This study aimed at the implementation and synchronization control of cardiac circuit. First, the MATLAB-Simulink was used to simulate the dynamic behavior of cardiac chaotic circuit, and simple electronic modules were used to implement the cardiac system. Then the Particle Swarm Optimization PSO was used to seek for the proportional, integral, and derivative gains of optimal PID controller, and the PID controller which could synchronize the slave cardiac circuit and the master cardiac circuit was obtained, in order to synchronize the master/slave chaotic cardiac circuits. This method can be provided for cardiac doctors to diagnose and medicate cardiac abnormality.Mathematical Problems in Engineering freeways during peak hours, the traffic stream on the freeway is the primary system, and the upstream and downstream on each interchange are the secondary system. If the primary system and the secondary system are synchronized, namely, the traffic flow and rate are controlled, there will be no traffic jam. In the sea, how to connect large ships to small ships in the fluctuant waves smoothly for oiling and transferring goods can be solved by such a concept of "synchronization." Even in the field of medicine, it can be used to adjust the heart rhythm regulator, so as to stabilize the heart beat frequency within the safety limit with the physical state to avoid heart attack. However, it is difficult to synchronize two nonlinear systems, and the selection of control mode is one of the factors. The two synchronous chaotic systems are called master system and slave system, respectively. In the generation of chaotic system, the slight difference in the initial values may result in voltage fluctuation and tremendous changes, occurring in a short or long duration, so the control mode of chaotic synchronization is the key point of this paper. Many recent studies have proposed different control modes based on chaotic synchronization. Lin et al. proposed synchronization control of time delay of complicated system dynamics based on adaptive robust observerbased approach 3 . Dismassi and Loría proposed synchronization control of the security of communication signals based on adaptive control 4 . However, all controllers require control parameters, so the search of parameters becomes another problem that must be overcome. In recent years, with the development of artificial intelligence, many studies have searched for the optimal parametric solution based on artificial intelligence. Sun et al. proposed a Neural Network based on PSO particle swarm optimization to predict and control the chaotic dynamic system for adaptive optimal control. The research result showed when the chaotic dynamic system is defined by the self-regulating function, the system could be stabilized 5 . Kao et al. proposed an adaptive dynamic neural network control to synchronize the chaotic gyros 6 . According to the previous research methods, using artificial intelligence to search for parameters and predict parameters can realize effective control and predicti...
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