Title :
An online actor/critic algorithm for event-triggered optimal control of continuous-time nonlinear systems
Author :
Vamvoudakis, Kyriakos G.
Author_Institution :
Center for Control, Dynamical-Syst. & Comput. (CCDC), Univ. of California, Santa Barbara, Santa Barbara, CA, USA
Abstract :
This paper proposes a novel optimal adaptive event-triggered control algorithm for nonlinear continuous-time systems. The goal is to reduce the controller updates, by sampling the state only when an event is triggered to maintain stability and optimality. The online algorithm is implemented based on an actor/critic neural network structure. The algorithm proposed exhibits dynamics with continuous evolutions described by ordinary differential equations and instantaneous jumps. A Lyapunov stability proof ensures that the closed-loop system is asymptotically stable.
Keywords :
Lyapunov methods; adaptive control; asymptotic stability; closed loop systems; continuous time systems; differential equations; discrete event systems; evolutionary computation; neurocontrollers; nonlinear control systems; optimal control; Lyapunov stability proof; actor-critic neural network structure; asymptotic stability; closed-loop system; continuous evolution; continuous-time nonlinear systems; controller update reduction; event-triggered optimal control; instantaneous jumps; online actor-critic algorithm; optimal adaptive event-triggered control algorithm; optimality; ordinary differential equations; state sampling; Asymptotic stability; Closed loop systems; Equations; Heuristic algorithms; Lyapunov methods; Neural networks; Stability analysis; Even-triggered optimal adaptive control; actor/critic framework;
Conference_Titel :
American Control Conference (ACC), 2014
Conference_Location :
Portland, OR
Print_ISBN :
978-1-4799-3272-6
DOI :
10.1109/ACC.2014.6859198
