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Intelligent robust control system of robotic unicycle based on the end-to-end soft computing technology

International Robotics & Automation Journal
Ulyanov Sergey,1 Ulyanov Viktor2

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The concept of an intelligent control system for a complex nonlinear biomechanical control object of an extension cableless robotic unicycle is considered. A thermodynamic approach to study optimal control processes in complex nonlinear dynamic systems is applied. The results of stochastic simulation of a fuzzy intelligent control system for various types of external/internal excitations for a dynamic, globally unstable control object-extension cableless robotic unicycle based on Soft Computing (Computational Intelligence Toolkit) technology are presented. A new approach to design an intelligent control system based on the principle of the minimum entropy production (minimum of useful resource consumptions) determination in the control object movement and the control system is developed. This determination as a fitness function in the genetic algorithm to achieve robust control of a robotic unicycle is used. An algorithm for entropy production calculation and representation of their interrelationship with the Lyapunov function (a measure of stochastic robust stability) is described.


robotics unicycle, intelligent control systems, essentially nonlinear model, globally unstable model, stochastic simulation, soft computing, calculation, representation, determination, algorithm, entropy, production, algorithm, dynamic, theory