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16 pages, 1767 KiB

Open AccessFeature PaperArticle

Control of Three-Phase Two-Level Inverters: A Stochastic LPV Model Approach

by Wensheng Luo, Ruifang Zhang, Jianwen Zhang, Ligang Wu, Sergio Vazquez and Leopoldo G. Franquelo

Energies 2024, 17(23), 6142; https://doi.org/10.3390/en17236142 - 5 Dec 2024

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Abstract

This paper proposes a stochastic linear parameter-varying (LPV) model approach to design a state feedback controller for three-phase, two-level inverters. To deal with the parameter changes, stochastic noise, and delays faced by the inverter, it is modeled as a stochastic LPV system with time delay. Stability analysis and control synthesis are conducted for the LPV system. With parameter-dependent Lyapunov functionals, a condition of sufficient stability for asymptotical mean-square stability is obtained. In addition, the slack matrix technique is employed to improve the feasibility and reduce the conservatism of the conditions. The obtained theoretical results are applied to the three-phase, two-level inverter, whose currents are treated as state variables and are controlled to reach the equilibrium point. The simulation results validate the effectiveness of the proposed theories and demonstrate the advantages of using the slack matrix. Full article

(This article belongs to the Special Issue Advanced Control in Power Electronics, Drives and Generators)

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30 pages, 858 KiB

Open AccessArticle

Sliding Mode Fault-Tolerant Control for Nonlinear LPV Systems with Variable Time-Delay

by Omayma Mansouri, Ali Ben Brahim, Fayçal Ben Hmida and Anis Sellami

Math. Comput. Appl. 2024, 29(6), 96; https://doi.org/10.3390/mca29060096 - 26 Oct 2024

Cited by 1 | Viewed by 1290

Abstract

This paper presents a robust sliding mode fault-tolerant control (FTC) strategy for a class of linear parameter variant (LPV) systems with variable time-delays and uncertainties. First fault estimation (FE) is conducted using a robust sliding mode observer, synthesized to simultaneously estimate the states and actuator faults of LPV polytopic delayed systems. Second, a sliding mode FTC is developed, ensuring all states of the closed-loop system converge to the origin. This paper presents an integrated sliding mode FTC strategy to achieve optimal robustness between the observer and controller models. The integrated design approach offers several advantages over traditional separated FTC methods. Our novel approach is based on incorporating adaptive law into the design of the Lyapunov–Krasovskii functional to improve both robustness and performance. This is achieved by combining the concept of sliding mode control (SMC) with the Lyapunov–Krasovskii function under the

H_{\infty}

criteria, which plays a key role in guaranteeing the stability of this class of system. The effectiveness of the proposed method is demonstrated through a diesel engine example, which highlights the validity and benefits of the integrated and separated FTC strategy for uncertain nonlinear systems with time delays and the sliding mode control. Full article

(This article belongs to the Special Issue Applied Optimization in Automatic Control and Systems Engineering)

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18 pages, 2852 KiB

Open AccessArticle

Observer-Based State Estimation for Recurrent Neural Networks: An Output-Predicting and LPV-Based Approach

by Wanlin Wang, Jinxiong Chen and Zhenkun Huang

Math. Comput. Appl. 2023, 28(6), 104; https://doi.org/10.3390/mca28060104 - 25 Oct 2023

Cited by 2 | Viewed by 1948

Abstract

An innovative cascade predictor is presented in this study to forecast the state of recurrent neural networks (RNNs) with delayed output. This cascade predictor is a chain-structured observer, as opposed to the conventional single observer, and is made up of several sub-observers that individually estimate the state of the neurons at various periods. This new cascade predictor is more useful than the conventional single observer in predicting neural network states when the output delay is arbitrarily large but known. In contrast to examining the stability of error systems solely employing the Lyapunov–Krasovskii functional (LKF), several new global asymptotic stability standards are obtained by combining the application of the Linear Parameter Varying (LPV) approach, LKF and convex principle. Finally, a series of numerical simulations verify the efficacy of the obtained results. Full article

(This article belongs to the Collection Feature Papers in Mathematical and Computational Applications 2023)

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15 pages, 670 KiB

Open AccessArticle

Sampled-Data Linear Parameter Variable Approach for Voltage Regulation of DC–DC Buck Converter

by Kaveh Hooshmandi, Farhad Bayat and Andrzej Bartoszewicz

Electronics 2022, 11(19), 3208; https://doi.org/10.3390/electronics11193208 - 6 Oct 2022

Cited by 2 | Viewed by 1746

Abstract

This paper addresses the new method for output voltage regulation of DC–DC buck converter nonlinear systems by a sampled-data linear parameter varying (LPV) controller. For this purpose, an output-error state-space affine LPV model is presented for DC–DC buck converter nonlinear systems. The sampled-data structure of the controller is considered as a time delay in the input, and stabilization conditions are obtained for LPV systems with affine dependence on the parameter by using a parameter-dependent Lyapunov–Krasovskii functional. Then, the design condition of the sampled-data LPV controller with an appropriate sampling period is derived to guarantee that the output voltage of the DC–DC buck converter can be adjusted to the desired voltage. Finally, simulation results are provided to show the validity of the presented approach in practical control applications where there are limitations on the value of the sampling period and the cost of the digital implementation. Full article

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