Optimal robust voltage control of electrically driven robot manipulators

This paper develops a novel robust optimal voltage control of electrically driven robot manipulators. The whole robotic system including the robot manipulator and motors is considered in the control problem. Particle Swarm Optimization (PSO) is used to optimize the control design parameters, thus the performance of control system is highly improved. Beside this, we use Voltage Control Strategy (VCS) which is more robust, faster, less coupled, and less computational compared with the common strategy called as Torque Control Strategy (TCS). To state these advantages, it is reasoning that the TCS is dependent on the manipulator dynamics whereas the VCS can be free from it. The robust optimal voltage control is verified by convergence analysis. A comparative study between the VCS and the TCS confirms superiority of the VCS to the TCS. Simulation results present effectiveness of the proposed methods applied on a spherical robot manipulator driven by permanent magnet dc motors.     

Decentralized direct adaptive fuzzy control of robots using voltage control strategy

Decentralized control is the most favorite control of robot manipulators due to computational simplicity and ease of implementation. Beside that, adaptive fuzzy control efficiently controls uncertain nonlinear systems. These motivate us to design a decentralized fuzzy controller. However, there are some challenging problems to guarantee stability. The state-space model of the robotic system including the robot manipulator and motors is in a noncompanion form, multivariable, highly nonlinear, and heavily coupled with a variable input gain matrix. For this purpose, adaptive fuzzy control may use all variable states. As a result, it suffers from computational burden. To overcome the problems, we present a novel decentralized Direct Adaptive Fuzzy Control (DAFC) of electrically driven robot manipulators using the voltage control strategy. The proposed DAFC is simple, in a decentralized structure with high-accuracy response, robust tracking performance, and guaranteed stability. Instead of all state variables, only the tracking error of every joint and its derivative are given as the inputs of the controller. The proposed DAFC is simulated on a SCARA robot driven by permanent magnet dc motors. Simulation results verify superiority of the decentralized DAFC to a decentralized PD-fuzzy controller.     

Discrete adaptive fuzzy control for asymptotic tracking of robotic manipulators

This paper presents a novel discrete adaptive fuzzy controller for electrically driven robot manipulators. It addresses how to overcome the nonlinearity, uncertainties, discretizing error and approximation error of the fuzzy system for asymptotic tracking control of robotic manipulators. The proposed controller is model-free in the form of discrete Mamdani fuzzy controller. The parameters of fuzzy controller are adaptively tuned using an adaptive mechanism derived by stability analysis. A robust control term is used to compensate the approximation error of the fuzzy system for asymptotic tracking of a desired trajectory. The controller is robust against all uncertainties associated with the robot manipulator and actuators. It is easy to implement since it requires only the joint position feedback. Compared with fuzzy controllers which employ all states to guarantee stability, the proposed controller is very simpler. Stability analysis and simulation results show its efficiency in the tracking control.     

A particle swarm optimization approach for fuzzy sliding mode control for tracking the robot manipulator

In this paper, an optimal fuzzy sliding mode controller is used for tracking the position of robot manipulator, is presented. In the proposed control, initially by using inverse dynamic method, the known sections of a robot manipulator’s dynamic are eliminated. This elimination is done due to reduction over structured and unstructured uncertainties boundaries. In order to overcome against existing uncertainties for the tracking position of a robot manipulator, a classic sliding mode control is designed. The mathematical proof shows the closed-loop system in the presence of this controller has the global asymptotic stability. Then, by applying the rules that are obtained from the design of classic sliding mode control and TS fuzzy model, a fuzzy sliding mode control is designed that is free of undesirable phenomena of chattering. Eventually, by applying the PSO optimization algorithm, the existing membership functions are adjusted in the way that the error tracking robot manipulator position is converged toward zero. In order to illustrate the performance of the proposed controller, a two degree-of-freedom robot manipulator is used as the case study. The simulation results confirm desirable performance of optimal fuzzy sliding mode control.     

