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The removal of perfluorooctanoate （PFOA） and turbidity from model solution by coagulation was investigated. A polyaluminum chloride (PACl) was used as a coagulant in the coagulation process. The effects of coagulant dose, slow mixing time, solution pH value and initial turbidity on the removal of both PFOA and turbidity from water were studied. It was found that the removal rate of PFOA in water increase along with the increase in slow mixing time, initial turbidity and PAC dose. The removal rate of PFOA is more effective at the near neutral solution pH values and the high initial turbidity. The removal percents of PFOA exceed 80% at the optimal condition. The removal mechanism was speculated to be the electrostatic interaction and hydrophobic interaction in coagulation process.

As the perfect fusion of intelligent robotics and China's classic culture, Opera robots, two omni-directional wheeled robots were made in my research centre. They can smoothly fight with each other just as Opera actors. A novel trajectory tracking method based on robotic dynamics model and wavelet sampling theorem for Opera robot is proposed in this paper. The formula for calculating torque of each driving motor when the robot moves along spline curves is studied in detail. By experiment, the robot can be derived smoothly to track predetermined trajectory.

For the probability neural network (PNN) algorithm is the non-surveillance's pattern taxonomic approach, the work load major problem, moreover the category number's selection will affect the cluster performance. How to optimize PNN enabled it to play a more effective role in the classified question, this paper proposed one use genetic algorithm optimization probability neural network method: introduction the auto-adapted mechanism genetic algorithm, to the probability neural network's parameter carries on the training, formed the supervised learning probability neural network based on the genetic algorithm, overcome the probability neural network existing algorithm flaw. Then introduces this model in the quality control, guaranteed that the production process is at the control state, achieves the quality control goal. Carries on the test through the simulation experiment to this algorithm, and with the probability neural network, the BP neural network carries on the comparative analysis, proved this method accuracy is high.