Single-neuron PSD adaptive control based-on Smith predictor for the main stream temperature

The main steam temperature process is regarded as a controllable process with large dead time and immeasurable disturbances. In this paper a new single-neuron PSD self-adaptive algorithm that based on Smith predictor was proposed, i.e., a compound controller was combined with Smith predictor and single-neuron PSD self-adaptive controller. Compared with conventional PID controller, the results of simulation show that the system has favorable dynamic properties and good adaptability. The variety of main steam temperature can be maintained in a very small range and it can manipulate variable changes smoothly under large-scale variety of load. Therefore, the scheme has promising application prospects.