基于有限时间收敛的双臂空间机器人捕获卫星主动对接力/位姿阻抗控制

针对双臂空间机器人捕获卫星主动对接力/位姿阻抗控制进行了研究.为防止捕获过程中机械臂末端执行器与卫星接触、碰撞时产生的冲击载荷对机器人关节造成冲击破坏,在各关节电机与机械臂之间加入了一种弹簧阻尼缓冲机构.该机构可通过弹簧实现冲击力矩的卸载,阻尼器则用于因弹簧引起的柔性振动的抑制.为解决捕获过程中的非完整动力学约束及捕获后混合体系统的协调控制问题,结合牛顿第三定律、捕获点的速度约束及闭链几何约束,获得捕获后混合体系统的动力学方程,且通过动量守恒关系计算碰撞冲击效应与碰撞冲击力.通过分析对接装置在载体坐标系下的运动学关系,建立对接装置相对载体的运动雅可比矩阵,并基于此建立基于力的二阶线性阻抗模型,实现对接装置输出力的精确控制.考虑到主动对接操作过程要求控制器具有收敛速度快,控制精度高的特点,通过结合终端滑模与超扭滑模的特点,提出一种非奇异快速终端滑模阻抗控制策略.该策略即能实现主动对接操作中位姿与输出力的快速响应,又能有效地抑制滑模的抖振以保证控制精度.通过Lyapunov定理证明系统的稳定性;利用数值模拟验证缓冲装置的抗冲击性能及所提阻抗控制策略的有效性.     

Robust control of flexible-joint robots using voltage control strategy

So far, control of robot manipulators has frequently been developed based on the torque-control strategy. However, two drawbacks may occur. First, torque-control laws are inherently involved in complexity of the manipulator dynamics characterized by nonlinearity, largeness of model, coupling, uncertainty and joint flexibility. Second, actuator dynamics may be excluded from the controller design. The novelty of this paper is the use of voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators. In addition, a novel method of uncertainty estimation is introduced to obtain the control law. The proposed control approach has important advantages over the torque-control approaches due to being free of manipulator dynamics. It is computationally simple, decoupled, well-behaved and has a fast response. The control design includes two interior loops; the inner loop controls the motor position and the outer loop controls the joint position. Stability analysis is presented and performance of the control system is evaluated. Effectiveness of the proposed control approach is demonstrated by simulations using a three-joint articulated flexible-joint robot driven by permanent magnet dc motors.     

Detumbling strategy and coordination control of kinematically redundant space robot after capturing a tumbling target

This paper focuses on the motion planning to detumble and control of a space robot to capture a non-cooperative target satellite. The objective is to construct a detumbling strategy for the target and a coordination control scheme for the space robotic system in post-capture phase. First, the dynamics of the kinematically redundant space robot after grasping the target is presented, which lays the foundation for the coordination controller design. Subsequently, optimal detumbling strategy for the post-capture phase is proposed based on the quartic B\(\acute{\text{ e }}\)zier curves and adaptive particle swarm optimization algorithm subject to the specific constraints. Both detumbling time and control torques were taken into account for the generation of the optimal detumbling strategy. Furthermore, a coordination control scheme is designed to track the designed reference path while regulating the attitude of the chaser to a desired value. The space robot successfully dumps the initial velocity of the tumbling satellite and controls the base attitude synchronously. Simulation results are presented for detumbling a target with rotational motion using a seven degree-of-freedom redundant space manipulator, which demonstrates the feasibility and effectiveness of the proposed method.     

System modeling and tracking control of mobile manipulator subjected to dynamic interaction and uncertainty

Trajectory tracking of a mobile manipulator is a challenging research because of its complex nonlinearity and dynamics. This paper presents an adaptive control strategy for trajectory tracking of a mobile manipulator system that consists of a wheeled platform and a modular manipulator. When a robot system moves in the presence of sliding, it is difficult to accurately track its trajectory by applying the backstepping approach, even if we employ a non-ideal kinematic model. To address this problem, we propose using a combination of adaptive fuzzy control and backstepping approach based on a dynamic model. The proposed control scheme considers the dynamic interaction between the platform and manipulator. To accurately track the trajectory, we propose a fuzzy compensator in order to compensate for modeling uncertainties such as friction and external disturbances. Moreover, to reduce approximation errors and ensure system stability, we include a robust term to the adaptive control law. Simulation results obtained by comparing several cases reveal the presence of the dynamic interaction and confirm the robustness of the designed controller. Finally, we demonstrate the effectiveness and merits of the proposed control strategy to counteract the modeling uncertainties and accurately track the trajectory.     

基于Clamped B样条的空间非合作目标抓捕策略研

空间机械臂技术是未来实施在轨服务与维护任务的关键技术之一. 利用机械臂对空间非合作目标, 特别是翻滚目标的抓捕仍然存在巨大的挑战. 本文提出一种基于Clamped B样条的空间非合作目标抓捕策略方案. 在对非合作目标与空间机械臂运动学与动力学分析的基础上, 结合非合作目标被空间机械臂抓捕后的动静态对偶性分析, 构建抓捕后的力可操作度椭球作为抓捕策略设计的优化指标. 其次, 考虑目标的运动预测和空间机械臂的抓捕能力图谱构建, 确定空间机械臂应对目标的最优抓捕时机与抓捕终端状态. 基于Clamped B样条对空间机械臂各关节轨迹进行时间归一化参数描述, 并对抓捕过程中的机械臂关节角、速度、避撞、抓捕走廊等约束进行数学变换, 最终将抓捕策略转换为多约束、多目标的非线性优化问题, 利用自适应惯性权重的粒子群优化算法进行求解. 将所设计的抓捕策略应用于空间七自由度运动学冗余机械臂, 实现了对空间中翻滚目标的成功捕获, 验证了所提抓捕策略的可行性与有效性.      

