控制专业方向介绍,英文

控制专业方向介绍,英文
控制专业方向介绍,英文

Application of fuzzy control in the temperature and humidity

control of artificial climate box

Fuzzy control is a control method which based on fuzzy sets theory and it is formed by the combined of fuzzy sets theory, fuzzy technology and automatic control technology. From birth of fuzzy control, there are lots of explorative and creative research and application achievements have been obtained. Now fuzzy control idea has been a widely used method to solve problems.

Although fuzzy control has been widely used in engineering applications, there are still many practical problems which have not been resolved, including the ways to access the rules of fuzzy control, how to find the parameters , fuzzy control problems in a various multivariable coupling system and the way to promote the steady-state accuracy of fuzzy control , and so on. If we want a promotion of fuzzy control,the first step is to resolve these problem.

To expand the scope where the application of fuzzy control is suitable, and solve the practice control problems in a new fuzzy control methods. There are several key issues in the application.

The way to access rules and optimize parameter in fuzzy control.

combining with fuzzy control, simulated annealing and genetic algorithms, Aimed at this problem, a new genetic algorithm, fuzzy adaptive simulated annealing genetic algorithm, which is used to optimize parameters in fuzzy controll, is presented. and its convergence, convergence speed and the prevention of "premature" phenomenon of this new genetic algorithm are analyzed.

the problems when fuzzy control solutions are used in a multivariable coupling system.

We can find a fuzzy compensation to decouple, and its decoupling ability is studied. We can optimize the rules and parameters of fuzzy compensation decoupling by a genetic algorithm.

The steady-state accuracy of fuzzy control is not accurate enough.

For a cyclical movevment objects fuzzy-iterative learning hybrid control method is presented combined with fuzzy control method and iterative learning control method; And for a servo objects, a grey prediction fuzzy compensation control

method is presented combined with fuzzy control method and grey prediction control method.

Artificial climate box is a laboratory equipment to simulate the natural environment such as temperature, humidity and illumination, to create local artificial climate .It can not only provide users with an ideal artificial climate experiment environment, can be used to plant germination, seedling, tissue cells, microbial cultivation, wood, textile, building materials and electronic product performance and aging experiment, the storage of chemicals and experiment and so on, also can be used for breeding of insects and small animals, water analysis of the artificial climate experiment of determining BOD, and other purposes.So the artificial climate box has been widely applied in the biological, medical, agriculture, food, material, chemical and other industries .

Artificial climate box usually need to control the casing temperature, humidity and light.The light can be shined by special fluorescent lamp lighting, according to the level of control can use the switch control, implementation is simpler, and the temperature and humidity control due to the particularity of object itself has, control is more complicated, its control method need additional research.The core issue of artificial climate box is the way to control temperature and humidity accuracy and response speed, etc.

We can know that when the temperature is low and heating, water for cooling and dehumidification climate crate before condensation of water will increase the internal moisture ;When the temperature is high and refrigeration would have fallen after the air humidity of refrigerator and make the humidity drop, similarly, when humidity is low and humidifying, external cold or hot and will change the internal temperature, moisture and humidity high moisture will inevitably led to the decrease of the temperature.So the temperature and humidity control is strong catenated. And different specifications of the coupling of temperature and humidity of the degree is different.And sometimes climate box need a cycle control for temperature and humidity, they have two periods that the temperature and humidity is different, and climate box, the mathematical model of temperature and humidity control and shows that they have larger delay hysteresis characteristics, to achieve fast rise, short transition time, small overshoot and the purpose of general control method is very difficult to work.

As mentioned earlier, there must be a strong catenated phenomenonthe between

temperature control and humidity control, the independent use of temperature and humidity control method of fuzzy control or others without considering their catenated phenomenon, the effect of control is bad, even can cause the phenomenon of oscillation.Due to temperature and humidity control influence each other, they again it is difficult to establish the mathematical model, and different types of artificial climate box and its catenated relationship is different, so the general solution method was less effective, here we use a simple and effective method, which adopts the method of fuzzy reasoning, according to the result of the fuzzy control output, and then to draw a decoupled to compensate the output of fuzzy reasoning, solution in front of the disaster to compensate the output and the fuzzy synthetic later for the actual output control output.

So we can use the fuzzy adaptive simulated annealing genetic algorithm (FASAGA) to optimize the parameters and rules of fuzzy control.

Fuzzy adaptive simulated annealing genetic algorithm (FASAGA) is a kind of improved genetic algorithm, it combines the fuzzy control, the simulated annealing algorithm and genetic algorithm.In the combination of simulated annealing mechanism and genetic algorithm, we can combine the simulated annealing mechanism to the crossover operator of genetic algorithm and the genetic operators, rather than individual simulated annealing treatment, so we can not only improved the genetic operators, also we can retain the population genetic algorithm and the characteristics of the new produce flexible, and increase the "climbing" ability of the simulated annealing algorithm.So we can combine simulated annealing algorithm and genetic algorithm in this way.

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