机械臂基于状态观测器的鲁棒控制及振动控制

讨论了漂浮基柔性空间机械臂基于状态观测器的鲁棒控制及振动最优控制问题。首先通过合理选择联体坐标系,实现两柔性杆弹性变形之间的解耦;根据拉格朗日方程与动量守恒原理,建立了载体位置无控、姿态受控飘浮基两杆柔性空间机械臂系统的动力学方程。接着利用奇异摄动法,将这个柔性两杆空间机械臂系统分解为一个慢变子系统与一个快变子系统。以此为基础,提出了一个包含慢变控制项与快变控制项的复合控制器。利用动态滑模观测器得到慢变子系统的观测速度矢量,基于这个观测速度矢量设计系统的鲁棒慢变控制律来实现载体姿态、关节轨迹的跟踪。利用线性观测器得到快变子系统的观测速度矢量,基于这个观测速度矢量与线性系统的最优控制理论设计系统的快变控制力矩,实现两柔性杆振动的抑制。最后通过系统的数值仿真,证实了方法的有效性。     

直接驱动型机械手的变结构控制

针对直接驱动型机械手的随动控制问题,提出了一种基于滑动模态扰动观测器的变结构控制器.通过观测由系统的非线性、模型的不确定性和外来干扰所造成的广义扰动,将非线性、强耦合的机械手动力学系统线性化,并解耦为多个单输入、单输出线性系统.控制器的设计不再依赖于机械手的精确模型.在二连杆机械手上做的仿真研究表明,在负载大范围变化的条件下,采用滑动模态扰动观测器的控制系统,比全状态反馈的控制系统具有更好的鲁棒性.     

Adaptive sliding mode control of a piezo-actuated bilateral teleoperated micromanipulation system

Piezoelectric actuators are widely used in micro manipulation applications. However, hysteresis nonlinearity limits the accuracy of these actuators. This paper presents a novel approach for utilizing a piezoelectric nano-stage as the slave manipulator of a teleoperation system based on a sliding mode controller. The Prandtl-Ishlinskii (PI) model is used to model actuator hysteresis in feedforward scheme to cancel out this nonlinearity. The presented approach requires full state and force measurements at both the master and slave sides. Such a system is costly and also difficult to implement. Therefore, sliding mode unknown input observer (UIO) is proposed for full state and force estimations. Furthermore, the effects of uncertainties in the constant parameters on the estimated external forces should be eliminated. So, a robust adaptive controller is proposed and its stability is guaranteed through the Lyapunov criterion. Performance of the proposed control architecture is verified through experiments.     

Extended observer based on adaptive second order sliding mode control for a fixed wing UAV

This paper addresses the design of attitude and airspeed controllers for a fixed wing unmanned aerial vehicle. An adaptive second order sliding mode control is proposed for improving performance under different operating conditions and is robust in presence of external disturbances. Moreover, this control does not require the knowledge of disturbance bounds and avoids overestimation of the control gains. Furthermore, in order to implement this controller, an extended observer is designed to estimate unmeasurable states as well as external disturbances. Additionally, sufficient conditions are given to guarantee the closed-loop stability of the observer based control. Finally, using a full 6 degree of freedom model, simulation results are obtained where the performance of the proposed method is compared against active disturbance rejection based on sliding mode control.     

Neural network adaptive sliding mode control for omnidirectional vehicle with uncertainties

This paper presents a novel neural network adaptive sliding mode control (NNASMC) method to design the dynamic control system for an omnidirectional vehicle. The omnidirectional vehicle is equipped with four Mecanum wheels that are actuated by separate motors, and thus has the omnidirectional mobility and excellent athletic ability in a narrow space. Considering various uncertainties and unknown external disturbances, kinematic and dynamic models of the omnidirectional vehicle are established. The inner-loop controller is designed based the sliding mode control (SMC) method, while the out-loop controller uses the proportion integral derivative (PID) method. In order to achieve the stable and robust performance, the artificial neural network (ANN) based adaptive law is introduced to model and estimated the various uncertainties disturbances. Stability and robustness of the proposed control method are analyzed using the Lyapunov theory. The performance of the proposed NNASMC method is verified and compared with the classical PID controller and SMC controller through both the computer simulation and the platform experiment. Results validate the effectiveness and robustness of the NNASMC method in presence of uncertainties and unknown external disturbances.     

