Design and experimental evaluation of a hierarchical coupling motion controller for distributed vehicles considering hierarchical control characteristics

A hierarchical coupling motion controller was introduced in this paper to address distributed vehicles high controllability and redundancy challenges. The controller models and compensates for hierarchical control characteristics explicitly to ensure that the upper-level control objectives generated are achievable by the lower-level controllers. To mitigate modeling errors within hierarchical controllers, we have developed a multi-objective optimization-based (MOO) algorithm for modeling hierarchical control characteristics, and the prediction model in the motion tracking (MT) layer was augmented. The MT layer employs a variable-time step discrete linear time-varying model predictive controller (VTDLTV-MPC) to compute the target global force/moment. This approach allows for adaptive changes to linearization reference points (LRP) based on the prior prediction state and control sequence and extends the prediction horizon using a variable-time step discrete method, thereby avoiding additional computational load. Additionally, this paper introduces a method for calculating heading deviation reference values by considering the reference sideslip angle, effectively decoupling the lateral and yaw motion of the vehicle. This method allows for simultaneous consideration of the vehicle's target posture during motion control. A distributed vehicle experimental platform has been constructed and experiments have been conducted to demonstrate the effectiveness of the proposed controller in managing both posture and coupling motion control, which exploits the motion potential fully to maintain the vehicle stability and tracking accuracy. Experimental videos demonstrating these validations are available: Video link. https://drive.google.com/file/d/1q_byDiDo7Jfivu37RXPynsOyWeOejQdu/view?usp=sharing