Weiwei Shang

Active Joint Synchronization Control for a 2-DOF Redundantly Actuated Parallel Manipulator

This brief applies the synchronization to solve control problem of redundantly actuated parallel manipulators. With the synchronization method, a new controller termed active joint-synchronization (AJ-S) controller is developed for a 2-degree-of-freedom (DOF) redundantly actuated parallel manipulator. The dynamic model of the parallel manipulator is formulated in the active joint space, in which the internal force is calculated by the projection method and the friction is depicted with the Coulomb + viscous friction model. By defining the tracking error, synchronization error, coupled error, and the referenced trajectory vector of the active joints, the AJ-S controller based on the dynamic model is designed. And the AJ-S controller is proven to guarantee asymptotic convergence to zero of both tracking and synchronization errors by the Barbalats lemma. The AJ-S controller is implemented in the trajectory tracking experiments of an actual 2-DOF redundantly actuated parallel manipulator, and the superiority of the AJ-S controller over the well-known tracking controller is studied.

Coordination Motion Control in the Task Space for Parallel Manipulators With Actuation Redundancy

This paper presents a task space coordination controller for the parallel manipulators with actuation redundancy to improve the motion relation between multiple kinematic chains. According to the mechanism characteristic of multiple kinematic chains, two different types of synchronization error are developed in the joint space of active joints and in the task space of end-effector, respectively. The coordination controller is designed by using the synchronization error, and it is proved to guarantee asymptotic convergence to zero of both tracking error and synchronization error with the Barbalats Lemma. The trajectory tracking experiments are carried out on an actual parallel manipulator with actuation redundancy, and the superiority of the coordination controller over the traditional augmented PD (APD) controller is studied.

Adaptive computed torque control for a parallel manipulator with redundant actuation

An adaptive computed torque (ACT) controller in the task space is proposed for the trajectory tracking of a parallel manipulator with redundant actuation. The dynamic model, including the active joint friction, is established in the task space for the parallel manipulator, and the linear parameterization expression with respect to the dynamic and friction parameters is formulated. On the basis of the dynamic model, a new control law, which contains adaptive dynamics compensation, friction compensation, and tracking error elimination terms, is designed. After defining the state-space model of the error system, the parameter adaptation law is derived by using the Lyapunov method, and the convergence of the tracking error and the error rate is proved by using the Barbalats lemma. The ACT controller is implemented in the trajectory tracking experiments of an actual 2-DOF parallel manipulator with redundant actuation, and the experiment results are compared with the computed torque controller.

Motion Control of Parallel Manipulators Using Acceleration Feedback

Acceleration feedback (AF) is applied to restrain the trajectory disturbances in the motion control of parallel manipulators to increase the trajectory tracking accuracy. A dynamic model is formulated in the task space, and the optimal exciting trajectory is calculated for dynamic identification. The acceleration signals can be estimated without acceleration sensors on the basis of the closed-loop constraint equations. Furthermore, the dynamic acceleration feedback (DAF) controller is developed by introducing the AF into the robust dynamics compensation and trajectory tracking, and the stability of the closed-loop system is proven. The DAF controller is implemented on a planar parallel manipulator platform, and the corresponding experimental results are compared with an existing, robust controller.

Augmented Nonlinear PD Controller for a Redundantly Actuated Parallel Manipulator

In order to improve trajectory tracking accuracy for a redundantly actuated parallel manipulator, a so-called augmented nonlinear PD (ANPD) controller based on the conventional dynamic controller is proposed in this paper. The ANPD controller is designed by replacing the linear PD in the augmented PD controller with a nonlinear PD algorithm. The stability of the parallel manipulator system with the proposed ANPD controller is proven using the Lyapunov stability theorem, and the ANPD controller is further proven to guarantee asymptotic convergence to zero of both the tracking error and error rate. The superiority of the ANPD controller is verified through trajectory tracking experiments of an actual 2-d.o.f. redundantly actuated parallel manipulator.

