Optimization Driven Robust Control of Mechanical Systems with Parametric Uncertainties

    Received 08 November 2023; accepted 11 December 2023; published 25 December 2023

    2023, Vol. 19, no. 4, pp.  585-597

    Author(s): Fam C. A., Nedelchev S.

    This paper presents a control algorithm designed to compensate for unknown parameters in mechanical systems, addressing parametric uncertainty in a comprehensive manner. The control optimization process involves two key stages. Firstly, it estimates the narrow uncertainty bounds that satisfy parameter constraints, providing a robust foundation. Subsequently, the algorithm identifies a control strategy that not only ensures uniform boundedness of tracking error but also adheres to drive constraints, effectively minimizing chattering. The proposed control scheme is demonstrated through the modeling of a single rigid body with parameter uncertainties. The algorithm possesses notable strengths such as maximal compensation for parametric uncertainty, chattering reduction, and consideration of control input constraints. However, it is applicable for continuous systems and does not explicitly account for uncertainty in the control input.
    Keywords: optimization, sliding mode control, parametric uncertainty, stability
    Citation: Fam C. A., Nedelchev S., Optimization Driven Robust Control of Mechanical Systems with Parametric Uncertainties, Rus. J. Nonlin. Dyn., 2023, Vol. 19, no. 4, pp.  585-597

    Download File
    PDF, 1.46 Mb

    Creative Commons License
    This work is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License