New results on adaptive systems

Abstract

Adaptive control had its peak in when multiple classic results on closed-loop control and parameter estimation were reported, such as References 1-3, and it is still of interest in our time. The current research directions of direct adaptive control address the problems of robustness and guaranteed performance, whereas one of the principal research axes of indirect adaptation and parameter estimation is the relaxation of excitation requirements. 4 These researches gave rise to various modern results of adaptive control, such as concurrent learning, 5 composite learning, 6 dynamic regressor extension and mixing, 7 as well as regulation methods, for example, those inspired by recent data-driven learning advances. 8 This special issue aims to provide state-of-the-art developments of new approaches in adaptive control, both direct and indirect, covering various topics of adaptive systems and their applications.The issue includes seven papers that can be divided into three groups. The first group focuses on direct adaptive control and its robustness to model uncertainties and disturbances. The second group studies adaptive parameter estimation under less restrictive excitation requirements than classic approaches. The third group unites these topics by addressing indirect adaptive solutions to control problems.The first group includes two papers, and both pay special attention to the robustness to parametric and signal uncertainties.• Rodrigues, Hsu, Oliveira, and Fridman, in their paper "Adaptive sliding mode control with guaranteed performance based on monitoring and barrier functions," propose a solution addressing both transient and tracking performance guarantees using a novel combination of two adaptation tools: monitoring and barrier function. The authors illustrate the benefits of the proposed method with an anti-lock braking system example.