Graduate Thesis Or Dissertation
 

Predictive control using feedback- : a case study of an inverted pendulum

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  • Vision is a flexible, non-contact sensor that can be used for position feedback in closed-loop control of dynamic systems. Current vision systems for industrial automation provide low sample rates and large sample delays relative to other types of position sensors. Poor sample rates and sample delays are a result of the vast volume of data that must be collected and processed by the vision system. A predictive visual tracker can help compensate for some of the deficiencies of current industrial vision systems. The objectives of the present research are to demonstrate that vision is a useful feedback sensor and prediction can be used to improve performance by compensating for the feedback delay of the vision system. An inverted pendulum was stabilized using a vision sensor as feedback to a state-feedback controller. The vision data was run through a d-step ahead predictor to compensate for the vision system delays. The system was simulated in Mat lab and an actual physical system was used to test the performance of the control system. The inverted pendulum provides a good test-bed for studying predictive control using vision feedback. The pendulum will fall without the constant adjustment of the cart position. The adjustment of the cart by the controller is delayed because of latency and quantization errors in vision feedback. The better the controller is able to compensate for delays and quantization errors, the greater its ability to stabilize the inverted pendulum.
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