Feedback linearization control of flexible joint robots

In this paper, the control of a two link, flexible joint manipulator is examined. Among external forces, an exogenous constraint force acting on the end-effector is included. The manipulator dynamics are described by:

. On the assumption that f(x), g(x) and J^T f_e(x) are smooth vector fields, it is shown that the inner loop control u is of the form:

u=1/dT_n,g(v−dT_n,(ƒ(x)+J^Tƒ_e(x)))

where u is an outer loop control signal and y = T(x) is a diffleomorphism that transform (a) into linear system. As the position control scheme is adopted, the value of the contact force is not controlled.

The results for the inner loop control are substantiated by simulation of a two-link robot model. The robustness of the control method is examined and a Lyapunov-based control correction, similar to that of the free motion case, is implemented. Results are obtained for parametric errors of up to 50%. In the simulation, the manipulator is required to follow a specified joint trajectory such that the end-effector traces a sinusoidal path along a constraint surface. The results obtained illustrate the tracking of the link reference trajectory and indicate that the inner loop corrections are valid.     

An adaptive control scheme for robot manipulators

An adaptive control scheme is developed for a robot manipulator to track a desired trajectory as closely as possible in spite of a wide range of manipulator motions and parameter uncertainties of links and payload.

The presented control scheme has two components: a nominal control and a variational control. The nominal control, generated from direct calculation of the manipulator dynamics along a desired trajectory, drives the manipulator to a neighbourhood of the trajectory. Then a new adaptive regulation scheme is devised based on the Lyapunov direct method, which generates the variational control that regulates the perturbation in the vicinity of the desired trajectory.     

一类非参数不确定系统的自适应重复学习控制

本文针对一类非参数不确定系统提出一种全限幅自适应重复学习控制方法. 利用期望轨迹的周期特性, 构 造周期性期望控制输入, 并基于Lyapunov方法设计自适应重复学习控制器, 实现系统对周期性期望轨迹的高精度跟 踪, 且无需已知非参数不确定性的上界. 设计全限幅学习律估计未知的期望控制输入, 保证估计值被限制在指定的 界内. 同时, 通过构造完全平方式消除部分误差相关项, 控制器设计中可避免使用符号函数, 从而抑制控制器抖振问 题. 最后, 基于Lyapunov方法对误差收敛性进行了分析, 并通过仿真对比验证本文所提方法的有效性.     

六自由度机械臂约束预测控制系统的设计

本文提出了一种基于约束预测控制的机械臂实时运动控制方法.该控制方法分为两层,分别设计了约束预测控制器和跟踪控制器.其中,约束预测控制器在考虑系统物理约束的条件下,在线为跟踪控制器生成参考轨迹;跟踪控制器采用最优反馈控制律,使机械臂沿参考轨迹运动.为了简化控制器的设计和在线求解,本文采用输入输出线性化的方式简化机械臂动力学模型.同时,为了克服扰动,在约束预测控制器中引入前馈策略,提出了带前馈一反馈控制结构的预测控制设计.因此,本文设计的控制器可以使机械臂在满足物理约束的条件下快速稳定地跟踪到目标位置.通过在PUMA560机理模型上进行仿真实验,验证了预测控制算法的可行性和有效性.     

Hybrid-damped resolved-acceleration control for manipulators

The singularity problem of the resolved-acceleration control scheme can be solved by the damped least-squares method. This approach, however, does suffer from one serious drawback: oscillations of the end-effector when the target is outside the workspace and self-motion of the manipulator when it is at the orientation degeneracy. In this paper, we present a hybrid-damped resolved-acceleration control scheme (HDRAC), which is capable of damping both the accelerations and the velocities to overcome this drawback. The main advantage of the present approach is that the control system need not plan the path to avoid the infeasible region of the manipulator, since the controller will automatically command the end-effector to move along the boundary of the workspace with a minimum trajectory error. Thus this approach renders the resolved-acceleration control scheme a much more practical control for the industry. The stability of the proposed control scheme is also proved in this paper. Incorporated with the concept of the degenerated-direction damped least-squares method (DDDLSM), this new control scheme can also apply only to the degenerated directions, which scheme is simulated on the PUMA 560 manipulator to verify its usefulness. ©1997 John Wiley & Sons, Inc.     

Robust adaptive control of uncertain force/motion constrained nonholonomic mobile manipulators

In this paper, force/motion tracking control is investigated for nonholonomic mobile manipulators with unknown parameters and disturbances under uncertain holonomic constraints. The nonholonomic mobile manipulator is transformed into a reduced chained form, and then, robust adaptive force/motion control with hybrid variable signals is proposed to compensate for parametric uncertainties and suppress bounded disturbances. The control scheme guarantees that the outputs of the dynamic system track some bounded auxiliary signals, which subsequently drive the kinematic system to the desired trajectory/force. Simulation studies on the control of a wheeled mobile manipulator are used to show the effectiveness of the proposed scheme.     

