Optimized adaptive tracking control for an underactuated vibro-driven capsule system

Liu, Pengcheng; Yu, Hongnian; Cang, Shuang

Abstract

This paper studies the issue of adaptive trajectory tracking control for an underactuated vibro-driven capsule system and presents a novel motion generation framework. In this framework, feasible motion trajectory is derived through investigating dynamic constraints and kernel control indexes that underlie the underactuated dynamics. Due to the underactuated nature of the capsule system, the global motion dynamics cannot be directly controlled. The main objective of optimization is to indirectly control the friction-induced stick–slip motions to reshape the passive dynamics and, by doing so, to obtain optimal system performance in terms of average speed and energy efficacy. Two tracking control schemes are designed using a closed-loop feedback linearization approach and an adaptive variable structure control method with an auxiliary control variable, respectively. The reference model is accurately matched in a finite-time horizon. The key point is to define an exogenous state variable whose dynamics is employed as a control input. The tracking performance and system stability are investigated through rigorous theoretic analysis. Extensive simulation studies are conducted to demonstrate the effectiveness and feasibility of the developed trajectory model and optimized adaptive control system.

Citation

Liu, P., Yu, H., & Cang, S. (2018). Optimized adaptive tracking control for an underactuated vibro-driven capsule system. Nonlinear Dynamics, 94(3), 1803-1817. https://doi.org/10.1007/s11071-018-4458-9

• Journal Article Type: Article
• Acceptance Date: Jun 28, 2018
• Online Publication Date: Jul 7, 2018
• Publication Date: 2018-11
• Deposit Date: Mar 9, 2020
• Publicly Available Date: Mar 9, 2020
• Journal: Nonlinear Dynamics
• Print ISSN: 0924-090X
• Electronic ISSN: 1573-269X
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 94
• Issue: 3
• Pages: 1803-1817
• DOI: https://doi.org/10.1007/s11071-018-4458-9
• Keywords: Control and Systems Engineering; Mechanical Engineering; Electrical and Electronic Engineering; Applied Mathematics; Ocean Engineering; Aerospace Engineering
• Public URL: http://researchrepository.napier.ac.uk/Output/2615086