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Adaptive critic anti-slip control of wheeled autonomous robot
Author(s): W.-S. Lin, L.-H. Chang, P.-C. Yang
Source: IET Control Theory & Applications, Volume 1, Issue 1, 2007 , p. 51 - 57
Type: Article
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When a wheeled autonomous robot drives with wheel slips, the velocity and posture control becomes difficult. An ideal automatic driving control system should be able to comply with changes in slip conditions so as to optimise the control performance. Using dual heuristic programming and multi-layer perceptron neural networks, an adaptive critic anti-slip control design is developed to achieve this goal. The critic structure enables neural network learning by satisfying the Bellman equation so that the inclination of the action performance can be assessed to improve the control parameters. A slip model of the robot vehicle is derived. The adaptive critic anti-slip control system is verified extensively by computer simulation. The result shows that the performance is significantly better than that of using traditional fuzzy control.

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Hierarchical fuzzy control for autonomous navigation of wheeled robots
Author(s): W.-S. Lin, C.-L. Huang, M.-K. Chuang
Source: IEE Proceedings - Control Theory and Applications, Volume 152, Issue 5, 2005 , p. 598 - 606
Type: Article
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The autonomous navigation wheeled robots (WR) requires integrated kinematic and dynamic control to perform trajectory tracking, path following and stabilisation. Considering a WR is a nonholonomic dynamic system with intrinsic nonlinearity, unmodelled disturbance and unstructured unmodelled dynamics, fuzzy logic system based control is appropriate and practical. However, the multivariable control structure of the WR results in the curse of dimensionality of the fuzzy design and prevents a domain expert from building the linguistic rules for autonomous navigation. Hierarchical fuzzy design decomposes the controller into three low-dimensionality fuzzy systems: fuzzy steering, fuzzy linear velocity control and fuzzy angular velocity control, so that manual construction of each rule base becomes feasible and easy. The proposed design enables a WR to perform position control in trajectory tracking and velocity profile tracking in continuous drive. The coupling effect between linear and angular motion dynamics is considered in the fuzzy steering by building appropriate linguistic rules. To facilitate the autonomous navigation design and verification, a prototype and the model of a kind of WR have been developed, and equipped with the hierarchical fuzzy control system. The simulation and experimental results are shown and compared.

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