A new adaptive DO (dissolved oxygen) concentration control algorithm considering DO electrode dynamics with response time delay has been developed. A system model with two time-varying parameters was used to relate the DO concentration with two control variables: air flow rate and agitation speed. Parameters of this model were estimated on-line using a regularized constant trace recursive least-squares method. An extended Kalman filter was used to remove the effect of noises from the DO concentration measurements and thus to improve control performance. A discrete one-step ahead control scheme was adopted to determine control actions based on the parameter estimation results. Experimental results showed that the new adaptive DO concentration control algorithm performed better than other algorithms tested, a PID controller and adaptive algorithms without the DO electrode dynamics.
The characteristics and performance of an autotuning proportional integral derivative (PID) controller developed by us have been investigated. T h e parameters for this controller, proportional gain, K , the integral time constant, Ti, and the derivative time constant, Td, are on-line-tuned by using heuristic rules, requiring no a priori tuning. The controller showed a stable and robust performance, even when only K was online-tuned. However, the dynamic (or time delay) of the membrane-type dissolved oxygen (DO) probe caused oscillations in the DO concentration unless it was properly compensated. This required a prediction method. When all three controller parameters were on-line-adjusted, the DO probe dynamic could be effectively overcome with no separate prediction step.
A novel control method involving an automatic tuning of digital proportional-integral--derivative controller parameters has been developed for better regulation of dissolved oxygen concentration by manipulating agitation speed in batch fermentation processes. Heuristic reasoning allows the proportional-integral--derivative controller to reach improved tuning decisions based upon the supervision of certain control performance indices in the same cognitive manner as in expert control.~-
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