Robust multimodel control applied on hydraulic turbine model

Osuský, Jakub; Hypiusova, Maria; Puleva, Teofana

doi:10.1109/cyberi.2016.7438603

Cited by 5 publications

(4 citation statements)

References 7 publications

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“…Step 5: Calculate the intersection points of the real axis and Nyquist plot using (22) for all critical frequencies, and then find gain intervals with the help of the generalized Nyquist theorem (23).…”

Section: Step-by-step Design Algorithmmentioning

confidence: 99%

“…After that, for each ω * ij , the intersection points of the Nyquist curve and real axis are calculated via (22).…”

Section: Example 1 (Interval Case)mentioning

confidence: 99%

“…In Gayvoronskiy et al [21], interval type polynomials are considered; however, the synthesized controller structure is different than a PID controller. On the other hand, affine‐linear polynomials are considered [22]. However, the vertex results are used during the controller design, and the robustness is guaranteed by checking the corresponding edge polynomials.…”

Section: Introductionmentioning

confidence: 99%

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Robust PID controller design via dominant pole assignment for systems with parametric uncertainties

Dincel

Söylemez

2020

Asian Journal of Control

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In this paper, a novel robust PID controller design technique is proposed for the parametric uncertain systems via the dominant pole assignment approach. In the closed‐loop, it is aimed that two poles are placed in the desired (dominant) region, and it is guaranteed that the remaining (unassigned) poles are located far away from the dominant pole region under all possible perturbations. The robust PID controller design technique is firstly given for the interval type characteristic polynomials with the help of vertex results. After that, the proposed method is generalized to cover the affine‐linear type characteristic polynomials. The method is based on the well‐known robust stability theorems and the generalized Nyquist theorem. The success of the proposed design technique is demonstrated on the control systems through simulation studies for both the interval and affine‐linear cases and compared with the other robust PID controllers from the literature. It is shown that the proposed robust PID controllers guarantee the desired pole configuration in the closed‐loop, and the closed‐loop performance specifications are satisfied even in the worst case.

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Section: Step-by-step Design Algorithmmentioning

confidence: 99%

“…After that, for each ω * ij , the intersection points of the Nyquist curve and real axis are calculated via (22).…”

Section: Example 1 (Interval Case)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust PID controller design via dominant pole assignment for systems with parametric uncertainties

Dincel

Söylemez

2020

Asian Journal of Control

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“…To improve the control quality, advanced controllers have been designed such as sliding mode control [8], predictive control [9] and robust control [10] Although the development of advanced control schemes has seen great progress in the past few decades, the classical proportional-integralderivative (PID)type controller is a preferred choice for the PSHP owing to its reliability, real-time computing ability, and easy implementation. Parameter optimization of the PID-type controller has proven effective for improving the control quality especially under some unfavorable conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

Controller Optimization Approach Using LSTM-Based Identification Model for Pumped-Storage Units

Feng

et al. 2019

IEEE Access

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In this paper, the controller optimization problem of the pumped-storage unit (PSU) was examined. The objectives of this paper were to identify the dynamic model of the PSU according to the deep learning model through training of the input-output data and to optimize the parameters of the controller on the basis of this identified model. To achieve the objectives, a novel pump-turbine model based on the B-spline surface was employed to precisely simulate the PSU for data measurement and identification. Next, the long short-term memory (LSTM) network architecture was applied to identify the dynamic model of the PSU. Then, gain tuning of the proportional-integral-derivative (PID) controller was conducted by applying particle swarm optimization on the basis of the identified model. To verify the effectiveness of the proposed method, a simulation platform based on the pumped-storage hydropower plant in China was chosen as the experimental object, and the comparative experiments were conducted. The results show the following: 1) the LSTM model performed better compared with the autoregressive model with exogenous variables, support vector machine, and feedforward neural network inaccuracy; 2) the PID controller tuned with the identified LSTM model has excellent control ability compared with the other identified models, and; 3) the identified LSTM model and optimized controller have very good robustness under different conditions.INDEX TERMS Pumpedstorage unit, pump-turbine governing system, surface model of pumpturbine optimization via LSTM-based identification.

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Fractional Order CRONE and PID Controllers Design for Nonlinear Systems Based on Multimodel Approach

Wardi

Abdelkrim

2021

Fractional Order Systems—Control Theory and Applications

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Robust multimodel control applied on hydraulic turbine model

Cited by 5 publications

References 7 publications

Robust PID controller design via dominant pole assignment for systems with parametric uncertainties

Robust PID controller design via dominant pole assignment for systems with parametric uncertainties

Controller Optimization Approach Using LSTM-Based Identification Model for Pumped-Storage Units

Fractional Order CRONE and PID Controllers Design for Nonlinear Systems Based on Multimodel Approach

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