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A stable explicit difference scheme, which is based on forward Euler format, is proposed for the Richards equation. To avoid the degeneracy of the Richards equation, we add a perturbation to the functional coefficient of the parabolic term. In addition, we introduce an extra term in the difference scheme which is used to relax the time step restriction for improving the stability condition. With the augmented terms, we prove the stability using the induction method. Numerical experiments show the validity and the accuracy of the scheme, along with its efficiency.

In order to improve the versatility of the control method of the four-rotor aircraft, a general mathematical model, the rectangular four-rotor aircraft, is modeled, and two special cases, square cross structure and square X structure, are deduced. Based on the conventional global sliding mode control, an improved global sliding mode control is proposed to control the position and the attitude of the four-rotor aircraft. The dynamic sliding mode surface of the improved global sliding mode control can evolve into the linear sliding mode surface in a limited time by changing the decay function of the dynamic sliding mode surface. In this way, the controlled system has not only the strong global robustness but also the quick response rate. Simulation results show that the position and the attitude of the four-rotor aircraft can be controlled by the improved global sliding mode control, and the control performances, for instance the response speed, can be improved.

In order to improve the physical realization of the chaotic secure communication, a chaos masking encoding method based on the synchronous control of chaotic neurons with different structure is proposed. The conventional chaotic neuron is set as the transmitting system, and the hysteretic chaotic neuron is set as the receiving system. Hysteretic parameters have creep characteristic which make the hysteretic chaotic neuron have uncertainty. Sliding mode control is used to perform the synchronous control, and fuzzy inference is used to reduce the chattering of the sliding mode control. Simulation results prove the effectiveness of the method.

A hysteretic chaotic neural network with the uncertain term is constructed, and a novel control strategy based on fuzzy sliding mode is proposed to control its dynamic behaviors without changing its structure. The control law contains fuzzy inference term which can reduce the chattering on the sliding mode. The system stability is proved by the Lyapunov theory. The hysteretic chaotic neural network based on the fuzzy sliding mode control can be used to resolve the function optimization problem without destroying chaos generation mechanism and changing the structures of the neural network, which is different to the common annealing optimization strategy. Simulation results prove that the control strategy is a valid method to control the dynamic behaviors of the neural network and resolve the function optimization problem. A hysteretic chaotic neural network with the uncertain term is constructed.A novel control strategy based on fuzzy sliding mode is proposed.Fuzzy inference term can reduce the chattering on the sliding mode.Function optimization problem is resolved by the hysteretic chaotic neural network.

Domestic waste is mainly treated by sanitary landfill. Leachate will be produced during sanitary landfill. The main characteristics of landfill leachate are high concentration of COD and BOD, high ammonia nitrogen content, high levels of refractory organics, heavy metal ions, unstable water quality and so on. With the increasing difficulty of leachate treatment, traditional manual or semi-automatic treatment methods can not meet the requirements. In order to ensure the water quality, the requirement of the leachate treatment to automation is increasing. According to the actual operation of sewage treatment plant, a set of treatment processes has been worked out. According to the characteristics and control requirements of landfill leachate processing technology, a landfill leachate processing control system is designed, which is controlled by PLC automatic control, realtime monitoring of Kingview and communication network to realize data exchange. Due to the wide range of leachate water quality changes, the traditional PID control method has poor control precision and the parameters are difficult to adjust online. Therefore, a PID control method based on adaptive control strategy has been proposed and designed. By using the nonlinear mapping ability and learning ability of neural network, the PID parameters can be adjusted online, and the final effluent quality can meet the discharge standard.