Decentralized robust interval type-2 fuzzy model predictive control for Takagi–Sugeno large-scale systems

Sarbaz, Mohammad; Zamani, Iman; Manthouri, Mohammad; Ibeas, Asier

doi:10.1080/00051144.2021.2003113

Cited by 10 publications

(2 citation statements)

References 36 publications

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“…Of course, the application of interval type-2 fuzzy logic in the domain of control has recently attracted a lot of attention due to its better performance under uncertain conditions. The fundamental issue, however, is the complexity of designing and constructing interval type-2 fuzzy controllers, which contain more parameters than their type-1 counterparts; therefore, this causes greater computational complexity and overhead issues [88][89][90][91][92][93][94][95][96][97][98][99]. Therefore, several efforts were made to reduce the complexity of generalized interval type-2 fuzzy logic systems; for example, Samui and Samarjit [100] published a neural network (NN)based tuning mechanism and Cagri and Tufan [101] developed a differential flatness-based controller, which both enable computation with generalized type-2 FLS (GT2FLS).…”

Section: Number Of Output Fuzzy Membership Functionsmentioning

confidence: 99%

Real-Time Metaheuristic Algorithm for Dynamic Fuzzification, De-Fuzzification and Fuzzy Reasoning Processes

2022

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This paper presents a systematic approach to designing a dynamic metaheuristic fuzzy logic controller (FLC) to control a piece of non-linear plant. The developed controller is a multiple-input–multiple-output (MIMO) system. However, with the proposed control mechanism is possible to adapt it to single-input–single-output (SISO) systems as well. During real-time operation, the dynamic behavior of the proposed fuzzy controller is influenced by a metaheuristic particle swarm optimization (PSO) mechanism. Nevertheless, to analyze the performance of the developed dynamic metaheuristic FLC as a piece of non-linear plant, a 1 kW four-wheel independent-drive electric rover is controlled under different road constraints. The test results show that the proposed dynamic metaheuristic FLC maintains the wheel slip ratio of all four wheels to less than 0.35 and a top recorded translational speed of 90 km/h is maintained for a fixed orientation.

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Section: Number Of Output Fuzzy Membership Functionsmentioning

confidence: 99%

Real-Time Metaheuristic Algorithm for Dynamic Fuzzification, De-Fuzzification and Fuzzy Reasoning Processes

2022

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“…Moreover, the decentralized approach considers more than one agent in the decision‐making environment, where one agent's decision can be affected by others and vice versa (Jokar et al., 2023). This approach brings more features with realistic characteristics to the analysis, although it adds to the complexity of the problem.…”

Section: Introductionmentioning

confidence: 99%

Game‐theoretic algorithm for interdependent infrastructure network restoration in a decentralized environment

Rangrazjeddi,

González,

Barker

2024

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Having reliable interdependent infrastructure networks is vital for well‐being of a safe and productive society. Systems are vulnerable to failure or performance loss due to their interdependence among various networks, as each failure can propagate through the whole system. Although the conventional view has concentrated on optimizing the restoration of critical interdependent infrastructure networks using a centralized approach, having a lone actor as a decision‐maker in the system is substantially different from the actual restoration decision environment, wherein infrastructure utilities make their own decisions about how to restore their network service. In a decentralized environment, the definition of whole system optimality does not apply as each decision‐maker's interest may not converge with the others. Subsequently, this results in each decision‐maker developing its own reward functions. Therefore, in this study, we address the concern of having multiple decision‐makers with various payoff functions in interdependent networks by proposing a decentralized game theory algorithm for finding Nash equilibria solutions for network restoration in postdisaster situations.

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A robust estimation and compensation-based fault-tolerant control for large-scale interconnected systems with actuator saturation

Abdul-Jaleel

Shaker

2022

Int. J. Dynam. Control

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Decentralized robust interval type-2 fuzzy model predictive control for Takagi–Sugeno large-scale systems

Cited by 10 publications

References 36 publications

Real-Time Metaheuristic Algorithm for Dynamic Fuzzification, De-Fuzzification and Fuzzy Reasoning Processes

Real-Time Metaheuristic Algorithm for Dynamic Fuzzification, De-Fuzzification and Fuzzy Reasoning Processes

Game‐theoretic algorithm for interdependent infrastructure network restoration in a decentralized environment

A robust estimation and compensation-based fault-tolerant control for large-scale interconnected systems with actuator saturation

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