The idea of optimization can be regarded as an important basis of many disciplines and hence is extremely useful for a large number of research fields, particularly for artificial-intelligence-based advanced control design. Due to the difficulty of solving optimal controlOptimal control problems for general nonlinear systems, it is necessary to establish a kind of novel learning strategies with intelligent components. Besides, the rapid development of computer and networked techniques promotes the research on optimal controlOptimal control within the discrete-time domain. In this chapter, the bases, derivations, and recent progresses of critic intelligence for discrete-time advanced optimal controlAdvanced optimal control design are presented with an emphasis on the iterative framework. Among them, the so-called critic intelligenceCritic intelligence methodology is highlighted, which integrates learning approximators and the reinforcement formulation.
On the Critic IntelligenceCritic intelligence for Discrete-Time Advanced Optimal ControlAdvanced optimal control Design
Intelligent Control & Learning Systems
Advanced Optimal Control and Applications Involving Critic Intelligence ; Chapter : 1 ; 1-28
2023-01-22
28 pages
Article/Chapter (Book)
Electronic Resource
English
Adaptive-Critic-Based Neural Networks for Aircraft Optimal Control
Online Contents | 1996
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