Automated PI tuning for a weigh belt feeder via unfalsified control

Abstract

Proposes and experimentally demonstrates an approach to automated PI tuning for an industrial weigh belt feeder that is based on unfalsified control concepts. Unfalsified control is used as a means of using both open and closed loop test data to identify a subset of controllers (from an initial set) that meets the multiple objectives specified by the control engineer. A novel feature of the unfalsified approach is that it allows the performance of a given controller to be predicted without inserting the controller in the loop. In addition, this methodology does not require an explicit model of the system to be controlled. When the unfalsified PI autotuning approach is applied to the industrial weigh belt feeder, it is able to successfully identify a subset of PI control laws that meets the performance specs. This automated PI tuning approach is implemented here off-line but may be implemented online and applied in a straight forward manner to other control systems.