Adaptive backstepping control of a wheeled mobile robot

This paper proposes an adaptive nonlinear controller to stabilize an autonomous wheeled mobile robot. The controller equations are obtained following a backstepping approach. The robot model is divided into two parts: a state space model with intermediate control inputs and algebraic nonlinear equations relating the true and the intermediate control inputs. The robot parameters are assumed unknown. First, a suitable change of variable is applied to the traditional robot dynamics to reveal the strict feedback structure of this state space model. ext, a three-step adaptive backstepping control design method is applied to obtain the intermediate control input expressions. Finally the true control inputs are found by solving iteratively the nonlinear equations that relates intermediate and true control inputs. The adaptation algorithms are based on the projection method and guarantee that estimated parameters converge and remain inside predefined domains. The proposed design strategy is tested in simulation. The results show good tracking performances despite large parameter variations.

[1]  Andrew Bartlett,et al.  Robust Control: Systems with Uncertain Physical Parameters , 1993 .

[2]  Miroslav Krstic,et al.  Nonlinear and adaptive control de-sign , 1995 .

[3]  R. Marino,et al.  Robust adaptive state-feedback tracking for nonlinear systems , 1998, IEEE Trans. Autom. Control..

[4]  Richard Bishop Intelligent Vehicle Applications Worldwide , 2000, IEEE Intell. Syst..

[5]  M.E. Khatir,et al.  Decentralized control of a large platoon of vehicles operating on a plane with steering dynamics , 2005, Proceedings of the 2005, American Control Conference, 2005..

[6]  M. Hirsch,et al.  On Algorithms for Solving f(x)=0 , 1979 .

[7]  Yingmin Jia,et al.  Robust control with decoupling performance for steering and traction of 4WS vehicles under velocity-varying motion , 2000, IEEE Trans. Control. Syst. Technol..

[8]  Frank L. Lewis,et al.  Control of a nonholonomic mobile robot using neural networks , 1998, IEEE Trans. Neural Networks.

[9]  Pu Li,et al.  Improving Handling Stability Performance of Four-Wheel Steering Vehicle via $\mu$-Synthesis Robust Control , 2007, IEEE Transactions on Vehicular Technology.

[10]  Pablo González de Santos,et al.  The evolution of robotics research , 2007, IEEE Robotics & Automation Magazine.

[11]  Fumio Miyazaki,et al.  A stable tracking control method for an autonomous mobile robot , 1990, Proceedings., IEEE International Conference on Robotics and Automation.