Barrier Function-Based Adaptive Sliding Mode Control for Disturbed Two-Wheeled Robot Obstacle Avoidance

Firouzi, Nasser; Khdir, Younis K.; Khazal, Haider; Podulka, Przemysław; Faqihi, Abdullah A.; Hadidi, Haitham M.

doi:10.22055/jacm.2026.49111.5743

Barrier Function-Based Adaptive Sliding Mode Control for Disturbed Two-Wheeled Robot Obstacle Avoidance

Articles in Press

Document Type : Research Paper

Authors

Nasser Firouzi ¹

Younis K. Khdir ²

Haider Khazal ³

Przemysław Podulka ⁴

Abdullah A. Faqihi ⁵

Haitham M. Hadidi ⁶

¹ Institute of Structural Mechanics, Bauhaus-University Weimar, Weimar, Germany

² Mechanical and Energy Engineering Department, Technical Engineering College, Erbil Polytechnic University, Erbil 44001, Iraq; email: younis.khdir@epu.edu.iq

³ Mechanical Engineering Department, College of Engineering, University of Basrah

⁴ Rzeszów University of Technology Faculty of Mechanical Engineering and Aeronautics 35-959 Rzeszów Powstańcow Warszawy 12 Str

⁵ Department of Industrial Engineering, College of Engineering and Computer Sciences, Jazan University, Jazan, Saudi Arabia

⁶ Department of Mechanical Engineering, College of Engineering and Computer Science, Jazan University, Jazan 45142, Saudi Arabia

10.22055/jacm.2026.49111.5743

Abstract

In this article, a novel optimal adaptive sliding mode control integrated with a control barrier function is designed for the safe navigation of a two-wheeled mobile robot subjected to unknown external disturbances. The nominal reference tracking is achieved using the sliding mode approach in which the switching gains capable of disturbance and un-certainty rejection are updated by developed adaptive laws, eliminating the need for prior knowledge of the disturbance upper bound. To further improve the closed-loop performance, additional control parameters are optimized using a particle swarm optimization algorithm which reduces steady-state tracking errors and mitigates high-value overshoots. Integrating the control barrier function in the proposed control framework guarantees obstacle avoidance by minimizing deviations between the safe control signals and those of the nominal control inputs. Simulation results illustrate the effectiveness of the proposed method in achieving accurate trajectory tracking, ensuring collision-free navigation, and maintaining control efficiency under uncertain conditions. Moreover, comparative simulation studies with a PD controller confirm that the proposed control structure has way better performance in disturbance rejection, minimizing control efforts, and path following.

Keywords

Adaptive sliding mode control

obstacle avoidance

mobile robot

Control barrier function

Particle swarm optimization

Subjects