Weighting function selection in H/sub ∞/-optimal control with application to a thyristor-driven DC-motor

Kneppova, V.; Kiffmeier, Ulrich; Unbehauen, H.

doi:10.1109/acc.1995.532064

Cited by 9 publications

(7 citation statements)

References 3 publications

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“…As shown in the figure, r(s) represents the reference input, e(s) the tracking error, u(s) the control input, d(s) the external (e.g., road) disturbance, y(s) the output, n(s) the noise of measurement, and K(s) the H ∞ LSC controller to be devised. We define the output y(s), tracking error e(s), and control input u(s) as: [27], which is subjected to the conservation law specified as [28],…”

Section: Controller Design Problemmentioning

confidence: 99%

“…As shown in the figure, 𝒓 𝑠 represents the reference input, 𝒆 𝑠 the tracking error, 𝒖 𝑠 the control input, 𝒅 𝑠 the external (e.g., road) disturbance, 𝒚 𝑠 the output, 𝒏 𝑠 the noise of measurement, and 𝑲 𝑠 the 𝐻 LSC controller to be devised. We define the output 𝒚 𝑠 , tracking error 𝒆 𝑠 , and control input 𝒖 𝑠 as: 𝑮 𝑠 𝑲 𝑠 the complementary sensitivity function [27], which is subjected to the conservation law specified as [28], With the consideration of additive modeling errors and removing the road disturbance for simplicity, we illustrate the control system in the block diagram shown in Figure 5, in which ∆ 𝑠 denotes the modeling uncertainty. The transfer function between the uncertain input and output can be expressed as:…”

Section: Controller Design Problemmentioning

confidence: 99%

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A Design Synthesis Method for Robust Controllers of Active Vehicle Suspensions

Zhu

2022

Designs

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This paper presents a design synthesis method for robust controllers of active vehicle suspensions (AVSs). Various control techniques have been applied to the design of AVSs for enhancing ride comfort and handling performance of ground vehicles. However, most of these model-based controller designs show poor robustness when the vehicle models are not accurate and operating conditions vary. To address the poor robustness problem of AVSs, a new controller is designed using the H∞ loop-shaping control technique. The controller targets robustness issues on vehicle models with parametric uncertainties and unmodelled dynamics. To facilitate the robust controller design, a design synthesis method is proposed: the H∞ loop-shaping controller design is formulated as a multi-objective optimization problem, the weighting functions’ parameters of the controller are treated as design variables, the expensive computing loads are handled by a parallel computing technique, and the solution of the optimization problem is the desired robust AVS controller. Simulation results demonstrate the benefits of the proposed AVS design.

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Section: Controller Design Problemmentioning

confidence: 99%

Section: Controller Design Problemmentioning

confidence: 99%

A Design Synthesis Method for Robust Controllers of Active Vehicle Suspensions

Zhu

2022

Designs

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“…This algorithm requires an augmented system that is the relationship between the variables of interest (the error and control variables) and the overall perturbations [54], [55]. The augmented system includes the weight functions that are used to construct the controller and to obtain the desired performances [56][57][58][59].…”

Section: Control Designmentioning

confidence: 99%

“…That gives: (28) The  value is positive and will be extracted using GDOA. Based on [57] and [58], the selected weight functions have the following mathematical expressions:…”

Section: Control Designmentioning

confidence: 99%

H∞based control of a DC/DC buck converter feeding a constant power load in uncertain DC microgrid system

Boukerdja¹,

Chouder²,

Hassaine

et al. 2020

ISA Transactions

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“…The choosing of weighting functions is an essential part in robust controller design, and many researches had been done concerning this issue [17][18][19]. In fact, mainly three kinds of weighting functions are used frequently in suspension controller design practices.…”

Section: H1 Control Strategymentioning

confidence: 99%