Robust adaptive control

A function approximation technique-based immersion and invariance (FATII) control method is proposed in this work. Firstly, an unknown control system is restructured as the combination of an auxiliary system and a variation term from the original system. The variation term is treated as a time-varying uncertainty and parameterized by a group of weighted chosen basis functions. These weights are estimated at every time instant, and the change of the estimates is governed by an update law. The update law is defined based on an immersion and invariance approach such that both the system state and the estimation error converge to zero. The FATII method is model-free and thus applicable to a wide range of systems. The asymptotic stability of the proposed method is established, and its feasibility is verified under simulations.

 

Adaptive coverage control for multi-agent systems

This work presents a safe adaptive coverage controller for mobile sensing networks and multi-agent systems with actuator faults and time-varying uncertainties. The centroidal Voronoi tessellation (CVT) is applied to generate an optimal configuration of multi-agent systems for covering an area of interest. As conventional CVT based controller cannot prevent collisions between agents with non-zero size, a control barrier function (CBF) based controller is developed to ensure collision avoidance with a function approximation technique (FAT) based design to deal with system uncertainties. The proposed controller is verified under simulations.