Robust adaptive motion/force tracking control design for uncertain constrained robot manipulators

In the presence of uncertain constraint and robot model, an adaptive controller with robust motion/force tracking performance for constrained robot manipulators is proposed. First, robust motion and force tracking is considered, where a performance criterion containing disturbance and estimated parameter attenuations is presented. Then the proposed controller utilizes an adaptive scheme and an auxiliary control law to deal with the uncertain environmental constraint, disturbances, and robotic modeling uncertainties. After solving a simple linear matrix inequality for gain conditions, the effect from disturbance and estimated parameter errors to motion/force errors is attenuated to an arbitrary prescribed level. Moreover, if the disturbance and estimated parameter errors are square-integrable, then an asymptotic motion tracking is achieved while the force error is as small as the inversion of control gain. Finally, numerical simulation results for a constrained planar robot illustrate the expected performance.     

Maneuverability modeling and trajectory tracking for fish robot

This study develops a 6-DOF mathematical model for a robotic fish that considers surge, sway, heave, roll, pitch, and yaw. The model considers the conditions of a fish swimming in ocean current perturbations similar to the ocean current perturbations of the slender-body autonomous underwater vehicles. For swimming and turning behaviors, a nonlinear, dynamic, carangiform locomotion model is derived by using a planar four-link model. A 2-DOF barycenter mechanism is proposed to provide body stabilization and to serve as an actuating device for active control design. A barycenter control scheme is developed to change the center of gravity of the robot fish body by moving balancing masses along two axes. The projected torque on x and y axes propel pitch and roll angles to the desired settings. A Stabilizing controller, fish-tail mechanism, rigid body dynamics, and kinematics are incorporated to enable the fish robot to move in three dimensional space. Simulation results have demonstrated maneuverability and control system performance of the developed controller which is proposed to conduct path tracking of the robot fish as it swims under current perturbations.     

Adaptive manipulator trajectory control using neural networks

A unified study of adaptive control and neural network based control schemes for the trajectory tracking problem of robot manipulators is presented. Efficacy of parametrized adaptive algorithms in compensating the structured uncertainties in robot dynamics is verified through extensive simulation. The ability of neural networks to provide a robust adaptive framework in the presence of both structured and unstructured uncertainties is investigated. A case study is carried out in support of a parametrized adaptive scheme using neural networks. Simulation results clearly indicate that the neural network based adaptive controller achieves better tracking in the presence of parametric uncertainties as well as unmodelled effects compared to the simple direct adaptive scheme.     

Direct adaptive control of manipulators in cartesian space

A new adaptive-control scheme for direct control of manipulator end effector to achieve trajectory tracking in Cartesian space is developed in this article. The control structure is obtained from linear multivariable theory and is composed of simple feedforward and feedback controllers and an auxiliary input. The direct adaptation laws are derived from model reference adaptive control theory and are not based on parameter estimation of the robot model. The utilization of adaptive feedforward control and the inclusion of auxiliary input are novel features of the present scheme and result in improved dynamic performance over existing adaptive control schemes. The adaptive controller does not require the complex mathematical model of the robot dynamics or any knowledge of the robot parameters or the payload, and is computationally fast for on-line implementation with high sampling rates. The control scheme is applied to a two-link manipulator for illustration.     

基于动力学与控制统一模型的蛇形机器人速度跟踪控制方法研究

对带有被动轮的蛇形机器人进行速度跟踪控制时,利用传统的动力学建模方法得到的动力学方程复杂且不利于控制器的设计. 本文基于微分几何的方法将带有被动轮的蛇形机器人动力学投影到速度分布空间中, 得到了动力学与控制统一模型, 更有利于速度跟踪控制器的设计. 考虑到蛇形机器人在进行速度跟踪时容易出现奇异位形, 提出增加头部扰动速度的方法. 基于头部扰动速度和统一模型, 提出避免奇异位形的速度跟踪控制方法, 最后通过逆向动力学得到控制力矩. 文中对速度跟踪控制进行了数值仿真和实验验证. 仿真和实验结果表明, 提出的速度跟踪控制方法能够跟踪想要方向的速度, 并且在跟踪过程中可以有效地避免奇异位形.     

Adaptive force and position control of manipulators

The article presents simple methods for the design of adaptive force and position controllers for robot manipulators within the hybrid control architecture. The force controller is composed of an adaptive PID feedback controller, an auxiliary signal, and a force feedforward term, and achieves tracking of desired force setpoints in the constraint directions. The position controller consists of adaptive feedback and feedforward controllers as well as an auxiliary signal, and accomplishes tracking of desired position trajectories in the free directions. The controllers are capable of compensating for dynamic cross-couplings that exist between the position and force control loops in the hybrid control architecture. The adaptive controllers do not require knowledge of the complex dynamic model or parameter values of the manipulator or the environment. The proposed control schemes are computationally fast and suitable for implementation in online control with high sampling rates. The methods are applied to a two-link manipulator for simultaneous force and position control. Simulation results confirm that the adaptive controllers perform remarkably well under different conditions.     

