Receding horizon tracking control for wheeled mobile robots with time-delay

• Published in: Journal of mechanical science and technology Vol. 22; no. 12; pp. 2403 - 2416
• Main Authors: Gao, Yu, Lee, Chang Goo, Chong, Kil To
• Format: Journal Article
• Language: English
• Published: Seoul Korean Society of Mechanical Engineers 01.12.2008; Springer Nature B.V; 대한기계학회
• Subjects: Applied sciences; Computer science; control theory; systems; Control; Control algorithms; Control system synthesis; Control theory. Systems; Dynamical Systems; Dynamics; Engineering; Exact sciences and technology; Horizon; Industrial and Production Engineering; Mathematical analysis; Mathematical models; Mechanical Engineering; Quadratic programming; Robotics; Robots; Studies; Tracking control; Vibration; 기계공학; Receding horizon control; Trajectory tracking; Wheeled mobile robot; Quadratic programming; Input error; Wheel; Obstacle; Model following; Moving robot; Control program; Control synthesis; Vehicle dynamics; Optimization; Robotics; Model predictive control; Kinematics; Tracking error; Delay time; Quadratic cost; Sampling; Initial value problem; Non holonomic system; Tracking task; Equilibrium point; Vehicle direction; Discrete time; Open ended horizon; Quadratic function
• ISSN: 1738-494X; 1976-3824
• DOI: 10.1007/s12206-008-0746-5

In this paper, a receding horizon (RH) controller is developed for tracking control of wheeled mobile robots (WMRs) subject to nonholonomic constraint in the environments without obstacles. The problem is simplified by neglecting the vehicle dynamics and considering only the steering system. First, the tracking-error kinematic model is linearized at the equilibrium point. And then, it is transferred to an exact discrete form considering the time-delay. The control policy is derived from the optimization of a quadratic cost function, which penalizes the tracking error and control variables in each sampling time. The minimizing problem is solved by using the QP (quadratic programming) method taking the current error state as the initial value and including the velocity constraints. The performance of the control algorithm is verified via the computer simulations with several different predefined trajectories showing that the strategy is feasible.