A new computation method for the force-closure workspace of cable-driven parallel manipulators

For cable-driven parallel manipulators (CDPMs), it is known that maintaining positive cable tension is critical in constraining the moving platform. Hence, the force-closure workspace of CDPMs represents a set of poses where the cable tensions can balance arbitrary external wrench applied on the moving platform, proposed by researchers. A new computation method for the force-closure workspace of CDPMs is developed in this paper, and the new method is realized by calculating the null space of the structure matrix and solving the linear matrix inequalities. The detailed calculation procedures of the force-closure workspace for the incompletely restrained, completely restrained, and redundantly restrained CDPMs are given, respectively, and the advantages of the new method are analyzed according to the time complexity. The simulation experiments of the force-closure workspace computation are implemented on a six-degree of freedom (6-DOF) CDPM with eight cables, and then the superiority of the new method over the existing algorithm is studied.

Design of the simulation platform for networked control systems based on DTHMM

In order to achieve the application of discrete-time hidden Markov model (DTHMM) in modeling and controlling the networked control system (NCS) with the network-induced delays in the forward channel, a simulation platform was designed and implemented in this paper by using TrueTime 1.5, which is a Matlab/Simulink-based simulator. There were one network module and four kernel modules (sensor, controller, actuator and interference nodes) on this simulation platform, and the composition and the main Matlab codes of each module were presented. On the simulation platform designed, the Expectation Maximization (EM) algorithm was achieved to derive the parameters of the DTHMM and the Viterbi algorithm was achieved to predict the controller-to-actuator delay (C-A delay) in the current sampling period. Based on the derived DTHMM and the predicted delays, a state-feedback controller to stabilize the NCS was also implemented on the simulation platform and used to solve the linear matrix inequalities. Taking a damped compound pendulum as the plant in the NCS, after 500 sampling periods the effectiveness of the modeling and controlling methods was carried out, and demonstrated the efficiency and easy operation of the simulation platform.

Self-calibration for kinematic parameters of a redundant planar two-degree-of-freedom parallel manipulator using evolutionary algorithms

In this article, the self-calibration problem of a planar two-degree-of-freedom (2-DoF) parallel manipulator with a redundant joint sensor is studied. By eliminating the passive joint positions, a new error function is proposed. Furthermore, by decoupling the kinematic parameters of the error function, the minimization process is simplified. In order to obtain the global optimum, three evolutionary algorithms including genetic algorithm, particle swarm optimization, and differential evolution are applied to minimize the error function. In the application, the performances and effectiveness of the applied algorithms on this specific problem are compared under three different error functions, and the results show that the differential-evolution method under the decoupled error function produces the best result. Finally, actual calibration is carried out based on differential evolution under the decoupled error function, and the result demonstrates that all of the 12 parameters of the manipulator are calibrated with high accuracy.

Continuous path planning and implementation in internet- based robot arm system

Continuous path (CP) control was researched on an Internet-based two degrees-of-freedom robot arm in this paper. First, the condition needed to realize the continuous path control was analyzed. The important parameter “the highest resultant speed” was calculated considering the existence of network-delay. Then the relation between the linear interpolation numbers and errors of the four-leaf rose curve was derived. The remote control experiment in the actual robot arm system was carried out, and the effects of the interpolation point number to control precision and drawing time were also discussed. At last, a constant compensation method was applied to eliminate the mechanical effects existed in the system and improve the precision of the path-tracking further.

Integrated Kinematic Calibration for All the Parameters of a Planar 2DOF Redundantly Actuated Parallel Manipulator

In this paper, the kinematic calibration of a planar two-degree-of-freedom redundantly actuated parallel manipulator is studied without any assumption on parameters. A cost function based on closed-loop constraint equations is first formulated. Using plane geometry theory, we analyze the pose transformations that bring infinite solutions and present a kinematic calibration integrated of closed-loop and open-loop methods. In the integrated method, the closed-loop calibration solves all the solutions that fit the constraint equations, and the open-loop calibration guarantees the uniqueness of the solution. In the experiments, differential evolution is applied to compute the solution set, for its advantages in computing multi-optima. Experimental results show that all the parameters involved are calibrated with high accuracy.