A simplify fuzzy logic controller design based safe experimentation dynamics for pantograph-catenary system

Farhan, Mohd Said; Shukor, Nor Sakinah Abdul; Ahmad, Mohd Ashraf; Suid, Mohd Helmi; Ghazali, Mohd Riduwan; Jusof, Mohd Falfazli Mat

doi:10.11591/ijeecs.v14.i2.pp903-911

Cited by 19 publications

(4 citation statements)

References 8 publications

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“…Each player moves in a random motion that is decided based on a predetermined probability. Since its first debut, SEDA has been utilized as a tool to cater to various engineering applications such as flexible joint robots [52], pantograph-catenary systems [53], underactuated container cranes [54], and DC/DC buck-boost converter-inverter-DC motors [55]. In the domain of a single agent, systematic studies have shown that SEDA has solid performance and is very simple to implement, with a safe updating mechanism.…”

Section: Hybridization Of Mpa and Sedamentioning

confidence: 99%

An Improved Marine Predators Algorithm-Tuned Fractional-Order PID Controller for Automatic Voltage Regulator System

et al. 2023

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One of the most popular controllers for the automatic voltage regulator (AVR) in maintaining the voltage level of a synchronous generator is the fractional-order proportional–integral-derivative (FOPID) controller. Unfortunately, tuning the FOPID controller is challenging since there are five gains compared to the three gains of a conventional proportional–integral–derivative (PID) controller. Therefore, this research work presents a variant of the marine predators algorithm (MPA) for tuning the FOPID controller of the AVR system. Here, two modifications are applied to the existing MPA: the hybridization between MPA and the safe experimentation dynamics algorithm (SEDA) in the updating mechanism to solve the local optima issue, and the introduction of a tunable step size adaptive coefficient (CF) to improve the searching capability. The effectiveness of the proposed method in tuning the FOPID controller of the AVR system was assessed in terms of the convergence curve of the objective function, the statistical analysis of the objective function, Wilcoxon’s rank test, the step response analysis, stability analyses, and robustness analyses where the AVR system was subjected to noise, disturbance, and parameter uncertainties. We have shown that our proposed controller has improved the AVR system’s transient response and also produced about two times better results for objective function compared with other recent metaheuristic optimization-tuned FOPID controllers.

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Section: Hybridization Of Mpa and Sedamentioning

confidence: 99%

An Improved Marine Predators Algorithm-Tuned Fractional-Order PID Controller for Automatic Voltage Regulator System

et al. 2023

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“…This manuscript proposes a model-free single-dimension fuzzy-based sliding mode control (SDF-SMC) design. The technique of single-dimension fuzzy-based sliding mode control has been proposed previously without model-free approach for several applications such as deep submergence rescue vehicle (DSRV) [41], double pendulum-type overhead crane [42] and NPS AUV II [43] for Pantograph-Cateary system [44] and for underactuated quadrotor craft [45]. This algorithm produced many methods, such as fast convergence rate, prompt execution time response, less chattering effect and less control input energy (CIE).…”

Section: Literature Reviewmentioning

confidence: 99%

Model-Free-Based Single-Dimension Fuzzy SMC Design for Underactuated Quadrotor UAV

et al. 2021

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The underactuated quadrotor unmanned aerial vehicle (UAV) is one of the nonlinear systems that have few actuators as compared to the degree of freedom (DOF); thus, it is a strenuous task to stabilize its attitude and positions. Moreover, an induction of unmodelled dynamic factors and uncertainties make it more difficult to control its maneuverability. In this paper, a model-free based single-dimension fuzzy sliding mode control (MFSDF-SMC) is proposed to control the attitude and positions of underactuated quadrotor UAV. The paper discusses the kinematic and dynamic models with unmodelled dynamic factors and unknown external disturbances. These unmodelled factors and disturbances may lead the quadrotor towards failure in tracking specific trajectory and may also generate some serious transient and steady-state issues. Furthermore, to avoid the problem of gimbal lock, the model is amalgamated with hyperbolic function to resolve the singularity issues dully developed due to Newton Euler’s dynamic modeling. The simulation results performed for MFSDF-SMC using MATLAB software R2020a are compared with conventional sliding mode control, fuzzy-based sliding control and single-dimension fuzzy-based sliding mode control without a model-free approach. The design and implementation of the model-free single dimension-based fuzzy sliding mode control (MFSDF-SMC) with an updated Lyapunov stability theorem is presented in this work. It is observed that MFSDF-SMC produces robust trajectory performance therefore, and the manuscript suggests the experimental setup to test the proposed algorithm in a noisy environment keeping the same conditions. The verification of the equipment used and its effective demonstration is also available for the reader within the manuscript.

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“…This paper discusses the integrated application of synergetic approach to improve the quality of intelligent steam generator control system. This approach combines various aspects and techniques including model-based control, adaptive control and artificial intelligence to create an efficient and flexible steam generator control system [3]- [5]. Model-based control provides a mathematical model of the steam generator, which is used to develop control algorithms and predict its behavior.…”

Section: Introductionmentioning

confidence: 99%

Integrated application of synergetic approach for enhancing intelligent steam generator control systems

Isamiddin,

Dilnoza

2024

IJECE

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This article focuses on the integrated application of the synergetic approach to enhance the quality of intelligent steam generator control systems.By combining various techniques such as model-based control, adaptive control, and artificial intelligence, an efficient and flexible control system can be developed. Model-based control utilizes mathematical models of steam generators to formulate control algorithms and predict system behavior. Adaptive control enables the system to adapt to changing conditions by adjusting control parameters based on real-time measurements. Artificial intelligence techniques, including neural networks and genetic algorithms, facilitate learning, optimization, and data-driven decision-making processes. The objectives of this research are to investigate the benefits of the synergetic approach in steam generator control, including improved steam generation efficiency, optimized energy consumption, enhanced system stability and reliability, and adaptability to varying operating conditions and disturbances. The findings and conclusions of this study are expected to provide valuable insights for engineers, researchers, and professionals involved in the design and implementation of intelligent steam generator control systems. By integrating the synergetic approach, substantial enhancements in control quality can be achieved, leading to optimal operation and maximum efficiency of power plants.

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A simplify fuzzy logic controller design based safe experimentation dynamics for pantograph-catenary system

Cited by 19 publications

References 8 publications

An Improved Marine Predators Algorithm-Tuned Fractional-Order PID Controller for Automatic Voltage Regulator System

An Improved Marine Predators Algorithm-Tuned Fractional-Order PID Controller for Automatic Voltage Regulator System

Model-Free-Based Single-Dimension Fuzzy SMC Design for Underactuated Quadrotor UAV

Integrated application of synergetic approach for enhancing intelligent steam generator control systems

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