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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.

This paper proposes a biomimetic method inspired by central pattern generator (CPG) for locomotion control and gait planning of a novel hexapod robot whose legs can radially free distributed around the robot body. The CPG network which consists of six CPG units based on the Matsuoka’s neural oscillator is used to generate oscillatory signals. The phase signals outputted by CPG network are converted to tip trajectory signals of six legs by adjustment function, and the joint angles are computed by the inverse kinematics of the robot. The relevant parameters which decide the movement of robot are tuned according to the processed feedback information. Then, some experiments are performed to verify the effectiveness of the control method. The experimental results indicate that the proposed method succeeds in enabling a hexapod robot to walk steadily on rugged terrain. The developed hexapod robot has many potential applications for its agility, stable walking, and good environmental adaptability.