Experimental comparison and application of various parameter-adaptive control algorithms

Abstract

Various recursive parameter estimation algorithms and controller design procedures can be combined to build up parameter-adaptive control algorithms. Two parameter estimation methods and six control algorithms have been selected, taking into account good convergence properties and small computational expense and regarding the conditions for closed-loop identification. The resulting 12 parameter-adaptive control algorithms are compared and tested with a process computer in on-line operation with analog simulated stable and unstable processes for stochastic disturbances and step changes of the reference signal. The results are very promising. In many cases a good control performance is achieved. As a priori knowledge only the sampling time, the process model order and time delay and in some cases a weighting factor for the process input signal are required. Some parameter-adaptive control algorithms with good properties are applied to digital adaptive control of an air heater. Conclusions are given for the selection of parameter-adaptive control algorithms, depending on the type of process and its disturbances. The adaptive control algorithms may be applied for adaptive control of constant and time variant, linear and weakly non-linear stable and unstable processes with process computers or micro computers or for self-tuning of control algorithms or tuning of conventional analog PID controllers, if external disturbances act on the loop.