Composite adaptation and learning techniques were initially proposed for improving
parameter convergence in adaptive control and have generated considerable research …

This article addresses the problem of distributed path following of multiple under-actuated
autonomous surface vehicles (ASVs) with completely unknown kinetic models. An integrated …

A real-time Deep Neural Network (DNN) adaptive control architecture is developed for
general uncertain nonlinear dynamical systems to track a desired time-varying trajectory. A …

Networked control systems have gained considerable attention over the last decade as a
result of the trend towards decentralised control applications and the emergence of cyber …

This article focuses on the problem of adaptive safe stabilization for a class of nonlinear
control affine systems with parameter uncertainties. Two novel definitions of adaptive control …

This paper studies the problem of utilizing data-driven adaptive control techniques to
guarantee stability and safety of uncertain nonlinear systems with high relative degree. We …

This article investigates the tracking problem of an uncertain-link robot manipulator with
guaranteed safety and performance. To tackle parametric uncertainties, the torque filtering …

This paper develops a model-based reinforcement learning (MBRL) framework for learning
online the value function of an infinite-horizon optimal control problem while obeying safety …

This paper studies the problem of synthesizing control policies for uncertain continuous-time
nonlinear systems from linear temporal logic (LTL) specifications using model-based …

Piecewise affine (PWA) systems are attractive models that can represent various hybrid
systems with local affine subsystems and polyhedral regions due to their universal …