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In this paper, feedback tracking control for wheeled nonholonomic mobile robots is proposed based on kinematic model. Coordinate transformations are used firstly to transform the robot kinematics into chained form. Then the two controllers are designed separately and backstepping technology is used to design the controllers. The simulation results demonstrate the effectiveness of the proposed controllers.

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In this paper, adaptive output feedback control is presented to solve the stabilization problem of nonholonomic systems in chained form with strong nonlinear drifts and uncertain parameters using output signals only. The objective is to design adaptive nonlinear output feedback laws which can steer the closed‐loop systems to globally converge to the origin, while the estimated parameters remain bounded. The proposed systematic strategy combines input‐state scaling with backstepping technique. Motivated from a special case, adaptive output feedback controllers are proposed for a class of uncertain chained systems. The simulation results demonstrate the effectiveness of the proposed controllers. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society

In this paper, control of a nonholonomic mobile manipulators with unknown dynamics is considered using Diagonal Recurrent Neural Network. The system is subject to nonholonomic constraint. The adaptive recurrent neural network controller is presented to deal with the unmodelled dynamics in the system. The proposed control strategy guarantees that the system motion asymptotically converges to the desired manifold.