IEEE Transactions on Automatic Control, Vol.58, No.9, 2292-2306, 2013
Controller Design for Multivariable Linear Time-Invariant Unknown Systems
This paper deals with the design of multivariable controllers for stable linear time-invariant multi-input multi-output systems, with an unknown mathematical model, subject to constant reference/disturbance signals. We propose a new controller parameter optimization approach, which can be carried out experimentally without knowledge of the plant model or the order of the system. The approach has the advantages that controllers can be tuned by perturbing only the initial conditions of the servocompensator, and that the order of the resulting controller can be specified by the designer. Implementation of the proposed controller design approach is described, and an experimental application study of the proposed method applied to a multivariable system with industrial sensor/actuator components is presented to illustrate the feasibility of the design method in an industrial environment.
Keywords:Large-scale systems;multivariable control;optimal control;parameter optimization;proportional-integral-derivative (PID) control;robust servomechanism problem;servocompensator;tuning controllers