On the development of an intelligent controller for neural networks: a type 2 fuzzy and chatter-free approach for variable-order fractional cases

Yousefpour, Amin; Yasami, Amirreza; Beigi, Alireza; Liu, Jinping

doi:10.1140/epjs/s11734-022-00612-8

Cited by 5 publications

(3 citation statements)

References 44 publications

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“…The Caputo method is used for numerical calculations. The Caputo fractional derivative is a popular choice to effectively model and analyze the dynamic behavior of various systems [47,48]. One advantage of the Caputo fractional derivative is that it provides a physically meaningful representation of the system dynamics by capturing the memory effect of the system [49].…”

Section: Arc Mems Resonatorsmentioning

confidence: 99%

A Novel Fault-Tolerant Super-Twisting Control Technique for Chaos Stabilization in Fractional-Order Arch MEMS Resonators

Alsaade

Al-zahrani

2023

Mathematics

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With the increasing demand for high-performance controllers in micro- and nano-systems, it is crucial to account for the effects of unexpected faults in control inputs during the design process. To tackle this challenge, we present a new approach that leverages an estimator-based super-twisting control technique that is capable of regulating chaos in fractional-order arch micro-electro-mechanical system (MEMS) resonators. We begin by studying the governing equation of a fractional-order arch MEMS resonator, followed by a thorough exploration of its chaotic properties. We then outline the design process for our novel control technique. The proposed technique takes into consideration the effects of uncertainty and faults in the control input by utilizing a finite time estimator and a super-twisting algorithm. The proposed technique addresses important challenges in the control of MEMS in real-world applications by providing fault tolerance, which enables the controller to withstand unexpected faults in the control input. We apply our controller to the fractional-order arch MEMS resonator, conducting numerical simulations. The numerical findings reveal that our proposed control technique is capable of stabilizing the system’s dynamics, even in the presence of a time-evolving fault in the control actuator. These results provide compelling evidence of the efficacy of our approach to control, despite the presence of an evolving fault.

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Section: Arc Mems Resonatorsmentioning

confidence: 99%

A Novel Fault-Tolerant Super-Twisting Control Technique for Chaos Stabilization in Fractional-Order Arch MEMS Resonators

Alsaade

Al-zahrani

2023

Mathematics

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“…In the current collection, robustness and stability, which are important measures in assessing the controller's performance, have been taken into account. In [27], taking advantage of a type 2 fuzzy and chatterfree approach, a new controller has been proposed to control and synchronize variable-order fractional networks. The behavior of a variable-order fractional system has been investigated, and the complex dynamics of the system have been controlled.…”

Section: Controlmentioning

confidence: 99%

Application of variable-order fractional calculus in neural networks: where do we stand?

Alotaibi

Jahanshahi

Castillo

2022

Eur. Phys. J. Spec. Top.

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After decades of evolution and advancement, artificial intelligence has profoundly affected all fields of science and engineering, and has started to revolutionize all aspects of today's life. In this regard, neural networks, which are a stepping stone in the search for artificial intelligence, play an important role. Motivated by this, the current special issue aims to explore recent trends and developments in the modeling, analysis, synchronization, and practical application of chaotic variable-order fractional neural networks.

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“…The use of state-of-the-art automatic control methods can help to improve the effectiveness and efficiency of various processes and systems, leading to better outcomes and more sustainable solutions [58][59][60][61][62][63][64][65][66][67]. Among the stated control strategies, intelligent controllers have significant advantages [68][69][70][71][72][73].…”

Section: Introductionmentioning

confidence: 99%

A New Fuzzy Reinforcement Learning Method for Effective Chemotherapy

et al. 2023

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A key challenge for drug dosing schedules is the ability to learn an optimal control policy even when there is a paucity of accurate information about the systems. Artificial intelligence has great potential for shaping a smart control policy for the dosage of drugs for any treatment. Motivated by this issue, in the present research paper a Caputo–Fabrizio fractional-order model of cancer chemotherapy treatment was elaborated and analyzed. A fix-point theorem and an iterative method were implemented to prove the existence and uniqueness of the solutions of the proposed model. Afterward, in order to control cancer through chemotherapy treatment, a fuzzy-reinforcement learning-based control method that uses the State-Action-Reward-State-Action (SARSA) algorithm was proposed. Finally, so as to assess the performance of the proposed control method, the simulations were conducted for young and elderly patients and for ten simulated patients with different parameters. Then, the results of the proposed control method were compared with Watkins’s Q-learning control method for cancer chemotherapy drug dosing. The results of the simulations demonstrate the superiority of the proposed control method in terms of mean squared error, mean variance of the error, and the mean squared of the control action—in other words, in terms of the eradication of tumor cells, keeping normal cells, and the amount of usage of the drug during chemotherapy treatment.

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On the development of an intelligent controller for neural networks: a type 2 fuzzy and chatter-free approach for variable-order fractional cases

Cited by 5 publications

References 44 publications

A Novel Fault-Tolerant Super-Twisting Control Technique for Chaos Stabilization in Fractional-Order Arch MEMS Resonators

A Novel Fault-Tolerant Super-Twisting Control Technique for Chaos Stabilization in Fractional-Order Arch MEMS Resonators

Application of variable-order fractional calculus in neural networks: where do we stand?

A New Fuzzy Reinforcement Learning Method for Effective Chemotherapy

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