DESIGNING (APPROXIMATE) OPTIMAL CONTROLLERS via DHP ADAPTIVE CRITICS & NEURAL NETWORKS
نویسندگان
چکیده
1. BACKGROUND The objective of this chapter is to provide the reader some guidance in applying the Dual Heuristic Programming (DHP) method in the context of designing neural-network controllers. DHP is a member of the class of Critic methods, which in turn is a member of the class of Reinforcement Learning methods. Development of the DHP method benefited from the confluence of several other developments; the following subsections describe associated background ideas useful in appreciating the DHP method. Subsequent sections will describe the DHP method itself, provide suggestions for application of DHP, and present worked-out examples.
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