LPV modelling and control of a 2-DOF robotic manipulator using PCA-based parameter set mapping
Proceedings of the 48th IEEE Conference on Decision and Control, 2009 : held jointly with the 2009 28th Chinese Control Conference ; CDC/CCC 2009 ; 15 - 18 Dec. 2009, Shanghai, China. - Piscataway, NJ, 2009. - Art. no. 5400621 7418-7423 (2009)
Contribution to Conference
This paper presents the construction of a realistic linear parameter-varying (LPV) model of a robotic manipulator using parameter set mapping, for the purpose of synthesizing an LPV gain-scheduled controller. A nonlinear dynamic model of the manipulator is obtained and a quasi-LPV model is derived. Since the quasi-LPV model has a large number of affine scheduling parameters and a large overbounding, parameter set mapping is used to reduce conservatism and complexity in controller design by finding tighter parameter regions with fewer scheduling parameters. Then, a polytopic LPV gain-scheduled controller is synthesized and implemented experimentally on an industrial robot for a trajectory tracking task. Comparison of results with a decentralized PD controller illustrates that the designed LPV controller improves the tracking error significantly. Moreover, it achieves a slightly better accuracy than a model-based inverse dynamics controller while being of lower complexity. ©2009 IEEE.