Enhanced tuning of Smith predictor based series cascaded control structure for integrating processes

This work combines the benefits of cascaded control, Smith predictor, moment matching, and outer-loop decomposition to design an enhanced series cascaded control approach with Smith Predictor for some industrial integrating plants. The inner-loop controller is assumed as a PI/PID type. If the outer-loop process model is of second-order, it is split into first-order models and an individual control-loop is established for each model. This technique is called 'outer-loop decomposition'. PI controller is employed in the loop having a first-order lag whereas proportional control is used if the loop contains an integrator. Controller parameters are obtained by moment matching i.e. equating the Maclaurin series of expected and real closed-loop system functions. Suitable equations and procedures are given to tune adjustable parameters to attain an expected maximum sensitivity. This makes the proposed method more beneficial than the contemporary schemes that require a hit and trial search within a given range of values. It is seen that the suggested scheme yields noteworthy enhancement in closed-loop response compared to some recent strategies even in the presence of perturbed process dynamics.