Adaptive PSO-LS-Wavelet H∞ control for Two-Wheeled Self-Balancing Scooter

다국어 초록 (Multilingual Abstract)

The current study is concerned with adaptive Particle Swarm Optimization Least Square Wavelet H∞ fora two-wheel self-balancing scooter that provides a platform in order to balance itself and transport the driver inaccordance to its natural lean. In order to keep the rider close to the upright position over smooth and non-smoothsurfaces, providing a stable control system is the main challenge for the aforementioned vehicle. For this purpose,H∞ is combined with adaptive algorithm, Least Square Support Vector Machine (LS-SVM) and Particle SwarmOptimization (PSO) to construct the adaptive control. The most important feature of the proposed control strategyis its inherent robustness and ability to handle the nonlinear behavior of the system. Simulations results indicatedthat the introduced motion control architecture is capable of providing appropriate control actions to achieve bothposition control and trajectory tracking satisfactorily.

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