Backstepping control of flexible joint manipulator based on hyperbolic tangent function with control input and rate constraints

In this paper, we investigate the trajectory tracking problems of the link angle and angle speed of the flexible joint manipulator model based on external disturbance, the control input and rate constraints. The controller of the flexible joint manipulator model is designed using the backstepping control scheme. To achieve this objective, the smooth hyperbolic tangent function is used to solve the problems of control input and rate constraints, and the stability is proved using Lyapunov function in the design procedure of the backstepping control scheme. Finally, the effectiveness of the proposed backstepping controller is verified by numerical simulation.     

Discrete-time adaptive control for mechanical manipulators having a joint compliance

This paper presents the application of a discrete-time adaptive control scheme to mechanical manipulators having a joint compliance. A control model of such manipulators is derived by linearizing the nonlinear equations about a desired trajectory. This control model is described by multivariable difference equations. The parameters of the model are estimated by parameter adaptation algorithms. Control gains, determined from the control model by using the pole placement technique, are computed on-line with the estimates of the system parameters. Simulation results with a two-link mechanical manipulator are presented to show the effectiveness of the proposed approach.     

参数不确定空间机械臂系统的鲁棒自适应混合控制

讨论了载体位置与姿态均不受控制的漂浮基空间机械臂系统的控制问题.对系统运动学、动力学的分析结果表明,结合系统动量守恒及动量矩守恒关系得到的系统广义Jacobi关系以及系统的动力学方程是系统惯性参数的非线性函数.证明了借助于增广变量法可以将系统的增广广义Jacobi矩阵及系统动力学方程表示为一组适当选择的(组合)惯性参数的线性函数.以此为基础,针对系统惯性参数不确定的情况,设计了空间机械臂末端抓手跟踪惯性空间期望轨迹的鲁棒自适应混合控制方案.仿真运算结果证实了方法的有效性.     

Path-constrained control of a redundant manipulator in a task space

This study addresses the problem of controlling a redundant manipulator with both state and control dependent constraints. The task of the robot is to follow by the end-effector a prescribed geometric path given in the task space. The control constraints resulting from the physical abilities of robot actuators are also taken into account during the robot movement. Provided that a solution to the aforementioned robot task exists, the Lyapunov stability theory is used to derive the control scheme. The numerical simulation results, carried out for a planar manipulator whose end-effector follows a prescribed geometric path given in a task space, illustrate the trajectory performance of the proposed control scheme.     

Decentralized adaptive control scheme for control of a multi-arm-type robot

This paper deals with the problem of decentralized stabilization for a class of unknown large-scale dynamic systems formed of interconnected subsystems under constant disturbances. A decentralized adaptive control scheme is proposed based on the Lyapunov direct method and a condition of asymptotic stability is derived. Then the decentralized adaptive control scheme is applied for a class of robot manipulators to track the desired trajectory as closely as possible despite a wide range of manipulator motions and parameter uncertainties of links and payload.     

Vibration control for a nonlinear three-dimensional flexible manipulator trajectory tracking

This paper proposes an innovative approach to the trajectory tracking in three-dimensional space and vibration control problems in the presence of a nonlinear three-dimensional flexible manipulator based on the partial differential equation model. Unlike two-dimensional plane, we select spherical coordinates to describe the position of the end point in three-dimensional space. This novel approach makes it possible to realise the trajectory tracking by controlling the two angles in spherical coordinates, meanwhile, a vibration control scheme is proposed to restrain vibrations. In addition, the existence and uniqueness of solutions are demonstrated. Finally, the performance of the desired trajectory tracking, the proposed vibration control scheme and their convergence properties are demonstrated by numerical simulations.     

Repetitive control of electrically driven robot manipulators

This article presents a novel robust discrete repetitive control of electrically driven robot manipulators for tracking of a periodic trajectory. We propose a novel model, which presents the highly non-linear dynamics of robot manipulator in the form of linear discrete-time time-varying system. Based on the proposed model, we develop a two-term control law. The first term is an ordinary time-optimal and minimum-norm (TOMN) control by employing parametric controllers to guarantee stability. The second term is a novel robust control to improve the control performance in the face of uncertainties. The robust control estimates and compensates uncertainties including the parametric uncertainty, unmodelled dynamics and external disturbances. Performance of the proposed method is compared with two discrete methods, namely the TOMN control and an adaptive iterative learning (AIL) control. Simulation results confirm superiority of the proposed method in terms of the convergence speed and precision.     

Adaptive stabilization and tracking control of electrically driven manipulators

This article presents two new adaptive strategies for motion control of uncertain rigid-link, electrically driven manipulators. The first controller is a position regulation scheme that ensures (semiglobal) asymptotic convergence of the position error if no external disturbances are present, and convergence to an arbitrarily small neighborhood of zero in the presence of bounded disturbances. It is shown that the regulation scheme can be modified to provide accurate trajectory tracking control through the introduction of adaptive feedforward elements in the control law; this second control strategy retains the simple structure of the first controller and ensures arbitrarily accurate tracking in the presence of bounded disturbances. Each of the adaptive schemes is computationally efficient and requires virtually no information concerning either the manipulator or actuator models. Computer simulation results are given for a PUMA 560 manipulator and demonstrate that accurate and robust motion control can be achieved by using the proposed controllers. Experimental results are presented for an IMI Zebra Zero manipulator and confirm that the proposed approach provides a simple and effective means of obtaining high performance motion control. © 1996 John Wiley & Sons, Inc.     

