Experimental validation of model predictive control stability for autonomous driving. (December 2018)

• Record Type: Journal Article
• Authors: Lima, Pedro F.; Collares Pereira, Gonçalo; Mårtensson, Jonas; Wahlberg, Bo
• Is Part Of: Control engineering practice. Volume 81(2018)
• Page Start: 244
• Page End: 255
• Publication Date: 2018-12
• Subjects: Model predictive control -- Stability -- Set invariance -- Autonomous driving -- Automatic control; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2018.09.021
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: This paper addresses the design of time-varying model predictive control of an autonomous vehicle in the presence of input rate constraints such that closed-loop stability is guaranteed. Stability is proved via Lyapunov techniques by adding a terminal state constraint and a terminal cost to the controller formulation. The terminal set is the maximum positive invariant set of a multi-plant description of the vehicle linear time-varying model. The terminal cost is an upper-bound on the infinite cost-to-go incurred by applying a linear–quadratic regulator control law. The proposed control design is experimentally tested and successfully stabilizes an autonomous Scania construction truck in an obstacle avoidance scenario. Graphical abstract: Highlights: Guaranteeing stability is essential for autonomous vehicles. The stability is guaranteed by terminal cost and constraints in the MPC. The stability is further improved by considering the steering rate limitation. Evaluation is performed in an autonomous Scania truck. Experimental tests demonstrate the improved stability of the truck.