Designing controller parameters of an LPV system via design space exploration

Abolpour, Roozbeh; Dehghani, Maryam; Sadabadi, Mahdieh S.

doi:10.1016/j.ejcon.2021.02.001

Cited by 8 publications

(3 citation statements)

References 24 publications

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“…The goal of the controller design method is to find appropriate matrices of the controller in ( 2) such that the closed-loop model avoids sever frequency deviation in presence of parameter uncertainties in the model. To solve the above problem, the direct searching idea, proposed in [26,32] is modified and used.…”

Section: Dynamic Output Controllermentioning

confidence: 99%

Optimal frequency regulation in an uncertain islanded microgrid: A modified direct search algorithm

Abolpour

Javanmardi

Dehghani

et al. 2022

IET Renewable Power Gen

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This paper presents a methodology for frequency regulation in a microgrid involving renewable energy sources (RES) using a dynamic controller, which is an output feedback controller (OFC). The parameters of OFC are tuned by searching the design space of the controller. Since the RES model is not exactly known, the uncertain model is derived and the OFC is considered for it. The goal of controller tuning is to find appropriate parameters of the controller such that the norm of frequency deviations, even in presence of uncertainties in the RES parameters is minimized. An algorithm based on searching the controller design space is suggested to find the suitable controller gains. The algorithm assumes the controller parameters lie in a convex space and searches the space systematically such that an appropriate solution is found. The method is proved mathematically and two theorems are mentioned, accordingly. Finally, a simulated model of a RES is utilized for algorithm evaluation and the results demonstrate the algorithm capability in optimal frequency regulation.

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Section: Dynamic Output Controllermentioning

confidence: 99%

Optimal frequency regulation in an uncertain islanded microgrid: A modified direct search algorithm

Abolpour

Javanmardi

Dehghani

et al. 2022

IET Renewable Power Gen

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“…After being sure about the suitability of the model, it is used for developing an LPV model for the COVID-19 pandemic according to the time-varying parameters. Stability analysis of this model according to various social distancing levels can obviously be done by such an LPV model using LMI-based methods or the direct searching idea [33] . The LPV model is also appropriate for model-based stability analysis and controller design for the COVID19 pandemic, especially, the robust stability analysis and controller design approaches.…”

Section: Introductionmentioning

confidence: 99%

Linear parameter varying model of COVID-19 pandemic exploiting basis functions

Abolpour

Siamak

Mohammadi

et al. 2021

Biomedical Signal Processing and Control

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Current outbreaks of the COIVD-19 pandemic demonstrate a global threat. In this paper, a conceptual model is developed for the COVID-19 pandemic, in which the people in society are divided into Susceptible, Exposed, Minor infected (Those who need to be quarantined at home), Hospitalized (Those who are in need of hospitalization), Intensive infected (ventilator-in-need infected), Recovered and Deceased. In this paper, first, the model that is briefly called SEMHIRD for a sample country (Italy as an example) is considered. Then, exploiting the real data of the country, the parameters of the model are obtained by assuming some basis functions on the collected data and solving linear least square problems in each window of data to estimate the time-varying parameters of the model. Thus, the parameters are updated every few days, and the system behavior is modeled according to the changes in the parameters. Then, the Linear Parameter Varying (LPV) Model of COVID19 is derived, and its stability analysis is presented. In the end, the influence of different levels of social distancing and quarantine on the variation of severely infected and hospitalized people is studied.

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“…To overcome the disadvantages of the present approaches, this paper extends the direct searching idea which is recently developed to design robust stabilizing controllers for continuous LTI systems [20,21] to LTI discrete models. In other words, here, a design algorithm is proposed for robust SOF stabilization of discrete LTI systems in the presence of polytopic uncertainties.…”

Section: Introductionmentioning

confidence: 99%