A new approach to design of smart intelligent control systems for advanced robotics and mechatronics is developed. The principle of minimum entropy production in a control object motion and a control system as a ®tness function for genetic algorithm is used. Simulation results of a smart robust control of non-linear systems described as coupled oscillators are presented.

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The structure of hardware asld software of AI control system of a m0blle robot for service use are described. Hardware of a mobile robot for service use include an autonomous wheel vehicle and a five degree of freedom manipulator. Software of AI control system of a mobile service robot is based on soft computing including fuzzy control rules, fuzzy neural network and genetic algorithms. Intelligent control of cooperative motion between of an autonomous vehicle and a manipulator r d i e the flexible operations as navigation of a mobile robot in presence of static and dynamic obstacles, the processes of opening door in rooms and push button of elemtor. New hieraxchical structure of PU control system includes direct humamrobot comunication line based on natural language and cognitive graphics, and generator of virtual reality for simulation of artificial life csnditions for mobile service robot. Simulation results and experimentd results of navigation and technoisgicd operations with mmipuiator for mobile robot of service use in office building are dexribed.

The soft computing simulation design methodology of intelligent control system for mobile micro-nanorobots based on modeling of non-linear dissipative equations of robots motion with a minimum entropy production is described. It includes hierarchical levels for description of dynamic behavior of mobile micro-nanorobots based on laws of microphysics, quantum logic of intelligent dynamic behavior of control objects, optimal control of states and dynamic system theory of mechanical motion. The description of a thermodynamic intelligent behavior (with minimum entropy production) of control objects (robots) and their interrelations with Lyapunov stability conditions are introduced. The role of soft computing on the basis of GA with a ®tness function as a minimum entropy production for intelligent control of mobile micro-nano-robots is discussed.

Our thermodynamic approach to the study and design of robust optimal control processes in nonlinear (in general global unstable) dynamic systems used soft computing based on genetic algorithms with a fitness function as minimum entropy production. Control objects were nonlinear dynamic systems involving essentially nonlinear stochastic differential equations. An algorithm was developed for calculating entropy production rate in control object motion and in control systems. Part 1 discusses relation of the Lyapunov function (measure of stability) and the entropy production rate (physical measure of controllability). This relation was used to describe the following qualitative properties and important relations: dynamic stability motion (Lyapunov function), Lyapunov exponent and Kolmogorov-Sinai entropy, physical entropy production rates, and symmetries group representation in essentially nonlinear systems as coupled oscillator models. Results of computer simulation are presented for entropy-like dynamic behavior for typical benchmarks of dynamic systems such as Van der Pol, Duffing, and Holmes-Rand, and coupled oscillators. Parts 2 and 3 discuss the application of this approach to simulation of dynamic entropy-like behavior and optimal benchmark control as a 2-link manipulator in a robot for service use and nonlinear systems under stochastic excitation.