Identification For Transfer Function Models Of Continuous-Time Systems

The transfer function is very important in the control analysis and design of system, the design of controller needs transfer function. Besides the dynamic characteristic of system, the structure of system, parameters on system performance were usually expressed with transfer function, and most of the chemical process is the first and second order systems. Therefore, the research of low-order transfer function model identification method has great important value in theory and practical application. This article is based on" The National Nature Science Foundation of China", and presents the identification algorithm for continuous system based on transfer function models. The author reads and researches a large number of relevant literature, and deep studies the identification of continuous systems based on step response and impulse response. the innovation reserch result in the thesis as follows:1. For the industry’s first and second order transfer function models, an multi-point identi-fication method is presented to estimate the parameters of continuous systems based on the step response data. The basic idea is that the input and output data were obtained through system step response. According to the transfer function model, a special data poin or more points were selected, then the transcendental equations are changed into the algebraic equations which are easy to solve for computing the parameters of the trans-fer function models. The numerical examples indicate that the proposed approaches can estimate the parameters of the systems.2. According to principles of iterative identification, the newton iterative identification algo-rithm is presented to estimate the parameters of transfer function models based on input and output data of system. The output error functions were used as the objective crite-rion function, then the parameter values were used as the parameter estimatesthen when the criterion function were minimization. Finally, the simulation examples were given and the simulation results indicate that the proposed algorithm works quite well with noise interference.3. Based on the impulse response data of system, the newton iterative identification algorithm was presented to estimate parameters of transfer function models with rational fraction. The transfer function was expressed with rational fraction to avoid the solution of the system gain K, and the impulse signal was used input signal. Then algorithm simulation examples were given for first and second order systems with white noises. The results show that the proposed algorithm works quite well under certain conditions.In conclusion, in this paper, we propose the multi-point identification algorithm and newton iterative identification algorithm to estimate parameters K and T of transfer function models based on step response and impulse response. Some simulation examples indicate that the estimated model can capture the dynamics of the system. A simple conclusion is obtained in the end, the insufficiency and further rasearch of the paper are also summarised in the end, for instance, the derived algorithms are lack of proof of practice and so on.