Controlling a multi-joint arm actuated by pneumatic muscles with quasi-DDP optimal control

G. Kumar Hari Shankar Lal Das, B. Tondu, O. Stasse, P. Soueres,
IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2016, HAL Publisher Bib

Abstract:

Pneumatic actuators have inherent compliance and hence they are very interesting for applications involving inter-action with environment or human. But controlling such kind of actuators is not trivial. The paper presents an implementation of iterative Linear Quadratic regulator (iLQR) based optimal control framework to control an anthropomorphic arm with each joint actuated by an agonist-antagonistic pair of Mc Kibben artificial muscles. The method is applied to positioning tasks and generation of explosive movements by maximizing the linkspeed. It is then compared to traditional control strategies to justify that optimal control is effective in controlling the position in highly non-linear pneumatic systems. Also the importance of varying compliance is highlighted by repeating the tasks atdifferent compliance level. The algorithm validation is reported here by several simulations and hardware experiments in which the shoulder and elbow flexion are controlled simultaneously.