Adaptive compliant force–motion control of coordinated non-holonomic mobile manipulators interacting with unknown non-rigid environments

Most studies on the coordination control of multiple mobile manipulators system assume exact knowledge of system dynamics and deal only with motion control. However, actual applications may involve the tasks in which multiple coordinated mobile manipulators system interacts with rigid or non-rigid working surfaces. In this paper, we consider multiple mobile manipulators grasping a rigid object in contact with a deformable working surface, whose geometric and real physical parameters are unknown but boundedness of physical parameters is known. The contact forces are nonlinear and difficult to model. A neuro-adaptive control for coordinated mobile manipulators is proposed for robust force/motion tracking. The control law is based on the philosophy of the parallel approach, in which the control problem is divided into three subspaces and the adaptive techniques are employed to deal with the uncertain environmental constraints, disturbances, and unknown robotic and object dynamics. The proposed adaptive force–motion controller guarantees the tracking errors of motion and force trajectories converge to zero. Simulation examples are presented to verify the effectiveness of the proposed control.     

Adaptive-backstepping force/motion control for mobile-manipulator robot based on fuzzy CMAC neural networks

In this paper, an adaptive backstepping fuzzy cerebellar-model-articulation-control neural-networks control （ABFCNC） system for motion/force control of the mobile-manipulator robot （MMR） is proposed. By applying the ABFCNC in the tracking-position controller, the unknown dynamics and parameter variation problems of the MMR control system are relaxed. In addition, an adaptive robust compensator is proposed to eliminate uncertainties that consist of approximation errors, uncertain disturbances. Based on the tracking position-ABFCNC design, an adaptive robust control strategy is also developed for the nonholonomicconstraint force of the MMR. The design of adaptive-online learning algorithms is obtained by using the Lyapunov stability theorem. Therefore, the proposed method proves that it not only can guarantee the stability and robustness but also the tracking performances of the MMR control system. The effectiveness and robustness of the proposed control system are verified by comparative simulation results.     

Motion/force control scheme for electrically driven cooperative multiple mobile manipulators

This paper presents the motion and force control problem of rigid-link electrically driven cooperative mobile manipulators handling a rigid object. Although, the motion/force control problem of cooperative mobile manipulators has been enthusiastically studied. But there is little research on the motion/force control of electrically driven cooperative mobile manipulators. Due to the inclusion of the actuator dynamics with the manipulator’s dynamics, the controller exhibits some important characteristics. For the electromechanical system, we have designed a novel controller at the dynamic level as well as at the actuator level. In the proposed control scheme, at the dynamic level, uncertain non-linear mechanical dynamics is approximated with a hybrid controller containing model-based control scheme combined with model-free neural network based control scheme together with an adaptive bound. The adaptive bound is used to suppress the effects of external disturbances, friction terms, and reconstruction error of the neural network. At the actuator level, for the approximation of the unknown electrical dynamics, the model-free neural network is utilized. The developed control scheme provides that the position tracking errors, as well as the internal force, converge to the desired levels. Additionally, direct current motors are also controlled in such a way that the desired currents and torques can be attained. In order to make the overall system to be asymptotically stable, online learning of the weights and the parameter adaptation of the parameters is utilized in the Lyapunov function. The superiority of the developed control method is carried out with the numerical simulation results and its superior robustness is shown in a comparative manner.     

Robust Adaptive Backstepping Motion Control of Linear Ultrasonic Motors Using Fuzzy Neural Network

A robust adaptive fuzzy neural network (RAFNN) backstepping control system is proposed to control the position of an X-Y-Theta motion control stage using linear ultrasonic motors (LUSMs) to track various contours in this study. First, an X-Y-Theta motion control stage is introduced. Then, the single-axis dynamics of LUSM mechanism with the introduction of a lumped uncertainty, which includes cross-coupled interference and friction force, is derived. Moreover, a conventional backstepping approach is proposed to compensate the uncertainties occurred in the motion control system. Furthermore, to improve the control performance in the tracking of the reference contours, an RAFNN backstepping control system is proposed to remove the chattering phenomena caused by the sign function in the backstepping control law. In the proposed RAFNN backstepping control system, a Sugeno-type adaptive fuzzy neural network (SAFNN) is employed to estimate the lumped uncertainty directly and a compensator is utilized to confront the reconstructed error of the SAFNN. In addition, the motions at the X axis, Y axis, and Theta axis are controlled separately. The experimental results show that the contour tracking performance is significantly improved and the robustness to parameter variations, external disturbances, cross-coupled interference, and friction force can be obtained, as well using the proposed RAFNN backstepping control system.     

