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In this paper, a fault detection method based on chaos is proposed for doubly-fed induction generator (DFIG). Firstly, the nonlinear differential equation of the DFIG is established by the stator flux-oriented vector control method, and then the motion state of the DFIG is proved by the 0-1 test algorithm. Secondly, the motion state of the DFIG is analyzed under normal and fault conditions. Due to some failures that may occur in the normal operation of the DFIG, the motion state of the DFIG system may enter chaos from the cycle, which is mainly manifested by the violent oscillation of the rotor current and speed. At this time, the system is in an extremely unstable operating condition. Thereby, a new sliding mode control rate is mentioned to suppress chaotic behavior. Its stability is analyzed by constructing the Lyapunov function to ensure that the system state can quickly and stably converge to the given value. After that, the simulation model of the system is built. The simulation results show that sliding mode control can make the DFIG get out of the chaotic state quickly. And, the sliding mode control has the characteristics of fast fault elimination and high control accuracy. In addition, the traditional sliding mode approach rate is compared with the proposed new sliding mode approach rate. It proves that the proposed new approach rate can achieve better control effect.

Buck converter is a kind of converter device with high efficiency, wide adjustable output voltage, small loss, small size and light weight. Its circuit has nonlinearity and will exhibit abundant nonlinear phenomena with the change of circuit parameters, resulting in unstable output voltage and being susceptible to load and external disturbances. Therefore, a control method based on Extreme Learning Machine (ELM) combined with a proportionalintegral-derivative (PID) controller is proposed in this paper and used for output voltage control of buck converter. Firstly, the mathematical model of buck converter in Continuous Conduction Mode (CCM) is established by the state space averaging method. Then the PID tuning algorithm is designed in combination with ELM, and the stability analysis of the model is carried out. Finally, the simulation experiment is carried out under different disturbances. By comparing with the open-loop control strategy, the effectiveness of the proposed ELM-PID control strategy is verified, indicating that the proposed method can achieve the stability of output voltage and good dynamic response.

In this paper, a five-dimensional hyperchaotic system for secure communication based on MCU is proposed. First, a five-dimensional hyperchaotic system is constructed and the features such as equilibrium stability and Lyapunov exponents are analyzed. The states of this system with different parameters are studied, including periodic, hyperchaotic and chaotic state. Next, the complexity of system is analyzed. By analyzing the complexity of each dimension, the correctness of system selection is verified and the dimension with the highest complexity is selected for communication encryption. Then, the hardware circuit is designed. The encryption and decryption of square wave signal are completed through simulation which realizing the secure communication. Finally, the accuracy of system and the algorithm of realizing chaos of MCU are adjusted, and the system after adjustment is in a chaotic state verified by 0–1 test, the chaos is successfully generated by MCU. Using MCU can reduce the hardware cost of signal encryption greatly, and apply five-dimensional hyperchaotic system to secure communication can not only improve the security but also enhance the anti-interference ability in the process of signal transmission.

Compared with the static cipher, the dynamic cipher has the characteristic of "one cipher at a time" proposed by Shannon theory. Therefore, it is regarded as the safest among many forms of identity authentication. This paper proposes a five-dimensional chaotic system suitable for the construction of dynamic cipher and analyzes its relevant characteristics, including stability, balance, time-domain waveform, Poincare cross sectional diagram, Lyapunov exponent and bifurcation diagram. The results show that the chaotic system has multiple controllable parameters and a wide range of chaos, which is very suitable for constructing chaotic dynamic ciphers. The complexity of the proposed chaotic system is analyzed to verify the high security of the proposed system. On this basis, a dynamic cipher electronic lock based on chaotic system is designed in this paper. In the designed hardware circuit, the fourth order Runge–Kutta solving algorithm is used to discretize the constructed system, and the chaos is successfully implemented in the single-chip microcomputer. The phase diagram obtained from the circuit simulation data is basically consistent with the numerical simulation. Finally, the circuits of the handheld terminal and the electronic lock terminal are designed and simulated. The simulation results show that the preset function can be basically realized, and the generated chaotic dynamic cipher is random and irregular. The five-dimensional chaotic system proposed in this paper has complex dynamic characteristics, which makes the dynamic cipher electronic lock based on the chaotic system extremely safe.

To detect the fault of the doubly-fed induction generator (DFIG), in this paper, a fault detection method of novel sliding mode observer is proposed, without a velocity sensor. In addition to better elimination of chattering for the new sliding mode observer, at the same time, it has better stability and faster convergence speed than the traditional sliding mode observer. Firstly, the sliding mode observer is built according to the mathematical model of the DFIG. Then, the rotor current and the rotational speed are estimated. After comparing the actual rotor current value with the observed value, the self-detection of the fault for the DFIG is realized. Secondly, three faults of grid voltage sags failure, DFIG inter-turn stator fault and rotor current sensor fault are given respectively. After that the Simulink simulation model is built under different fault conditions. It is proved by simulation that this sliding mode observer can well detect faults occurring at different positions. Additionally, it can also be proved that the sliding mode observer has the characteristics of fast response and good stability.