Analysis of Creeping Locomotion of a Snake-like Robot on a Slope

The diverse locomotion modes and physiology of biological snakes make them supremely adapted for their environment. To model the noteworthy features of these snakes we have developed a snake-like robot that has no forward direction driving force. In order to enhance the ability of our robot to adapt to the environment, in this study we investigate the creeping locomotion of a snake-like robot on a slope. A computer simulator is presented for analysis of the creeping locomotion of the snake-like robot on a slope, and the environmentally-adaptable body shape for our robot is also derived through this simulator.     

非完整移动机器人的神经网络鲁棒自适应控制

在非完整移动机器人轨迹跟踪问题中,针对机器人运动学与动力学模型的参数和非参数不确定性,提出了一种混合神经网络鲁棒自适应轨迹跟踪控制器,该控制器由运动学控制器和动力学控制器两部分组成;其中,采用了参数自适应的径向基神经网络对运动学模型的未知部分进行了建模,并采用权值在线调整的单层神经网络和自适应鲁棒控制项构成了动力学控制器;基于Lyapunov方法的设计过程保证了系统的稳定性和收敛性,仿真结果证明了算法的有效性。     

Analysis of creeping locomotion of a snake-like robot

Snakes perform many kinds of movement adapted to the environment. Utilizing the snake (its forms and motion) as a model to develop a snake-like robot, that performs the snake's function, is important for generating a new type of locomotion and expanding the possible uses of robots. In this study, we developed a simulator to simulate the creeping locomotion of the snake-like robot, in which the robot dynamics is modeled and the interaction with the environment is considered through Coulomb friction. This simulator makes it possible to analyze creeping locomotion with normaldirection slip, adding to the glide along the tangential direction. Through the developed simulator, we investigate the snake-like robot creeping locomotion which is generated only by swinging each of the joints from side to side and discuss the optimal creeping locomotion of the snake-like robot that is adapted to the environment.     

非完整移动机器人轨迹跟踪自适应控制器设计

针对轮式移动机器人的非完整运动学模型,将自适应反演控制技术和李亚普诺夫稳定性理论应用于机器人轨迹跟踪控制,设计了具有全局渐近稳定性的自适应轨迹跟踪控制器,并在Matlab环境下实现了移动机器人对直线和椭圆2种轨迹追踪的仿真实验.实验表明:该控制方法在轨迹跟踪控制中有较好的航向跟踪效果,对机器人非完整系统模型的非线性特性...     

Robust neural network–based tracking control and stabilization of a wheeled mobile robot with input saturation

This paper presents a robust neural network–based control scheme to deal with the problem of tracking and stabilization simultaneously for a wheeled mobile robot subject to parametric uncertainties, external disturbances, and input saturation. At first, a new error‐state transformation scheme is designed by introducing some auxiliary variables as an additional virtual control signals to reduce the adverse effect caused by the underactuation. These variables can change their structures for different desired trajectories to be tracked. Then, a robust control law is proposed combining with a kinematic controller and a dynamic controller, while a three‐layer neural network system is applied to approximate model uncertainties. Stability analysis via the Lyapunov theory shows that the proposed controller can make tracking errors converge to bounded neighborhoods of the origin. Finally, some simulation results are illustrated to verify the effectiveness of the proposed control strategy.     

Semi-decentralized adaptive fuzzy control for cooperativemultirobot systems with H∞ motion/internal forcetracking performance

We present a semi-decentralized adaptive fuzzy control scheme for cooperative multirobot systems to achieve H(infinity) performance in motion and internal force tracking. First, we reformulate the overall system dynamics into a fully actuated system with constraints. To cope with both parametric and nonparametric uncertainties, the controller for each robot consists of two parts: 1) model-based adaptive controller; and 2) adaptive fuzzy logic controller (FLC). The model-based adaptive controller handles the nominal dynamics which results in both zero motion and internal force errors for a pure parametric uncertain system. The FLC part handles the unstructured dynamics and external disturbances. An H(infinity) tracking problem defined by a novel performance criterion is given and solved in the sequel. Hence, a robust controller satisfying the disturbance attenuation is derived being simple and singularity-free. Asymptotic convergence is obtained when the fuzzy approximation error is bounded with finite energy. Maintaining the same results, the proposed controller is further simplified for easier implementation. Finally, the numerical simulation results for two cooperative planar robots transporting an object illustrate the expected performance.     

