Title: Multi-constraint model predictive visual servo control algorithm with penalty factor

Authors: Yuhan Zhao; Yang Lu; Jingzhen Guo; Liteng Liu; Sen Zhang; Wenlong Zhao

Addresses: School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China ' School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China ' Centre for Collaborative Research, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China ' School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China ' School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China ' Centre for Collaborative Research, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China

Abstract: Visual servo control (VSC) is widely used in medical robot. But it contends with drawbacks such as servo failure caused by loss view. The traditional proportional (P) controller in image-based visual servoing (IBVS) has defects in dealing with constraints. It is also difficult to maintain fast response and stability when tracking fast moving targets. To address these issues, model predictive controller (MPC) is integrated into IBVS, enabling better prediction and response to fast-moving targets. This fusion aims to reduce the risk of visual feature loss, enhance tracking performance, and significantly accelerate convergence velocity. In this paper, a multi-constrained MPC controller with penalty factor is proposed, and strict joint position, velocity and acceleration constraints are carried out, and visual boundary constraints are incorporated into the prediction process. In addition, the cost function takes into account various adverse conditions to enhance the robustness of the system. These improvements enable the manipulator to flexibly adapt to the surrounding environment and complex conditions, thereby improving the reliability and performance of the system. The results show that the proposed IBVS-MPC controller significantly improves the convergence velocity of the servo system. It also improves tracking stability and safety compared with MPC without penalty factor.

Keywords: model predictive control; image-based visual servoing; IBVS; visual boundary; penalty factor; image Jacobi matrix.

DOI: 10.1504/IJISTA.2026.153224

International Journal of Intelligent Systems Technologies and Applications, 2026 Vol.24 No.2, pp.157 - 174

Received: 03 Apr 2024
Accepted: 02 Sep 2024
Published online: 29 Apr 2026 *

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