Robust adaptive motion/force control for wheeled inverted pendulums

Previous works for wheeled inverted pendulums usually eliminate nonholonomic constraint force in order to make the control design easier, under the assumption that the friction force from the ground is as large as needed. Nevertheless, such an assumption is unfeasible in practical applications. In this paper, adaptive robust motion/force control for wheeled inverted pendulums is investigated with parametric and functional uncertainties. The proposed robust adaptive controls based on physical properties of wheeled inverted pendulums make use of online adaptation mechanism to cancel the unmodelled dynamics. Based on Lyapunov synthesis, the proposed controls ensure that the system outputs track the given bounded reference signals within a small neighborhood of zero, and guarantee the semi-global uniform boundedness of all closed loop signals. The effectiveness of the proposed controls is verified through extensive simulations.     

Stability guaranteed teleoperation: an adaptive motion/force control approach

An adaptive motion/force controller is developed for unilateral or bilateral teleoperation systems. The method can be applied in both position and rate control modes, with arbitrary motion or force scaling. No acceleration measurements are required. Nonlinear rigid-body dynamics of the master and the slave robots are considered. A model of the flexible or rigid environment is incorporated into the dynamics of the slave, while a model of the human operator is incorporated into the dynamics of the master. The master and the slave are subject to independent adaptive motion/force controllers that assume parameter uncertainty bounds. Each parameter is independently updated within its known lower and upper bounds. The states of the master (slave) are sent to the slave (master) as motion/force tracking commands instead of control actions (efforts and/or flows). Under the modeling assumptions for the human operator and the environment, the proposed teleoperation control scheme is L/sub 2/ and L/sub /spl infin// stable in both free motion and flexible or rigid contact motion and is robust against time delays. The controlled master-slave system behaves essentially as a linearly damped free-floating mass. If the parameter estimates converge, the environment impedance and the impedance transmitted to the master differ only by a control-parameter dependent mass/damper term. Asymptotic motion (velocity/position) tracking and force tracking with zero steady-state error are achieved. Experimental results are presented in support of the analysis.     

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.     

Robust Adaptive Control of Cooperating Mobile Manipulators With Relative Motion

In this paper, coupled dynamics are presented for two cooperating mobile robotic manipulators manipulating an object with relative motion in the presence of uncertainties and external disturbances. Centralized robust adaptive controls are introduced to guarantee the motion, and force trajectories of the constrained object converge to the desired manifolds with prescribed performance. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The tracking of the constraint trajectory/force up to an ultimately bounded error is achieved. The proposed adaptive controls are robust against relative motion disturbances and parametric uncertainties and are validated by simulation studies.     

Adaptive neural network control of bilateral teleoperation with unsymmetrical stochastic delays and unmodeled dynamics

In this paper, adaptive NN control is proposed for bilateral teleoperation system with dynamic uncertainties, unknown external disturbances, and unsymmetrical stochastic delays in communication channel to achieve transparency and robust stability. Compared with previous passivity‐based teleoperation framework, the communication delays are unsymmetrical and stochastic. By partial feedback linearization using nominal dynamics, the nonlinear dynamics of the teleoperation system are transformed into two subsystems: local master/slave dynamics control and time‐delay motion tracking. By integrating Markov jump systems and adaptive parameters updating, adaptive NN control strategy is developed. The stability of the closed‐loop system and the boundedness of tracking errors are proved using Lyapunov–Krasovskii functional synthesis under specific linear matrix inequalities conditions. The proposed adaptive NN control is robust against motion disturbances, parametric uncertainties, and unsymmetrical stochastic delay, which effectiveness is validated by extensive simulation studies. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive robust motion/force control of holonomic-constrained nonholonomic mobile manipulators.

