Chao-Ying Liu

Application research of information fusion technology of multi-sensor in level measurement

According to the velocity of sound calibration and the nonlinear rectification in the ultrasonic level meter, a new information fusion algorithm based on neural network is presented. An improved BP algorithm -LM algorithm is used to train the neural network, which can improve the datas convergent speed. The simulation result shows that the effect of the temperature to the sound velocity would be fused in the level measurement while realizing non-linear compensation of temperature, so the level can be measured accurately.

Mathematical model of thermocouple characteristic based on neural network

The nonlinear compensation in the intelligent thermometer measurement instrumentation is introduced, and disadvantages of the compensation in hardware or software are discussed. The BP neural network method for the nonlinear compensation and its merits are proposed. The number of the hidden layer nodes and the improved algorithm are analyzed deeply, and the modeling process is presented in this paper. The example demonstrates that a more precise mathematical model of the thermocouple can be obtained based on the improved BP algorithm, which can be implemented by software, is beneficial to improve the instrument accuracy.

Control System Design of Heat Exchange Station Based on Fuzzy Technology

The heating supply system is a system with very large thermal inertia and the adjustment of the system can not be too frequence, so this paper presents averaging control strategy and discusses the temperature control deeply based on fuzzy control technology. From application effect it can be seen that the control method can guarantee the quality of heating and at the same time reduce the requirement of energy resource

Investigation on application of fuzzy decoupling control into penicillin crystallization process

On the basis of analyzing the relationships between inputs and outputs in penicillin crystallization process, a fuzzy decoupling control scheme has been applied into the process. The results of simulation showed that comparing with conventional decoupling controller, this control method with fuzzy decoupling not only had better dynamic and static property, stronger robustness, but it was also a simple and effective method to improve the property of conventional decoupling controller.

The design and analysis on a new type of fuzzy controller

Based on analyzing the effect of the scaling factors of a fuzzy controller on system performance, the paper proposes a new type of fuzzy controller with nonlinear scaling functions and discusses its effect on membership functions, equivalent mapping between input and output parameter, nonlinear surface for the controller and system performance in detail. Besides the parts mentioned above, the paper also studies the relationship of the parameters in nonlinear scaling functions and system performance. The parameter design of the fuzzy controller with nonlinear scaling functions is simple and normalization is also easy for online learning and adjustment in an adaptive fuzzy controller. Simulation result shows that compared with a conventional fuzzy controller, this controller with nonlinear scaling function has better dynamic and static properties, and it is a simple, useful and effective method for improving the fuzzy controller properties.

Research on predictive control of coagulant dosage based on neural network

By analyzing the characters of coagulant dose process and factors related to coagulation, a predictive model of optimal coagulant dosage based on neural network is proposed in this paper. Historical data were used to simulate, the results show that this model is better than the traditional regression model. At last, an effective predictive control strategy of coagulant dosage is put forward based on this model, which offers an effective way for achieve the optimal coagulant dosing.

Optimizing Parameters of Fuzzy Controller Based on Genetic Algorithm

For effects of the parameters of fuzzy controller with nonlinear scaling factors on a systems performance and the parameters are interactive, this paper proposes a method based on genetic algorithm (GA) to tune and optimize the parameters. Simulation results show that system which adopted the parameters derived from the method has better dynamics and static property. When the parameters or structure of plant is changed, a fuzzy controller with nonlinear scaling factors can maintain good performance indicators through re-tuning parameters and has stronger robustness.

Robust PID control for steam superheater

The main steam system of boiler is typical time delay process. The steam temperature of superheater is an important parameter that must be kept in a certainty range when the unit plant is running. According to the characteristic of the process, the paper introduces a new type of robust PID controller that can assure stability when parameter and time delay are mismatched with the controller. Simulation result shows that the control effect is very well.

A realization method for fuzzy decoupling control of the Circulating Fluidized Bed Boiler

Since the combustion system of the Circulating Fluidized Bed Boiler (CFBB) is a complex object characterized by multiple variables, long time-delay, tight coupling, and time-varying. This paper introduces a new method of fuzzy decoupling, which fuzzy rules were used for compensation decoupling unit. And it puts forward for the strongly multivariable coupling of the combustion control system. From the simulation of the CFBB by using MATLAB/SIMULINK, the new method has effective decoupling performance, and it has good dynamic characteristic and static characteristic.

The study of the control of the bed temperature in the Circulating fluidized bed boiler based on the fuzzy control system

Bed temperature, which influences boiler overall combustion efficiency and the rate of pollutants emission, is one of the most significant parameters in the operation of the Circulating fluidized bed boiler. at the some time, it was affected by many variable, so it is a time-vary and multivariate uncertain complex control system. In this paper three kinds of controllers is designed, including a fuzzy controller, fuzzy controller with adjustable factor and fuzzy-PID controller of the feeding coal-temperature subsystem. All models of the system were generated by using MATLAB/SIMULIN. The simulation results showed that the fuzzy-PID controller was superior to the other controllers in speediness and stability ability.