CHAOS SYNCHRONIZATION USING SUPER-TWISTING SLIDING MODE CONTROL APPLIED ON CHUA’S CIRCUIT

Chua’s circuit is the classic chaotic system and the most widely used in serval areas due to its potential for secure communication. However, developing an accurate chaos control strategy is one of the most challenging works for Chua’s circuit. This study proposes a new application of super twisting algorithm (STC) based on sliding mode control (SMC) to eliminate or synchronize the chaos behavior in the circuit. Therefore, the proposed control strategy is robust against uncertainty and effectively regulates the system with a good regulation tracking task. Using the Lyapunov stability, the property of asymptotical stability is verified. The whole of the system including the (control strategy, and Chua’s circuit) is implemented under a suitable test setup based on dSpace1104 to validate the effectiveness of our proposed control scheme. The experimental results show that the proposed control method can effectively eliminate or synchronize the chaos in the Chua's circuit

Neural Adaptive Kalman Filter for Sensorless Vector Control of Induction Motor

This paper presents a novel neural adaptive Kalman filter for speed sensorless field oriented vector control of induction motor. The adaptive observer proposed here is based on MRAS (model reference adaptive system) technique, where the linear Kalman filter calculate the stationary components of stator current and the rotor flux and the rotor speed  is calculated with an adaptive mechanism. Moreover, to improve the performance of the PI classical controller under different conditions, a novel adaptation scheme based on ADALINE (ADAptive LInear NEuron) neural network is used. It offers a solution to the PI parameters to stabilize automatically about their optimum values and speed estimation to converge quicker to the real. The proposed adaptive Kalman filter represents a good comprise between estimation accuracy and computationally intensive. The simulation results showed the robustness, efficiency, and superiority of the proposed scheme compared to the classical method even in low speed region

Finite-time integral sliding mode control for chaotic permanent magnet synchronous motor systems

In this paper, an integral finite-time sliding mode control scheme is presented for controlling a chaotic permanent magnet synchronous motor (PMSM). The controller can stabilize the system output tracking error to zero in a finite time. Using Lyapunov’s stability theory, the stability of the proposed scheme is verified. Numerical simulation results are presented to present the effectiveness of the proposed approach

A New Quasi Open Loop Synchronization Technique for Grid-Connected Applications

– This paper presents an effective quasi open-loop (Q-OLS) synchronization technique for grid-connected power converters and which is organized in two different blocks. The first block is a new flexible technique for extracting the positive and negative sequence voltage under unbalanced and distorted conditions. It is a decoupled double self-tuning filter (DD-STF) or multiple self-tuning filters (M-STF) according to the conditions. The main advantages of this technique are its simple structure and the fact of been able to work under highly distorted conditions. Each harmonic is separately treated and this allows selective compensation in active filter applications. The second block is the frequency detector; we propose a neural approach based on an ADALINE for online adaptation of the cutoff frequency of the DD-STF and M-STF considering a possible variation in the main frequency. The main advantage of this method is its immunity to the voltage signal amplitude and phase. In order to improve the performance of the frequency estimation under distorted source voltage a pre filtering stage is introduced. Experimental tests validate the proposed method and illustrate all its interesting features. Results show high performance and robustness of the method under low voltage ride through

A New Quasi Open Loop Synchronization Technique for Grid-Connected Applications

This paper presents an effective quasi open-loop (QOLS) synchronization technique for grid -connected power converters that is organized in two different blocks. The first block is a new flexible technique for extracting the positive and negative sequence voltage under unbalanced and distorted conditions. It is a decoupled double self-tuning filter (DD-STF) or multiple self-tuning filters (M-STF) according to the conditions. The main advantages of this technique are its simple structure and the fact of being able to work under highly distorted conditions. Each harmonic is separately treated and this allows for selective compensation in active filter applications. The second block is the frequency detector; we propose a neural approach based on an ADALINE for online adaptation of the cut-off frequency of the DD-STF and M-STF considering a possible variation in the main frequency. The main advantage of this method is its immunity to the voltage signal amplitude and phase. In order to improve the performance of the frequency estimation under distorted source voltage, a pre-filtering stage is introduced. Experimental tests validate the proposed method and illustrate all its interesting features. Results show high performance and robustness of the method under low voltage ride through