Neural algorithms of optimal and adaptive control of mechanical systems

Methods and principles of optimal and adaptive control of mechanical systems are discussed, as well as principles of their neural implementation for optimal control in real time. Optimal programmed controllers, feedback controllers, adaptive controllers and programmers of optimal movements of nonlinear mechanical systems with reversible dynamics are synthesised. Methods of optimal and adaptive controller and programmer parameters adjustment are proposed, and parallel (neural) architectures for their implementation are discussed.