In this paper, adaptive robust force/motion control strategies are presented for mobile manipulators under both holonomic and nonholonomic constraints in the presence of uncertainties and disturbances. The proposed control is robust not only to parameter uncertainties such as mass variations but also to external ones such as disturbances. The stability of the closed-loop system and the boundedness of tracking errors are proved using Lyapunov stability synthesis. The proposed control strategies guarantee that the system motion converges to the desired manifold with prescribed performance and the bounded constraint force. Simulation results validate that the motion of the system converges to the desired trajectory, and the constraint force converges to the desired force.     

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.     

Dynamics and control of a novel 3-DOF parallel manipulator with actuation redundancy

This paper deals with the dynamics and control of a novel 3-degrees-of-freedom （DOF） parallel manipulator with actuation redundancy. According to the kinematics of the redundant manipulator, the inverse dynamic equation is formulated in the task space by using the Lagrangian formalism, and the driving force is optimized by utilizing the minimal 2-norm method. Based on the dynamic model, a synchronized sliding mode control scheme based on contour error is proposed to implement accurate motion tracking control. Additionally, an adaptive method is introduced to approximate the lumped uncertainty of the system and provide a chattering-free control. The simulation results indicate the effectiveness of the proposed approaches and demonstrate the satisfactory tracking performance compared to the conventional controller in the presence of the parameter uncertainties and un-modelled dynamics for the motion control of manipulators.     

Motion Control of Passive Intelligent Walker Using Servo Brakes

We propose a new intelligent walker based on passive robotics that assists the elderly, handicapped people, and the blind who have difficulty in walking. We developed a prototype of the robot technology walker (RT walker), a passive intelligent walker that uses servo brakes. The RT walker consists of a support frame, two casters, two wheels equipped with servo brakes, and it has passive dynamics that change with respect to applied force/moment. This system is intrinsically safe for humans, as it cannot move unintentionally, i.e., it has no driving actuators. In addition, the RT walker provides a number of navigational features, including good maneuverability, by appropriately controlling the torque of servo brakes based on RT. We propose a human adaptive motion control algorithm that changes the apparent dynamics to adapt to user difficulties, and an environmentally adaptive motion control algorithm, which incorporates environmental information to provide obstacle/step avoidance and gravity compensation functions. The proposed control algorithms are experimentally applied to the RT walker to test their validity.     

时滞柔性关节机械臂自适应位置/力控制

针对具有时滞的柔性关节机械臂自适应位置和力控制问题进行了研究.首先,通过坐标变换得出降维的位置/力控制模型.随后,将时间滞后近似表示成一阶滞后,进行时滞补偿.利用自适应算法修正机械臂系统参数,克服模型参数不确定性对系统的影响.同时,采用反步控制技术设计机械臂位置/力控制器,运用Lyapunov稳定性定理证明控制器能使机械臂位置和力跟踪误差收敛.最后的仿真研究验证了控制方案的有效性.     

Adaptive feedforward compensation of force ripples in linear motors

In this paper, an adaptive control scheme is proposed to reduce force ripple effects impeding motion accuracy in Permanent Magnet Linear Motors (PMLMs). The displacement periodicity of the force ripple is first obtained by using a Fast Fourier Transform (FFT) analysis. The control method is based on recursive least squares (RLS) identification of a nonlinear PMLM model which includes a model of the force ripple. Based on this model, the control algorithm can be commissioned which consists of a PID feedback control component, an adaptive feedforward component for compensation of the force ripple and another adaptive feedforward component based on the inverse dominant linear model which will serve to expedite motion tracking response. Simulation and experimental results are presented to verify the effectiveness of the proposed control scheme for high precision motion tracking applications.     

