Fuzzy predictive functional control of a class of non‐linear systems

Wang, Bin; Yang, Lingyu; Wu, Faqi; Chen, Diyi

doi:10.1049/iet-cta.2018.5903

Cited by 7 publications

(2 citation statements)

References 39 publications

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“…Despite the successes of fuzzy control, there are still many basic problems yet to be solved. Systematic design and stability analysis are certainly among the most important issues for fuzzy control systems [22,23]. Nevertheless, those studies have neglected the modelling errors between fuzzy models and non-linear systems under control.…”

Section: Introductionmentioning

confidence: 99%

Parallel distributed compensation scheme for chaotic masking system via Rivest cipher 4 stream cipher

Hsiao

2023

IET Control Theory & Appl

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This study presents a design methodology for Takagi-Sugeno (T-S) fuzzy models-based secure communications in multiple time-delay chaotic (MTDC) systems with Rivest cipher 4 (RC4) algorithm. The main advantage of the RC4 algorithm is that the key length does not affect the encryption and decryption speeds. To block a hacker from stealing a message, this study proposes increasing the complexity of an encrypted message (ciphertext) using a method of double encryption using the RC4 algorithm and chaotic masking. As a result, this more secure communications system can effectively defend the encrypted message (ciphertext). First, the RC4 algorithm and a key are used to encrypt the initial message (plaintext). To enhance security, the encrypted message (ciphertext) is then converted into an encrypted signal, which is a double encryption using chaotic masking. Additionally, an improved genetic algorithm (IGA) is adopted in this study, it can seek better feedback gains of fuzzy controllers to speed up the synchronization. In accordance with the IGA, a model-based fuzzy controller is synthesized to exponentially stabilize the error systems so that the trajectories of the slave systems can approach those of the master systems. Finally, a numerical example with simulations is provided to illustrate the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Parallel distributed compensation scheme for chaotic masking system via Rivest cipher 4 stream cipher

Hsiao

2023

IET Control Theory & Appl

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“…The obtained method has been developed utilising a sliding mode controller. Another new fuzzy control system for a non‐linear system has been presented in [13] which is based on predictive algorithm. In the work, according to the Takagi–Sugeno fuzzy model, a fuzzy prediction model of the system is obtained.…”

Section: Introductionmentioning

confidence: 99%

Adaptive control strategy for velocity control of a linear switched reluctance motor

Masoudi

Mehrjerdi

Ghorbani

2020

IET Electric Power Applications

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A new adaptive control strategy for a double‐sided linear switched reluctance motor is proposed in this work. Switched reluctance motors inherently have non‐linear dynamics that complicates their analysis and control. The Takagi–Sugeno fuzzy logic system has been used in this work to achieve an appropriate adaptive control system for the proposed linear motor. The fuzzy system has been heightened by non‐linear rule consequences and a time‐varying parameter. Updated laws have been designed to refresh the amount of the parameter consequently the suggested control system shows a stable performance in control of switched reluctance motors. The proposed control strategy is independent of the uncertainties of the motor dynamics and has an acceptable adaptability. This control method along with a conventional fuzzy logic based system have been studied on the proposed linear switched reluctance motor and their performances were compared in different performance conditions. An appropriate evaluation method has been used to compare the obtained results. The efficiency of the proposed method in different velocity commands has been examined and confirmed using appropriate simulation and experimental results.

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