Research Of Self-adjusting Fuzzy PID For Automatic Analyzer Sampling Institution

“Automatic chemiluminescence immune analyzer” is an important diagnosisinstrument in bio-medical field. It can diagnose disease by detecting specific antigenand antibody in sample. Three dimensional sampling institution as an importantcomponent of the analyzer is responsible for the aspiration, transference and distributionof micro biological samples and nanometer magnetic beads. The velocity, motionsmoothness and positioning accuracy of the institution have a direct effect on analyzer’sefficiency and detection precision. When the analyzer is in batch production, thedifferences of parts’ machining error and assembly accuracy causes differences tomotion environment of sampling institution. As conventional PID has no universalapplicability, it costs much time and energy to tune the parameters for every instrument.To solve the problem this topic studies a motion control method which has adaptiveability.The self-adaptive fuzzy PID controller which combines fuzzy controller andconventional PID controller can adjust the PID controller’s parameters online based oncontrolled object’s response without knowing its mathematical model. The controllerwhich has not only the same adaptability and flexibility with fuzzy control, but also thesame precision and high robustness with conventional PID controller takes charge forsampling institution’s accurate motion control.First, by analyzing the control requirement and index of the sampling institution,TMS320F2812is chosen as the master control chip. Around the chip sensor signalcollection circuit, communication circuit and motor drive circuit are designed. Thiscomposes a close loop control system for sampling institution, and it puts up theplatform for the research of motion control method later.Then, the motion controller based on self-adaptive fuzzy PID is designed,confirming the universe of input and output in the fuzzy controller, summarizing therules of PID control, formulating the fuzzy rules and confirming the fuzzy reasoningand defuzzification method. A fuzzy controller is designed in matlab using FUZZYtoolbox and the simulation experiment of the controller is done using the DC motor asthe controlled plant. The result is compared with the conventional PID motion controllerto verify the controller’s feasibility.Finally, the self-adaptive fuzzy PID is implemented using C language and theexperiment of sampling institution motion control is done. The experiment is used toverify the effectiveness of hardware, motion control algorithm and software of theworkstation. By regulating the bearing pre-tightening force, tension degree ofsynchronous belt and movement inertia, the adaptive ability of the control method is verified.