Distributed formation tracking of nonholonomic autonomous vehicles via event-triggered and sampled-data method

ABSTRACT

This paper addresses the distributed formation tracking control problem for multi-vehicle systems with nonholonomic constraints, by the aid of event-triggered and sampled-data control methods. Two classes of event-triggered communication and control strategies with fixed sampling period are considered. By designing different event conditions, the communications amongst neighbouring vehicles are allowed at each sampling time instant in the first strategy, whereas the control input of each vehicle is updated only when its own or neighbours’ event conditions are violated. Furthermore, both communication and control update are allowed only when the events of itself or neighbours are triggered in another strategy. To this end, an unified event-triggered and distributed observer-based controller with globally asymptotic convergence rate is proposed. And corresponding sufficient conditions are derived regarding to two types of event conditions, based on Lyapunov technique, matrix analysis and algebraic graph theory. It is worth noting that the Zeno-behaviour of systems with the presented controllers and event conditions is naturally avoided for all the vehicles due to the advantageous property of sampled-data control. Finally, simulations are provided to verify the effectiveness of the obtained theoretical results.

KEYWORDS:

• Multi-vehicle systems
• formation tracking
• nonholonomic constraint
• distributed observer
• event-triggered mechanism
• sampled-data control

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Fundamental Research Funds for the Central Universities [grant number YWF-17-ZF-F-07], [grant number YWF-15-SYS-JTXY-007], [grant number YWF-16-BJ-Y-21], [grant number 2017JBM067]; National Natural Science Foundation of China [grant number 61503016, 61403019]; the National Key R&D Program of China [grant number 2017YFB0103202]; China Scholarship Council.