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Robust Design of Two-Level Non-Integer SMC Based on Deep Soft Actor-Critic for Synchronization of Chaotic Fractional Order Memristive Neural Networks
by
Haghighi, Ahmad Reza
, Basse-O’Connor, Andreas
, Roohi, Majid
, Mirzajani, Saeed
in
Adaptability
/ Algorithms
/ Artificial neural networks
/ Chaos theory
/ Control systems
/ Control theory
/ deep neural network of SAC agent
/ delayed FO memristive neural networks
/ Design
/ finite-time synchronization
/ Lyapunov stability theorem
/ Machine learning
/ Methods
/ Neural networks
/ Optimization
/ PIφ-SMC
/ Robust control
/ Robust design
/ Signal processing
/ Simulation methods
/ Sliding mode control
/ Surface stability
/ Systems stability
/ Time synchronization
2024
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Robust Design of Two-Level Non-Integer SMC Based on Deep Soft Actor-Critic for Synchronization of Chaotic Fractional Order Memristive Neural Networks
by
Haghighi, Ahmad Reza
, Basse-O’Connor, Andreas
, Roohi, Majid
, Mirzajani, Saeed
in
Adaptability
/ Algorithms
/ Artificial neural networks
/ Chaos theory
/ Control systems
/ Control theory
/ deep neural network of SAC agent
/ delayed FO memristive neural networks
/ Design
/ finite-time synchronization
/ Lyapunov stability theorem
/ Machine learning
/ Methods
/ Neural networks
/ Optimization
/ PIφ-SMC
/ Robust control
/ Robust design
/ Signal processing
/ Simulation methods
/ Sliding mode control
/ Surface stability
/ Systems stability
/ Time synchronization
2024
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Robust Design of Two-Level Non-Integer SMC Based on Deep Soft Actor-Critic for Synchronization of Chaotic Fractional Order Memristive Neural Networks
by
Haghighi, Ahmad Reza
, Basse-O’Connor, Andreas
, Roohi, Majid
, Mirzajani, Saeed
in
Adaptability
/ Algorithms
/ Artificial neural networks
/ Chaos theory
/ Control systems
/ Control theory
/ deep neural network of SAC agent
/ delayed FO memristive neural networks
/ Design
/ finite-time synchronization
/ Lyapunov stability theorem
/ Machine learning
/ Methods
/ Neural networks
/ Optimization
/ PIφ-SMC
/ Robust control
/ Robust design
/ Signal processing
/ Simulation methods
/ Sliding mode control
/ Surface stability
/ Systems stability
/ Time synchronization
2024
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Robust Design of Two-Level Non-Integer SMC Based on Deep Soft Actor-Critic for Synchronization of Chaotic Fractional Order Memristive Neural Networks
Journal Article
Robust Design of Two-Level Non-Integer SMC Based on Deep Soft Actor-Critic for Synchronization of Chaotic Fractional Order Memristive Neural Networks
2024
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Overview
In this study, a model-free PIφ-sliding mode control ( PIφ-SMC) methodology is proposed to synchronize a specific class of chaotic fractional-order memristive neural network systems (FOMNNSs) with delays and input saturation. The fractional-order Lyapunov stability theory is used to design a two-level PIφ-SMC which can effectively manage the inherent chaotic behavior of delayed FOMNNSs and achieve finite-time synchronization. At the outset, an initial sliding surface is introduced. Subsequently, a robust PIφ-sliding surface is designed as a second sliding surface, based on proportional–integral (PI) rules. The finite-time asymptotic stability of both surfaces is demonstrated. The final step involves the design of a dynamic-free control law that is robust against system uncertainties, input saturations, and delays. The independence of control rules from the functions of the system is accomplished through the application of the norm-boundedness property inherent in chaotic system states. The soft actor-critic (SAC) algorithm based deep Q-Learning is utilized to optimally adjust the coefficients embedded in the two-level PIφ-SMC controller’s structure. By maximizing a reward signal, the optimal policy is found by the deep neural network of the SAC agent. This approach ensures that the sliding motion meets the reachability condition within a finite time. The validity of the proposed protocol is subsequently demonstrated through extensive simulation results and two numerical examples.
Publisher
MDPI AG
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