Work

Adaptive Asymptotic Tracking Control for the Dynamic Models of Differential-Drive Unmanned Ground Vehicles Under Parametric Uncertainties

Year: 2026

Type: article

Abstract: This paper proposes a dual-loop layered control mechanism for the dynamic trajectory tracking of non-holonomic unmanned ground vehicles (UGVs). The proposed scheme enhances steady-state precision while guaranteeing parameter convergence under specified trajectory constraints. To tackle the underactuated constraints of Unmanned Ground Vehicles, the control mechanism is structured into kinematic and dynamic loops. Specifically, a kinematic controller is first synthesized to serve as a virtual control law, generating desired velocity commands. Subsequently, a layered adaptive control strategy based on the Immersion and Invariance technique is developed for the dynamic loop. This strategy integrates a parameter estimation layer, which utilizes tailored tuning functions to ensure the exponential convergence of estimation errors under the condition that the reference trajectory is not persistently vertical. A controller design layer is then responsible for uncertainty compensation. By decoupling parameter adaptation from control law synthesis, the proposed mechanism circumvents the structural limitations of the certainty equivalence principle. Theoretical analysis confirms that the proposed design achieves almost-global asymptotic tracking. Simulation results demonstrate that the mechanism resolves the imprecise parameter convergence inherent in traditional adaptive schemes, eliminates steady-state pose fluctuations during time-varying trajectory tracking, and achieves asymptotic convergence of tracking errors.

Source: Drones

DOI: 10.3390/drones10060465

Authors: Min Zhang, Song Gao, Chaobo Chen, Qingmin Liu, Kai Cao, Tianli Ma

Institution: Xi'an Technological University

Language: English

Topic: Control and Dynamics of Mobile Robots

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funders: National Natural Science Foundation of China, Education Department of Shaanxi Province, Key Research and Development Projects of Shaanxi Province