State Predictive Control with Multiple Modification Terms and Robust Stability Analysis Based on Complementary Sensitivity Functions

Yanase, Shotaro; Masui, Yoichiro; Hirata, Kentaro; Hagiwara, Tomomichi

doi:10.1016/j.ifacol.2020.12.1036

Cited by 2 publications

(2 citation statements)

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“…It readily follows for the above special case that the modified state predictive control system is stable if and only if A+BF is Hurwitz and M is Schur. The closed-loop poles for the case when μ i (i = 0,...,N −1) have mutually rational ratios can readily be obtained through the results for this special case (see [6] for details).…”

Section: Roots Of the Characteristic Equationmentioning

confidence: 99%

“…An earlier version of this paper extending the treatment in [5] was presented in the conference paper [6], but the derivations of the characteristic equation and the complementary sensitivity function of the closedloop system, together with the comparison of the simulation results, were not given. The present paper also considers a different improved numerical example as well as non-parametric uncertainties in the simulations so that the effectiveness of modified state predictive control in enhancing robust stability against such uncertainties can be demonstrated also in the time domain.…”

Section: Introductionmentioning

confidence: 99%

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Modified State Predictive Control Aiming at Improving Robust Stability

Hagiwara,

Yanase,

Masui

et al. 2023

Transactions of ISCIE

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Finite spectrum assignment, also known as state predictive control, is an effective control method for systems with time delay in the input. This paper considers introducing some modification on the control law of state predictive control, where the modification can be interpreted, roughly speaking, as suitably taking account of the (intentionally introduced) deviation of the past input from what is desired in the sense of the conventional state predictive control. The motivation for introducing such modification lies in an attempt to modify the dynamics of the controller while maintaining a feature of the conventional state predictive control to a certain extent. In particular, we aim at improving robust stability for non-parametric uncertainties of the plant. We first derive the characteristic equation of the modified state predictive control systems, and give a necessary and sufficient condition for stability. We then derive an explicit representation of the complementary sensitivity function associated with the robust stability analysis problem for multiplicative uncertainties. Finally, we demonstrate through a numerical example that modified state predictive control can indeed be useful for improving robust stability if the modification is introduced suitably.

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Section: Roots Of the Characteristic Equationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%