Formation Trajectory Tracking Control of UTVs: A Coupling Multi-Objective Iterative Distributed Model Predictive Control Approach
Zheng Zang, Jianwei Gong, Zhiwei Li, Jiarui Song, Haiou Liu, Cheng Gong, Xi Zhang, Yuanyuan Li
Abstract
High-efficiency, real-time and precise formation trajectory tracking control (FTTC) is a fundamental and difficult task for unmanned tracked vehicles (UTVs) in unstructured variable curvature scenarios. It is quite challenging and time-consuming for FTTC optimization on UTVs, due to its strongly nonlinear constraint, poor real-time and computation complexity. In this paper, a coupling multi-objective iterative distributed model predictive control (CMOI-DMPC) approach is proposed to address the above difficulties. The proposed CMOI-DMPC approach consists of two steps. The first step is to build a linearized cross-coupled instantaneous centers of rotation (ICR) kinematics model of the UTV to address the strongly nonlinear constraints. The second step is to design a multi-objective iterative optimization DMPC strategy to solve the problems of time-consuming computation and low tracking accuracy. Moreover, the sufficient condition on ensuring closed-loop stability is demonstrated by Lyapunov theorem. The proposed CMOI-DMPC approach is also applied to solve an optimal FTTC problem of UTVs in near-natural simulation environment and real vehicle environment, which validates the effectiveness and practicality of the proposed CMOI-DMPC approach.