Title :
Learning control of failure avoidance problems with known analytical form of cost function
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Univ., Chicago, IL, USA
Abstract :
We study adaptive critic designs for a class of failure avoidance control problems. We categorize such problems by the choice of local cost function as zero throughout a trial except at the last time step when a failure occurs. We derive an analytical form of its overall cost function defined as the infinite summation of the local cost function over time. We demonstrate that the outputs of the critic network after learning resemble well the analytically derived cost function.
Keywords :
cost optimal control; discrete time systems; dynamic programming; failure analysis; learning (artificial intelligence); neurocontrollers; nonlinear control systems; action-dependent heuristic dynamic programming; adaptive critic designs; approximate optimal control; cart-pole problem; critic network; discrete-time nonlinear dynamical system; dynamic programming; failure avoidance control problems; infinite summation; learning control; local cost function; neural network learning; nonlinear environments; overall cost function; Adaptive control; Control systems; Cost function; Dynamic programming; Failure analysis; Neural networks; Nonlinear control systems; Optimal control; Programmable control; Signal design;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1020716