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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2025  > In Press, Accepted Manuscript
J.-Z. Yang, J.-X. Zhang, and T. Chai, “Prescribed performance control of nonlinear systems with unknown sign-switching virtual control coefficients,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 0, pp. 1–10, Dec. 2025.
Citation: J.-Z. Yang, J.-X. Zhang, and T. Chai, “Prescribed performance control of nonlinear systems with unknown sign-switching virtual control coefficients,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 0, pp. 1–10, Dec. 2025.
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Prescribed Performance Control of Nonlinear Systems With Unknown Sign-Switching Virtual Control Coefficients

Funds:  This work was supported in part by the National Natural Science Foundation of China (61991404, 62473089), the Research Program of the Liaoning Liaohe Laboratory (LLL23ZZ-05-01), the Key Research and Development Program of Liaoning Province of China (2023JH26/10200011), the 111 Project 2.0 of China (B08015), the National Key Research and Development Program of China (2022YFB3305905), the Xingliao Talent Program of Liaoning Province of China (XLYC2203130), the Natural Science Foundation of Liaoning Province of China (2024JH3/10200012, 2023-MS-087), the Open Research Project of the State Key Laboratory of Industrial Control Technology of China (ICT2024B12), and the Fundamental Research Funds for the Central Universities of China (N2108003, N2424004)
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    Abstract
  • The problem of high-performance tracking control for the lower-triangular systems with unknown sign-switching virtual control coefficients as well as unmatched disturbances is investigated in this paper. Instead of the online estimation algorithm, the sliding mode method and the Nussbaum gain technique, a group of orientation functions are employed to handle the unknown sign-switching virtual control coefficients. The control law is combined with the orientation functions and the barrier functions lumped in a recursive manner. It achieves output tracking with the preassigned rate, overshoot, and accuracy. In contrast with the existing solutions, it is effective for the nearly model-free case, with the requirement for information of neither the system nonlinearities nor their bounding functions of the plant, nor the bounds of the disturbances. In addition, our controller exhibits significant simplicity, without parameter identification, disturbance estimation, function approximation, derivative calculation, dynamic surfaces, or command filtering. Two simulation examples are conducted to substantiate the efficacy and advantages of our approach.

     

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