Quasi-equivalent State Space Modeling Research Of Two-wheeled Differentially Driven Mobile Robot

Two-wheeled differentially driven mobile robot (TDDMR) has simple structureand is easy control. The study of robot motion model is an important part of academicfield and is of practical significance for accurate description and control of mobilerobot.In physical robot system, there have the following characteristics:①The drive system always contains two double closed-loop control structurewhere nonlinear links exist according to previous study. Meanwhile, Changes inloads of the robot also influence the dynamic behavior of drive system.②Two-wheeled differentially driven mobile robot is a system subject to classicalnonholonomic constraints.③As a typical multi-input-multi-output (MIMO) system, the mobile robot systemhas mutual coupling between two underlying control circuit.In a word, the mobile robot is not only subject to nonholonomic constraints, butalso a multi-input-multi-output (MIMO) system that contain closed-loop nonlinear linksand dynamic coupling. Thus the establishment of the robot motion model is an emphasisand difficulty in theoretic study related to nonlinearity.The quasi-equivalent modeling approach is an nonlinear modeling method bywhich some important parameters can be included in the model that reflect majorproperties of physical system. This approach is adopted to establish the motion modelof the TDDMR. The main works are as follows:①Based on double closed-loop control system load variable quasi-equivalentmodel, the state space motion model of two-wheeled differentially driven mobile robotis established.By introducing the dynamic coupling into dynamic structure of double-closed loopdrive system and converting the loads of robot into equivalent moment of inertia of themodel, the quasi-equivalent state space motion model is obtained by means of thequasi-equivalent modeling approach.②The parameter tuning method of quasi-equivalent state-space motion modelbased on genetic algorithm is proposed.The robot system consists of two drive system coupled with each other, so theimproved genetic algorithm is used to tune parameters of the model by applying simultaneously step signals to the two drive system.③To validate the motion model and parameter tuning method, a novelload-adjustable two-wheel differential drive mobile robot being the experiment platformis designed in this paper.Experimental findings show that the modeling method and motion model proposedin this paper prove as practical.