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.     

Adaptive tracking control of rigid manipulators using only position measurements

This article presents a new approach to trajectory tracking control of uncertain rigid manipulators using only position measurements. The proposed control strategy is an adaptive scheme that is very general and computationally efficient, requires virtually no information regarding the manipulator dynamic model, and is implementable without calculation of the robot inverse dynamics or inverse kinematic transformations. It is shown that the controller ensures semiglobal uniform boundedness of all signals in the presence of bounded disturbances, and that the ultimate size of the tracking errors can be made arbitrarily small. Additionally, it is demonstrated that the proposed strategy can be used as the basis for developing controllers for “cascaded” robotic systems, such as manipulators with significant actuator dynamics or joint flexibility. The efficacy of this approach to manipulator control is illustrated through both computer simulations and hardware experiments. © 1997 John Wiley & Sons, Inc.     

Analysis and Verification of Repetitive Motion Planning and Feedback Control for Omnidirectional Mobile Manipulator Robotic Systems

Mobile manipulator robotic systems (MMRSs) composed of a manipulator and a mobile platform are investigated in this paper. In order for the mobile manipulator robotic system (MMRS) to return to its initial state when the manipulator’s end-effector is requested to execute cyclical tasks, a quadratic program (QP) based repetitive motion planning and feedback control (RMPFC) scheme is proposed and analyzed. Such an RMPFC scheme can not only mix motion planning and reactive control, but also consider the physical limits of the robotic system. Mathematically, the efficacy of the RMPFC scheme is verified via gradient dynamics analysis. To further demonstrate the effectiveness of the RMPFC scheme, a kinematically redundant MMRS composed of a three degrees-of-freedom (DOF) planar manipulator and an omnidirectional mobile platform is designed, modeled and analyzed. Then, repetitive motion planning and feedback control for the designed omnidirectional MMRS is studied. Besides, a numerical algorithm is developed and presented to solve the QP and resolve the redundancy of the robotic system. Moreover, computer simulations are comparatively performed on such an omnidirectional MMRS, and simulation results substantiate the effectiveness, accuracy and superiority of the proposed RMPFC scheme.     

Adaptive neural control for an uncertain robotic manipulator with joint space constraints

In this paper, adaptive neural tracking control is proposed for a robotic manipulator with uncertainties in both manipulator dynamics and joint actuator dynamics. The manipulator joints are subject to inequality constraints, i.e., the joint angles are required to remain in some compact sets. Integral barrier Lyapunov functionals (iBLFs) are employed to address the joint space constraints directly without performing an additional mapping to the error space. Neural networks (NNs) are utilised to compensate for the unknown robot dynamics and external force. Adapting parameters are developed to estimate the unknown bounds on NN approximations. By the Lyapunov synthesis, the proposed control can guarantee the semi-global uniform ultimate boundedness of the closed-loop system, and the practical tracking of joint reference trajectory is achieved without the violation of predefined joint space constraints. Simulation results are given to validate the effectiveness of the proposed control scheme.     

Iterative learning control: A survey and new results

Learning control is an iterative approach to the problem of improving transient behavior for processes that are repetitive in nature. In this article, we present some results on iterative learning control. A complete review of the literature is given first. Then, a general formulation of the problem is given. Next, we present a complete analysis of the learning control problem for the case of linear, time-invariant plants and controllers. This analysis offers: (1) insight into the nature of the solution of the learning control problem by deriving sufficient convergence conditions; (2) an approach to learning control for linear systems based on parameter estimation; and (3) an analysis that shows that for finite-horizon problems it is possible to design a learning control algorithm that converges, with memory, in one step. Finally, a time-varying learning controller is given for controlling the trajectory of a nonlinear robot manipulator. A brief simulation example is presented to illustrate the effectiveness of this scheme.     

Compound control of a compound cosine function neural network and PD for manipulators

In this paper, a compound cosine function neural network controller for manipulators is presented based on the combination of a cosine function and a unipolar sigmoid function. The compound control scheme based on a proportional-differential (PD) feedback control plus the cosine function neural network feedforward control is used for the tracking control of manipulators. The advantages of the compound control are that the system model does not need to be identified beforehand in the manipulator control system and it can achieve better adaptive control in an on-line continuous learning manner. The simulation results for the two-link manipulator show that the proposed compound control has higher tracking accuracy and better robustness than the conventional PD controllers in the position trajectory tracking control for the manipulator. Therefore, the compound cosine function neural network controller provides a novel approach for the manipulator control with uncertain nonlinear problems.