Design and experimental evaluation of a multivariable self-tuning PID controller

A multivariable self-tuning PID (proportional-integral-derivative) controller design scheme is proposed which has a static matrix precompensator to reduce the interaction terms of the process transfer function matrix adjusted by an online estimator. The p*p precompensated multivariate system is then controlled via ʹpʹ univariate self-tuning PID controllers whose parameters are adjusted by a second identifier placed around the precompensated plant. The PID parameters are calculated online based on the relationship between the PID and generalised minimum variance control laws. The scheme is experimentally evaluated on a 2*2 level plus temperature control system. Experimental results illustrate the effectiveness of this scheme.