Robust adaptive quasi-sliding mode controller for discrete-time systems

In this paper, a discrete robust quasi-sliding mode adaptive controller is presented for the system with model uncertainties, unmodeled dynamics and bounded disturbances. The proposed method is adaptive control in conjunction with a sliding mode based controller design. The bounded motion of the state around the sliding surface and the stability of the global system in the sense that all signals remain bounded are guaranteed. In the proposed adaptive algorithms, the dead-zone method is employed even though the upper and lower bounds of the disturbances are unknown. Simulation results have shown the effectiveness of the proposed algorithms.     

Motion and force control with a nonlinear force error filter for underwater vehicle-manipulator systems

This paper deals with a control scheme for autonomous underwater robots equipped with manipulators. Several motion and force controllers have been developed. Most of them were designed in disregard of the dynamics of marine thrusters to develop a controller with a simple structure. However, the robot body propelled by thrusters generally has a considerably slower time response than the manipulator driven by electrical motors. Therefore, it may be difficult to construct a high-gain feedback control system to achieve a good control performance, because the high gain may excite the slow thruster dynamics ignored in the controller design, and the excitation will degrade the control performance. In this paper, we develop a motion and force controller for mathematical models with the dynamics of thrusters. It includes a nonlinear force error filter which allows us to construct a stable motion and force control system. To investigate its control performance, we conducted numerical simulations for comparing the proposed control scheme with an existing control scheme designed in disregard of the thruster dynamics. Simulation results demonstrate the usefulness of the proposed controller.     

Adaptive Force-Motion Control of Coordinated Robots Interacting With Geometrically Unknown Environments

Most studies on adaptive coordination of multi-robot systems assume exact knowledge of system kinematics and deal only with dynamic uncertainties. However, many industrial applications involve tasks in which a multi-robot system interacts with geometrically unknown environments. In this paper, we consider a multi-robot system grasping a rigid object in contact with a geometrically unknown surface. The proposed adaptive hybrid force-motion controller guarantees asymptotic tracking of desired motion and force trajectories while ensuring exact identification of constraint Jacobian matrix without persistency of excitation condition. The control signal is smooth and does not depend on contact force derivative. The proposed adaptive controller is robustified against environmental friction and nonparametric uncertainty in environment geometry. Simulation examples are presented to illustrate the results.     

空间机械臂本体与末端抓手协调运动的自适应控制方法

讨论了载体位置不受控制的漂浮基空间机械臂本体与末端抓手协调运动的自适应控制问题. 对系统的运动学、动力学分析表明, 结合系统动量守恒关系得到的系统动力学方程及协调运动的增广广义Jacobi矩阵可以表示为适当选择的组合惯性参数的线性函数. 以此为基础, 对于系统存在未知参数的情况, 设计了本体姿态与机械臂末端抓手惯性空间轨迹协调运动的自适应控制方案. 上述控制方案的显著优点在于: 不需要测量、反馈飞行器本体的位置、移动速度及移动加速度. 仿真运算, 证实了上述控制方案的有效性.     

Robust adaptive boundary control of a perturbed hybrid Euler-Bernoulli beam with coupled rigid and flexible motion

In this paper, a robust adaptive boundary controller is proposed to stabilize the coupled rigid-flexible motion of an Euler-Bernoulli beam in presence of boundary and distributed perturbations. Applying Hamilton’s principle, the dynamics of the hybrid beam model, including the actuators hub and the payload at its ends, is represented through four nonhomogeneous nonlinear partial differential equations (PDEs) subject to ordinary differential equations (ODEs) of boundary conditions. Using a Lyapunov-based control synthesis procedure, a robust nonlinear boundary controller is established that asymptotically stabilizes the perturbed beam vibration while regulating the rigid motion coordinates. A redesign of the proposed control laws produces a robust adaptive boundary controller that achieves control objectives in the presence of both parametric and modelling uncertainties. Control design is directly based on system PDEs without truncating the model so that instabilities from spillover effects are mitigated. The control inputs to the beam consist of three forces/torque applied to the actuators hub and a transverse force applied to the tip payload. Simulation results are used to investigate the efficiency of the proposed approach.