This paper proposes a novel seven-dimensional fractional-order chaotic system applied to secure communication. First, a seven-dimensional fractional order system is constructed by selecting an arbitrary fractional order q. Then, the chaotic and non-chaotic dynamic behaviors of the system are analyzed by 0–1 Test, and the correctness is verified by phase diagram comparison and complexity analysis. Then, the corresponding fractional-order chaotic circuit is designed, and the phase image which is basically consistent with the experimental simulation results is obtained. Finally, the seven-dimensional fractional-order chaotic system is used to complete the signal encryption and decryption test to achieve secure communication. This indicates that the seven-dimensional fractional-order chaotic system proposed to this paper has more complex dynamic characteristics and can be used for secure communication.

With the continuous expansion of the scale of wind turbine system, wind power production, operation and equipment control of wind turbine have become more and more significant. To improve the reliability of wind turbine systems fault diagnosis, combining with data-driven technology, this paper proposes a multi-fault diagnosis method for wind power system based on recurrent neural network. According to the actual wind speed data, the normal operation and fault data of the wind turbine system are obtained by system modeling, and the classification and prediction model based on the recurrent neural network algorithm is established, which takes 30 characteristic parameters such as wind speed, rotor speed, generator speed and power generation as input, and 10 different types faults labels of the wind turbine as output. Specific rules formed inside the sample data of the wind turbine system are learned intelligently by the model which is continuously trained, optimized and tested to verify the feasibility of the algorithm. The results of evaluation standards such as accuracy rate, missed detection rate and F1-measure that compared with other related algorithms such as deep belief network show that the proposed algorithm can solve the problem of multi-classification fault diagnosis for wind power generation system efficiently.

Permanent magnet synchronous linear motor (PMSLM) is a linear motion device, which has the characteristics of simple structure, low loss, high precision, repeatability, large stroke, and simple maintenance. Simultaneously, due to its feature of non-linearity, time-varying, strong coupling, and external load uncertainty, a speed disturbance control method base on sliding mode control of PMSLM is proposed in this paper. The method of sliding mode control uses the power function to smooth the processing. It replaces the symbolic function based on the exponential approach method; therefore, the buffeting of the conventional sliding mode can be well suppressed by this method. When considering different disturbances, the simulation proves that the sliding mode control system can overcome the influence of system parameter changes and external disturbances. Therefore, the control of the PMSLM can be achieved. Meanwhile, the simulation results show that the proposed new sliding mode approach rate can better suppress chattering compared with the traditional approach rate. Additionally, the stability of the system and anti-interference is improved.

In the fields of physics, mathematics, communication, control, biology, etc., chaos is widely used, and it plays an important role in modern science and technology. In this paper, a new seven-dimensional hyperchaotic system is proposed and some related features of the hyperchaotic system are analyzed, including equilibrium stability, dissipation, bifurcation and Lyapunov exponent. The results show that the proposed hyperchaotic system exhibits hyperchaotic, chaotic, quasi-periodic and periodic dynamic behaviors. The seven-dimensional hyperchaotic system is implemented through experiments, and the phase diagrams of the circuit simulation are consistent with those of the numerical simulation, which verifies the physical realization of the hyperchaotic system. In view of chaos in some important fields, such as communication security and complex systems, the seven-dimensional hyperchaotic system is applied to signal encryption and decryption circuit design. Firstly, the proposed seven-dimensional hyperchaotic system is scaled and transformed into a hyperchaotic system that is easy to implement. Then an improved chaotic circuit module design is adopted. Finally, the seven-dimensional hyperchaotic circuit is designed to form a hyperchaotic secure communication circuit. The electronic circuit realizes the confidential communication and its experimental results prove the effectiveness of the designed scheme.

In the traction system of high-speed EMUs, the inverter’s Insulated Gate Bipolar Transistor (IGBT) often occurs open-circuit (OC) faults. However, traditional fault diagnosis relies mainly on signal processing to extract fault features, which is susceptible to environmental interference, resulting in poor generalization ability of the model. Aiming at this problem, a fault diagnosis method based on an improved convolutional neural network is proposed. Firstly, the three-phase stator current signal is preprocessed by wavelet domain denoising. Secondly, fault features are independently learned through a convolutional network. Finally, a fully-connected layer is used for fault diagnosis. The experimental results show that this method could resolve the OC fault diagnosis problem of the inverter’s IGBT effectively, and also achieve higher accuracy under the interference of noise, and the diagnosis can be made at 0.01s after the fault occurs.

In this paper, we introduce a novel iterative method for finding a series of fixed point and design a steady controllability approach for nonlinear systems by using Firefly algorithm and ELM. First, we construct a fixed-point search model, but it is just only looking for a fixed point. Because of the need of non-linear dynamic systems, we need to find a series of fixed point under certain circumstances. Then, we apply the Firefly Algorithm and ELM to design a steady controllability approach. Finally, we have an example to verify the method we have proposed. Through the method, we get a series of fixed point, which make dynamic Nonlinear Systems or nonlinear circuit is under a relatively stable state.