Yiu-Kuen Yiu

Bio: Yiu-Kuen Yiu is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Real-time Control System & Parallel manipulator. The author has an hindex of 1, co-authored 1 publications receiving 320 citations.

Dynamics and control of redundantly actuated parallel manipulators

Abstract: It has been shown that redundant actuation provides an effective means for eliminating singularities of a parallel manipulator, thereby improving its performance such as Cartesian stiffness and homogeneous output forces. Based on this concept, several high-performance parallel manipulator prototypes have been designed. A major difficulty that prevents application of the vast control literature developed for the serial counterparts to redundantly actuated parallel manipulators is the lack of an efficient dynamical model for real-time control. In this paper, using the Lagrange-D'Alembert formulation, we propose a simple scheme for computing the inverse dynamics of a redundantly actuated parallel manipulator. Based on this approach, four basic control algorithms, a joint-space proportional derivative (PD) control, a PD control in generalized coordinates, an augmented PD control, and a computed-torque control, are formulated. A two-degrees-of-freedom redundantly acutated parallel manipulator designed for a high-speed assembly task is used to verify the simplicity of the proposed approach and to evaulate the performance of the four control algorithms.

Adaptive Parameter Estimation and Control Design for Robot Manipulators With Finite-Time Convergence

Abstract: For parameter identifications of robot systems, most existing works have focused on the estimation veracity, but few works of literature are concerned with the convergence speed. In this paper, we developed a robot control/identification scheme to identify the unknown robot kinematic and dynamic parameters with enhanced convergence rate. Superior to the traditional methods, the information of parameter estimation error was properly integrated into the proposed identification algorithm, such that enhanced estimation performance was achieved. Besides, the Newton–Euler (NE) method was used to build the robot dynamic model, where a singular value decomposition-based model reduction method was designed to remedy the potential singularity problems of the NE regressor. Moreover, an interval excitation condition was employed to relax the requirement of persistent excitation condition for the kinematic estimation. By using the Lyapunov synthesis, explicit analysis of the convergence rate of the tracking errors and the estimated parameters were performed. Simulation studies were conducted to show the accurate and fast convergence of the proposed finite-time (FT) identification algorithm based on a 7-DOF arm of Baxter robot.

Internal Preload Control of Redundantly Actuated Parallel Manipulators—Its Application to Backlash Avoiding Control

Abstract: Redundant actuation of parallel manipulators can lead to internal forces without generating end-effector forces (preload). Preload can be controlled in order to prevent backlash during the manipulator motion. Such control is based on the inverse dynamics. The general solution of the inverse dynamics of redundantly actuated parallel manipulators is given. For the special case of simple overactuation an explicit solution is derived in terms of a single preload parameter. With this formulation a computational efficient open-loop preload control is developed and applied to the elimination of backlash. Its simplicity makes it applicable in real-time applications. Results are given for a planar 4RRR manipulator and a spatial heptapod.