水产养殖用水下移动机械手的耦合动力学分析

对水下移动机械手系统中本体与机械手之间的耦合动力学进行了研究,分别采用指数积方法和凯恩方程对水下移动机械手系统进行了运动分析和动力学建模并进行了求解,模拟了机械手在展开的过程中本体的运动,该研究工作对于进一步了解水下机械手的工作特点和开展机构的控制有重要价值。     

Reachable set estimation for Takagi-Sugeno fuzzy systems against unknown output delays with application to tracking control of AUVs

In this paper, we address the problem of reachable set estimation for continuous-time Takagi-Sugeno (T-S) fuzzy systems subject to unknown output delays. Based on the reachable set concept, a new controller design method is also discussed for such systems. An effective method is developed to attenuate the negative impact from the unknown output delays, which likely degrade the performance/stability of systems. First, an augmented fuzzy observer is proposed to capacitate a synchronous estimation for the system state and the disturbance term owing to the unknown output delays, which ensures that the reachable set of the estimation error is limited via the intersection operation of ellipsoids. Then, a compensation technique is employed to eliminate the influence on the system performance stemmed from the unknown output delays. Finally, the effectiveness and correctness of the obtained theories are verified by the tracking control of autonomous underwater vehicles.     

轻量级电驱水下机械臂设计与运动学分析

设计了一款四功能水下机械臂，并对驱动关节进行了模块化设计和密封测试。为了保证水下机械臂的可靠性，在水下机械臂水下测试前，进行了强度校核和模态分析。为了验证水下机械臂的性能，通过 Ｄ- Ｈ法建立了其运动学模型，在此基础上分别进行了正、逆运动学分析。此外还采用蒙特卡洛法，在正运动学分析的基础上研究了工作空间特点。研究结果将为进一步的运动控制提供有益的帮助。     

水下机器人-机械手系统的动力学分析

随着我国海洋开发事业的发展，水下机器人操作手在水下勘探、水下采矿、海洋石油工程等领域发挥着越来越重要的作用。本文提出了一种运用指数积公式和凯恩方程对水下机器人机械手系统进行了动力学建模的新方法。采用该方法可以在同一个坐标体系中描叙系统的运动学，而且在建立动力学模型中可以避免大量的求导运算，并可以得到最少数目的微分方程。模型中考虑了海水的拖曳阻力、机器人与机械手之间的相互作用、推进器推力等因素。研究表明指数积-凯恩方法是一种建立水下机器人-机械手的一种有效方法。     

基于自适应滑模控制器的机械臂运动控制方法

由于无法消除机械臂运动过程中存在的高频振动,导致运动控制方法存在跟踪精度低、控制稳定性差和控制性能差等问题。对此,提出一种基于自适应滑膜控制器的机械臂运动控制方法,在机械臂动力学模型的基础上设计非线性观测器,对机械臂控制系统中存在的干扰信号进行观测,设计自适应滑膜控制器对干扰信号进行补偿。将补偿器引入自适应滑膜控制器中,其主要作用是抑制机械臂在运动过程中存在的高频振动,以提高控制稳定性,通过 Lyapunov 函数设计自适应滑膜控制器的总控制律,根据总控制律利用改进后的自适应滑膜控制器完成机械臂的运动控制。实验结果表明,所提方法的跟踪精度高、稳定性好、控制性能高。     

A compound control strategy combining velocity compensation with ADRC of electro-hydraulic position servo control system

In order to enhance the anti-jamming ability of electro-hydraulic position servo control system at the same time improve the control precision of the system, a compound control strategy that combines velocity compensation with Active Disturbance Rejection Controller (ADRC) is proposed, and the working principle of the compound control strategy is given. ADRC controller is designed, and the extended state observer is used for observing internal parameters uncertainties and external disturbances, so that the disturbances of the system are suppressed effectively. Velocity compensation controller is designed and the compensation model is derived to further improve the positioning accuracy of the system and to achieve the velocity compensation without disturbance. The compound control strategy is verified by the simulation and experiment respectively, and the simulation and experimental results show that the electro-hydraulic position servo control system with ADRC controller can effectively inhibit the external disturbances, the precise positioning control is realized after introducing the velocity compensation controller, and verify that the compound control strategy is effective.     

