Nullspace Adaptive Identification of Plant and Actuator Model Parameters for Underactuated Ground Vehicles: Theory and Experimental Evaluation ⁎

作     者：Allan H. Elsberry Jeremy J. Dawkins Annie M. Mao Louis L. Whitcomb 

作者机构：Department of Weapons Robotics and Control Engineering United States Naval Academy Annapolis MD 21401 USA Department of Mechanical Engineering Johns Hopkins University Baltimore MD 21218 USA 

出 版 物：《IFAC-PapersOnLine》 

年 卷 期：2024年第58卷第28期

页      面：1097-1102页

主　　题：Nonlinear Adaptive Control Vehicle Dynamics Model Parameter Identification 

摘      要：This paper reports a novel Nullspace Adaptive Identification (NSAID) algorithm to estimate plant and actuator model parameters for an underactuated ground vehicle with dynamics represented by a 3 degree-of-freedom second-order dynamic model, and reports an evaluation of its performance in simulation and experiments. Precise identification of ground vehicle plant and actuator model parameters is critical for physically realistic model-based simulation, control, navigation, and fault detection. However, ground vehicle plant model parameters, such as vehicle mass, moments of inertia, tire cornering stiffness and actuator model parameters such as motor torque constants are generally not possible to estimate a priori from first principles, and can change with varying payloads, configurations, and driving environments, and thus must be determined experimentally. Some parameter identification methods such as least squares regression depend on acceleration measurements, and most identification methods assume a priori knowledge of actuator parameters. In contrast, NSAID estimates plant and actuator parameters simultaneously, does not require acceleration measurements, can be utilized offline or online during vehicle operation, and can be applied with open or closed-loop control.