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The Study Of Fuzzy Predictive Learning Control Method For Batch Process

Posted on:2007-04-08Degree:MasterType:Thesis
Country:ChinaCandidate:W LiFull Text:PDF
GTID:2178360185971629Subject:Detection Technology and Automation
Abstract/Summary:PDF Full Text Request
Batch processes are batch-production processes following sequential operation steps. They are widely used in industrial domains such as fine chemical, pharmaceutical producing, biology engineering, modern agriculture etc. With the flexible trend of industrial manufacture and various requirements of market on products, they are paid more and more attention. Human operation dominates in traditional batch processes, so the corresponding automation is generally lack. As a result, advanced control strategy and optimization method are urgently required to develop productive efficiency and save productive cost.Because non-linearity, large time lag, time-varying, non-accurate mathematic model etc. exist in many batch process units, PID control method can not do as well as expected. Besides, as these batch processes always run under transitional condition without stability, their control and optimization are quite complex, as a result, simple intelligent control algorithm can not do well either. So, new suitable intelligent control strategy must be researched. The particular character of batch operations is that they are repetitive and errors in one batch are likely to repeat in the subsequent ones, which coincides with the application feature of iterative learning control (ILC). But the traditional ILC is only designed for SISO systems, furthermore, it's not quite suitable for solving problems such as constraint, coupling etc, which are frequently encountered in process control. Meanwhile, fuzzy model and predictive control have their respective advantages in the problems above. Based on the combination and improvement of the three kinds of method above, a new algorithm of predictive iterative learning control is introduced in this paper. Moreover, a new method is given that the iterative learning controller based on fuzzy prediction can be designed without mathematic model and prior experience. In this paper, programs for the control algorithm are given, and the performance of the controller is tested by corresponding simulation. Finally, considering that pesticides production is a typical batch process, the controller is applied to omethoate synthesis temperature process control. The simulation result shows that it meets proposed standard better.The main contents are as follow: (1) The present condition of fuzzy control, predictive control and iterative learning...
Keywords/Search Tags:batch process, iterative learning control, model prediction, T-S fuzzy model identification
PDF Full Text Request
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