基于观测器和全局收缩映射的设定点控制

针对具有参数不确定性并且仅有位置信息可测的机器人系统,本文首先研究了带有速度近似的■+有偏标称重力补偿的设定点控制方法。该方法利用线性观测器理论对不可测速度信号进行近似,基于此伪速度信号设计的设定点控制虽然可以保证闭环系统全局稳定,但由于无法对重力精确补偿,因此系统存在静差。为消除静差,本文借助全局收缩映射理论,每到闭环系统输出达到稳态时,通过重复修正线性观测器参数使静差逐步收敛到零,保证系统全局渐进稳定。利用所设计的控制器对并行机器人进行设定点控制,仿真实验表明,虽然不同的设计参数对控制效果有所影响,但都能够确保系统输出收敛到标称点。     

基于改进扩展状态观测器的四旋翼无人机轨迹鲁棒跟踪控制

针对四旋翼无人机在轨迹跟踪过程中会受到内外部扰动、模型误差等不确定性因素的影响,本文提出了一种基于改进型扩展状态观测器的积分滑模控制方案。具体来讲,首先,将四旋翼无人机系统存在的模型误差以及内外部扰动等不确定性因素视作集总干扰,通过借鉴的改进扩展状态观测器对其进行观测;进而,在此基础上,进一步考虑四旋翼无人机系统控制的连续性,基于四旋翼无人机轨迹误差、速度误差、姿态角误差和姿态角速度误差设计积分滑模控制器,分析了系统的稳定性并分别进行了数值仿真和实机实验。结果表明,采用本文算法时,在数值仿真中,各状态跟踪误差不超过1%,跟踪精度最高;在实机实验中,位置跟踪误差总体上能控制在20%以下。因此,本文方法具备有效性和可行性。     

Trajectory tracking for two-degree of freedom helicopter system using a controller-disturbance observer integrated design

Trajectory tracking control for helicopters, which are widely used in severe situations such as military and rescue missions, is a challenging field of research. In helicopter system, the stability problem and predefined trajectories tracking are main challenges, especially in the presence of external disturbances and dynamic model uncertainties. Hence, a robust control design is needed for tracking the desired references. There has been a lot of motivation for solving these problems with simpler methods and also reducing the couplings in the helicopter system to achieve better performance, as the presented paper attempts to fill these gaps. This paper focuses on designing control laws for two-degree of freedom helicopter system while assuring the closed-loop stability. A nonlinear disturbance observer-based control (NDOBC) is designed for attenuating the effects of exogenous disturbances. Trajectory tracking controller and nonlinear disturbance observer are formulated in the form of two linear matrix inequality (LMI) problems. The closed-loop system stability, including controller and observer, is investigated by Lyapunov theorem. The effectiveness of the proposed design for tracking the trajectories (vertical flight and pitch angle rotor blade) and disturbance estimation is verified by simulation results.     

Nonlinear PID control to improve the control performance of the pneumatic artificial muscle manipulator using neural network

A novel actuator system which has achieved increased popularity to provide these advantages such as high strength and power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available, cheap power source, inherent safety and mobility assistance to humans performing tasks has been the utilization of the pneumatic artificial muscle (PAM) manipulator, in recent times. However, the complex nonlinear dynamics of the PAM manipulator makes it a challenging and appealing system for modeling and control design. The problems with the time variance, compliance, high hysteresis and nonlinearity of pneumatic systems have made it difficult to realize precise position control with high speed. In order to realize satisfactory control performance, the effect of nonlinear factors contained in thePAM manipulator must be considered. The purpose of this study is to improve the control performance of thePAM manipulator using a nonlinearPID controller. Superb mixture of conventionalPID controller and the neural network, which has powerful capability of learning, adaptation and tackling nonlinearity, brings us a novel nonlinearPID controller using neural network. This proposed controller is appropriate for a kind of plants with nonlinearity uncertainties and disturbances. The experiments were carried out in practicalPAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through the experiments, which suggests its superior performance and disturbance rejection.     

Performance improvement of pneumatic artificial muscle manipulators using magneto-rheological brake

A novel pneumatic artificial muscle actuator (PAM actuator), which has achieved increased popularity to provide the advantages such as high strength and high power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available and cheap power source, inherent safety and mobility assistance to humans performing tasks, has been regarded during the recent decades as an interesting alternative to hydraulic and electric actuators However, some limitations still exist, such as the air compressibility and the lack of damping ability of the actuator bring the dynamic delay of the pressure response and cause the oscillatory motion Then it is not easy to realize the performance of transient response of pneumatic artificial muscle manipulator (PAM manipulator) due to the changes in the external inertia load with high speed In order to realize satisfactory control performance, a variable damper — Magneto-Rheological Brake (MRB), is equipped to the joint of the manipulator Superb mixture of conventional PID controller and a phase plane switching control method brings us a novel controller This proposed controller is appropriate for a kind of plants with nonhnearity, uncertainties and disturbances. The experiments were carried out in practical PAM manipulator and the effectiveness, of the proposed control algorithm was demonstrated through experiments, which had proved that the stability of the manipulator can be improved greatly in a high gain control by using MRB with phase plane switching control method and without regard for the changes of external inertia loads