Geodesic
Optimization Driven Robust Control of Mechanical
Russian journal of nonlinear dynamics, Tome 19 (2023) no. 4, pp. 585-597

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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 
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     author = {Ch. A. Fam and S. Nedelchev},
     title = {Optimization {Driven} {Robust} {Control} of {Mechanical}},
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     pages = {585--597},
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     number = {4},
     year = {2023},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/ND_2023_19_4_a8/}
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Ch. A. Fam; S. Nedelchev. Optimization Driven Robust Control of Mechanical. Russian journal of nonlinear dynamics, Tome 19 (2023) no. 4, pp. 585-597. http://geodesic.mathdoc.fr/item/ND_2023_19_4_a8/