Decentralized adaptive control of robot manipulators

A decentralized adaptive control scheme is proposed for the trajectory tracking of a general n-degree-of-freedom robot manipulator. The robot is considered as a set of decoupled second-order systems with disturbances. The controller consists of feedforward from the desired trajectory based on the “inverse system” of the model, PID feedback from the actual trajectory, and auxiliary input for the compensation of the neglected terms in modeling in each subsystem. The gain is derived in diagonal matrix form, and is adjusted by the model reference adaptive control theory based on the Lyapunov's direct method. The result is high accuracy in path tracking despite the high speed, load change, and sudden torque disturbances. Numerical simulations on.a planar two-link robot manipulator are presented to show the performance under various practical considerations.     

NSGA-Ⅱ在蛇形机器人中的优化与控制

研究蛇形机器人蜿蜒运动步态的优化与控制问题。结合摩擦力模型,并分析蛇形机器人运动步态模型,根据基于闭环反馈的控制系统结构运用PID控制器对其步态进行跟踪控制,在此基础上采用基于非支配排序遗传算法(NSGA-Ⅱ)对步态进行优化,该优化方法实现对闭环反馈跟踪控制系统的参数优化。仿真结果表明,NSGA-Ⅱ算法能达到变量优化目的,在功率和速度之间寻找最优值,对于解决蛇形机器人运动步态多目标优化问题是可行有效的。     

Robust control of robot manipulators with fast load adaptation

Many adaptive robot controllers have been proposed in the literature to solve manipulator trajectory tracking problems for high-speed operations in the presence of parameter uncertainties. However, most of these controllers stem from the applications of the existing adaptive control theory, which is traditionally focused on tracking slowly time-varying parameters. In fact, manipulator dynamics have fast transient processes for high-speed operations and load changes are abrupt. These observations motivate the present research to incorporate change detection techniques into self-tuning schemes for tracking abrupt load variations and achieving fast load adaptation. To this end, a robustly global stabilizing controller for a robot model with parametric and non-parametric uncertainies is developed based on the Lyapunov second method, and it is then made adaptive via the self-tuning regulator concept. The two-model approach to online change detection in load is used and the estimation algorithm is reinitialized once load changes are detected. This allows a much faster adaptive identification of load parameters than the ordinary forgetting factor approach. Simulation results demonstrate that the proposed controller achieves better tracking accuracy than the existing adaptive and non-adaptive controllers.     

A discrete-time adaptive control scheme for robot manipulators

A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.     

performance control of robot manipulators with kinematics,dynamics and actuator uncertainties

This paper deals with the task‐space trajectory tracking control problem of robot manipulators. An improved adaptive backstepping controller is proposed to deal with the uncertainties in kinematics, dynamics, and actuator modeling. To avoid the explosion of computation in conventional backstepping techniques, a modified dynamic surface control algorithm is proposed, which guarantees the asymptotic convergence rather than the uniformly ultimately boundedness of tracking errors in conventional dynamic surface control methods. Furthermore, the expression of the norm of tracking errors is explicitly derived in relation to the controller parameters, which provides instructions on tuning controller parameters to adjust the system performance. Moreover, the passivity structure of the designed adaptation law is thoroughly analyzed. Simulation of a free‐floating space robot is used to verify the effectiveness of the proposed control strategy in comparison with the conventional tracking control schemes. Copyright © 2016 John Wiley & Sons, Ltd.     

基于Webots的蛇形机器人翻滚运动仿真及实现

针对蛇形机器人的侧向翻滚运动,给出一种建立正交关节蛇形机器人三维空间运动模型的方法,提出了一种更为简单的实现蛇形机器人侧向翻滚运动的舵机输入函数.通过选择不同的控制参数,可以实现蛇形机器人"U"字形和"V"字形侧向翻滚运动.在Webots移动机器人仿真软件上进行正交关节蛇形机器人翻滚运动仿真,并在蛇形机器人本体上进行试验,验证了所提控制规律的有效性.     

新型蛇形机器人蜿蜒运动的动力学分析

为提高蛇形机器人执行各种运动的能力,研制了新型蛇形机器人系统．重点研究了该蛇形机器人的动力学．建立了机器人的运动学模型,并根据运动学模型提出了控制蛇形机器人蜿蜒运动的复合运动控制方法．用拉格朗日方法建立动力学模型,对不同参数下蛇形机器人的关节力矩特性和摩擦力特性进行了分析比较,为蛇形机器人的有效运动提供了理论依据．     

Adaptive creeping locomotion of a CPG-controlled snake-like robot to environment change

In this paper, we present a biomimetic approach which is based on Central Pattern Generator (CPG) to solve the difficulty in control of a snake-like robot with a large number of degrees of freedom. A new network with a feedback connection is proposed, which can generate uniform outputs without any additional adjustment. The relations between the CPG parameters and the characteristics of output are also investigated. A simulation platform is also established for the analysis of the CPG-based locomotion control of a snake-like robot. To figure out adaptive creeping locomotion of the robot to the environment with changed friction or the given slope, the relations of CPG parameters and locomotion efficiency by the proposed curvature adaptive principle have been discussed.