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.
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