Modeling And Control Of AirBall System

Airball system consisted of a DC electric motor, a fan, a glass tube, an airball and an ultrasonic sensor etc. The system is very complicated, nonlinear and multiple disturbance etc. This thesis was based on Airball system provided by B&R Company, the PLC control system, Automation Studio configuration software and Matlab/Simulink software. The research concentrated on the modeling and control of Airball system using the method of mechanism modeling.The whole model was based on mechanism modeling. The DC electric motor theory was used to build a model for motor. Hydromechanics and Bernoulli's equation was used for wind model. The airball model used Newton's law of motion. Finally, the whole mathematic model of Airball system was built. The Matlab/Simulink model was built, and a series of simulation researches were done to test the different height output of different voltage input. Experiments were made and the results showed that the airball kept the same height within a certain range of voltage input.The B&R PLC was used to control the airball system by cascade PID algorithm. The PID controller was designed under the circumstance of Matlab/Simulink and was downloaded into PLC. Experiments were made and the results showed that the controller of airball system was realized.H∞robust controller of the standard framework was researched and designed, the true and rational controller K was seeked, made the controlled object G stable. The robust control toolbox of MATLAB software was used to design the H∞robust controller, which greatly reduced the complexity of computation. The weighting functions were selected on line. This paper domained the choice of weighting matrix frequency, and then, transformed into a state space for calculation, when the mixed sensitivity problem was designed. H∞Robust control can ensure the system to have a good control effect in uncertain cases.The LQR controller was researched and designed. The controller can well track the given instruction, and reach the steady state very quickly. The LQR controller of the system was designed which attributed to the objective function determination of weight matrix. The results shown that the designed controller has strong robustness.