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This dissertation presents a novel model-based control scheme for a self-driving vehicle simulator prototype. The entire system is modeled as a descriptor system in semi-explicit form for system analysis and control design. A trajectory tracking controller is developed based on differential parameterization. In addition, robustness in the presence of parameter uncertainties and disturbances is achieved using the Ljapunov-stability-based method without change of the essential control structure. A new model-based approach to design the motion cueing strategy is proposed, which formulates the trajectory generation problem as a constrained optimal control problem resolved in a model predictive control manner. Furthermore, an imperceptible washout strategy is developed in order to resolve the stabilization problem caused by the nonhyperbolic internal dynamics while keeping the perceptual constraints under the detection thresholds. Experimental results show the effectiveness of the developed control scheme. The proposed wheeled driving simulator can fulfill increased demands of urban traffic simulation and provide a great potential for developing and testing highly complex automated driving functions in automotive industry.
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Model-based control of a highly dynamic wheeled driving simulator, Zhongyi Gong
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- Année de publication
- 2018
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