Real-time robust adaptive control of robots subjected to actuator voltage constraint

This paper is concerned with the problem of design and implementation of a robust adaptive control strategy for electrically driven robots while considering to the constraints on the actuator voltage input. The proposed approach provides a flexible design framework and stable to deal with robustness compared with many other adaptive controllers, such as halting/slowing adaption techniques and adaptively adjusting command signal, which are proposed for robotic applications. The control design procedure is based on a new form of universal approximation theory and using Stone–Weierstrass theorem, to avoid saturation besides being robust against both structured and unstructured uncertainties associated with external disturbances and actuated manipulator dynamics. Moreover, the proposed approach eliminates problems arising from classic adaptive feedforward control scheme. The analytical studies as well as experimental results produced using MATLAB/SIMULINK external mode control on a two degree of freedom electrically driven robot demonstrate high performance of the proposed control schemes.     

Nonlinear robust and optimal control of robot manipulators

In this paper, we propose a new optimal control method for robust control of nonlinear robot manipulators. Many industrial robot systems are required to perform relatively large angular movement with sufficient accuracy. In real circumstances, highly nonlinear manipulator dynamics and uncertainties such as unknown load placed on the manipulator, external disturbance, and joint friction make the precise control of manipulators a very challenging task. The main contribution of this work is to develop a new robust control strategy to accomplish the precise control of robot manipulators under load uncertainty using a nonlinear optimal control formulation and solution. This methodology is based on the underlying relation between the robust stability and performance optimality. A class of robust control problems can be transformed to an equivalent optimal control problem by incorporating the uncertainty bounds into the cost functional. The θ-D optimal control approach is utilized to find an approximate closed-form feedback solution to the resultant nonlinear optimal control problem via a perturbation process. Numerical simulations show that the proposed robust controller is able to control the robot manipulator precisely under large load variations.     

Robust control of electrically driven robots by adaptive fuzzy estimation of uncertainty

This paper presents a novel robust decentralized control of electrically driven robot manipulators by adaptive fuzzy estimation and compensation of uncertainty. The proposed control employs voltage control strategy, which is simpler and more efficient than the conventional strategy, the so-called torque control strategy, due to being free from manipulator dynamics. It is verified that the proposed adaptive fuzzy system can model the uncertainty as a nonlinear function of the joint position error and its time derivative. The adaptive fuzzy system has an advantage that does not employ all system states to estimate the uncertainty. The stability analysis, performance evaluation, and simulation results are presented to verify the effectiveness of the method. A?comparison between the proposed Nonlinear Adaptive Fuzzy Control (NAFC) and a Robust Nonlinear Control (RNC) is presented. Both control approaches are robust with a very good tracking performance. The NAFC is superior to the RNC in the face of smooth uncertainty. In contrast, the RNC is superior to the NAFC in the face of sudden changes in uncertainty. The case study is an articulated manipulator driven by permanent magnet dc motors.     

Nonlinear control of electrical flexible-joint robots

This paper is devoted to the nonlinear tracking control of electrically driven flexible-joint manipulators using the voltage control strategy. Despite the torque control laws that are involved in the complexity of manipulator dynamics, the proposed control law is free from manipulator dynamics. This novelty is for adopting the voltage control strategy to derive a simple robust adaptive control under both structured and unstructured uncertainty. The proposed control approach has a fast response with a good tracking performance under the well-behaved control efforts in the form of decentralized control. The control method is justified by the stability analysis and simulated on a flexible-joint electrically driven robot manipulator.     

Image based visual servoing for robot positioning tasks

Visual servoing has become a popular paradigm for the control of complex robotic systems: this sensor based approach exploits the image informations provided by one ore more cameras in a feedback control loop to drive the system to the desired configuration. Here authors will refers to a monocular system where the camera is mounted on the end effector of a 6-DOF manipulator. Among different Visual Servoing approaches Image Based Visual Servoing (IBVS) has been the most investigated in the literature because of its nice properties of robustness with respect to both robot modeling and camera calibration errors: in IBVS the control loop is in fact directly closed in the image; moreover IBVS doesn’t require the knowledge of the target/scene model (model-free approach). Despite its advantages IBVS may be affected by singularity and local minima problems of the control law: these drawbacks arise especially when the initial and the goal camera images respectively corresponding to the actual and desired system configurations are very different (i.e for large system displacements). To overcome these problems an image path planning can be exploited to ensure system convergence. In this paper author presents an off-line image path planning that can be used to execute system positioning task also in presence of large camera displacements: planning trajectories has been developed such as to make the robot end effector move on a 3D helix, connecting the initial and the desired arm configuration, by generating feasible robot twist-screws and keeping the target in the image field of view. During control execution also 3D target informations are retrieved through an adaptive estimation law. Both simulations and experimental results show the feasibility of the proposed approach.     

