Abstract
The ability of a control scheme for a mobile robot to ensure satisfactory performance in an unstructured or unknown environment is what makes the control law unique. Various sources of uncertainties pose a serious challenge to the tracking performance of the system. The state-of-the-art control law presented in Chap. 1 cannot ensure stability in the presence of uncertainties due to feedback linearization methodology, as it requires exact cancellation of the nonlinearities in the system [1, 2]. Moreover, singular perturbation-based approach is prone to generate high control gains which may jeopardize the integrity of the actuators [1, 2]. This is where robust control techniques step in, to assure stable and acceptable performance in the presence of uncertainties. To imitate variation of ground condition, time-varying uncertainties have been induced through the friction coefficients in the planar snake robot model. These uncertainties have been assumed to be bounded with a known upper bound to implement a Sliding-Mode Control (SMC) law with the aim of achieving efficient head-angle and velocity tracking. Furthermore, to relax the constraint on the uncertainty bound and also to solve the overestimation of switching gain, an adaptive SMC has been proposed to improve the tracking performance.
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Mukherjee, J., Kar, I.N., Mukherjee, S. (2021). Adaptive Sliding-Mode Control for Velocity and Head-Angle Tracking. In: Adaptive Robust Control for Planar Snake Robots. Studies in Systems, Decision and Control, vol 363. Springer, Cham. https://doi.org/10.1007/978-3-030-71460-4_2
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DOI: https://doi.org/10.1007/978-3-030-71460-4_2
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