空间机器人捕获卫星操作基于柔顺装置的无源模糊避撞柔顺控制

讨论了漂浮基空间机器人在轨捕获非合作卫星过程避免关节受冲击及过载破坏的避撞柔顺控制问题。在关节电机与机械臂之间配置了一种柔顺装置——旋转型串联弹性执行器(RSEA),其作用一是在捕获阶段,通过其内置弹簧的变形来缓冲捕获过程中被捕获卫星对空间机器人关节产生的冲击能量;二是在捕获完成后的镇定运动阶段,结合所设计的避撞柔顺策略来适时开关关节电机以保证关节冲击力矩受限在安全范围。首先,根据拉格朗日法及牛顿-欧拉法分别建立了含柔顺装置空间机器人与目标卫星系统的动力学方程;之后,结合整个系统动量守恒关系、系统运动几何及位置约束关系,建立了捕获操作后两者形成混合体系统的动力学方程。在此基础上,针对捕获操作后不稳定的混合体系统,提出了一种基于无源性理论的避撞柔顺模糊控制方案以实现其镇定控制。最后,通过仿真实验验证了所提避撞柔顺策略的有效性。     

Adaptive neural impedance control for electrically driven robotic systems based on a neuro-adaptive observer

Nonlinear Dynamics - This paper proposes an adaptive neural impedance control (ANIC) strategy for electrically driven robotic systems, considering system uncertainties and external disturbances....     

Dynamic delayed feedback control for stabilizing the giant swing motions of an underactuated three-link gymnastic robot

This paper investigates the dynamics of the giant swing motions of an underactuated three-link gymnastic robot moving in a vertical plane by means of dynamic delayed feedback control (DDFC). DDFC, being one of useful methods to overcome the so-called odd number limitation in controlling a chaotic discrete-time system, is extended to control a continuous-time system such as a 3-link gymnastic robot with passive joint. Meanwhile, a way to calculate the error transfer matrix and the input matrix which are necessary for discretization is proposed, based on a Poincaré section which is defined to regard the target system as a discrete-time system. Moreover, the stability of the closed-loop system by the proposed control strategy is discussed. Furthermore, some numerical simulations are presented to show the effectiveness in controlling a chaotic motion of the 3-link gymnastic robot to a periodic giant swing motion.     

Fuzzy adaptive output feedback control for robotic systems based on fuzzy adaptive observer

In this paper, a fuzzy adaptive output feedback control scheme based on fuzzy adaptive observer is proposed to control robotic systems with parameter uncertainties and external disturbances. It is supposed that only the joint positions of the robotic system can be measured, whereas the joint velocities are unknown and unmeasured. First, a fuzzy adaptive nonlinear observer is presented to estimate the joint velocities of robotic systems, and the observation errors are analyzed using strictly positive real approach and Lyapunov stability theory. Next, based on the observed joint velocities, a fuzzy adaptive output feedback controller is developed to guarantee stability of closed-loop system and achieve a certain tracking performance. Based on the Lyapunov stability theorem, it is proved that all the signals in closed-loop system are bounded. Finally, simulation examples on a two-link robotic manipulator are presented to show the efficiency of the proposed method.     

Study on vibration reduction and mobility improvement for?the flexible manipulator via redundancy resolution

The flexible redundant manipulator, i.e., the flexible manipulator with redundant rigid degrees of freedom, possesses the same kinematic redundancy property as the rigid redundant manipulator. Some undesired effects on the flexible redundant manipulator are expected to alleviate via kinematic redundancy. Due to the presence of structural flexibility, a manipulator will inevitably vibrate when performing tasks. Therefore, how to reduce its vibration responses is a significant problem. Moreover, the manipulator??s mobility, i.e., its ability to move, is another important issue, because good mobility is a desirable goal for almost all robotic manipulator systems. In this paper, how to reduce vibration and improve mobility is studied for the flexible redundant manipulator. Firstly, a method for vibration control via redundancy resolution is put forward. Secondly, the self-motions satisfying vibration reduction are analyzed, and its additional optimization ability is revealed. Based on this ability, a strategy is proposed to both reduce vibration and improve mobility for the flexible redundant manipulator. Finally, simulation results demonstrate the effectiveness of this strategy.