Title of article :
Automatic tuning of decentralized PID controllers for MIMO processes
Author/Authors :
Y. Halevi، نويسنده , , Z. J. Palmor، نويسنده , , T. Efrati، نويسنده ,
Abstract :
An automatic tuning algorithm for decentralized PID control in multiple-input multiple-output (MIMO)
plants is presented• This algorithm generalizes the authorsʹ recent auto-tuner for two-input two-output
systems to any number of inputs and outputs. The algorithm consists of two stages. In the first, the
desired critical point, which consists of the critical gains of all the loops and a critical frequency, is identified.
The auto-tuner identifies the desired critical point with almost no a priori information about the
process. During the identification phase all controllers are replaced by relays, thus generating limit cycles
with the same period in all loops. It is shown that each limit cycle corresponds to a single critical point
of the process. By varying the relays parameters different points can be determined. The auto-tuner contains
a procedure which converges rapidly to the desired critical point while maintaining the amplitudes
of the process variables as well as of the manipulated variables within prespecified ranges. In the second
stage, the data of the desired critical point is used to tune the PID controllers by the Ziegler-Nichols rules
or their modifications. This paper focuses on the first stage. The steady-state process gains, which are
required for the appropriate choice of the desired critical point, are determined by the auto-tuner in
closed-loop fashion simultaneously with the identification of the critical points. The identification of the
process gains is achieved at no extra plant time. Based upon a large number of simulated cases, the proposed
auto-tuner seems to be efficient and robust. The paper discusses the underlying principles of the
auto-tuner and its properties and capabilities are demonstrated via examples.
Keywords :
Robustness , interpolation , Model-based control , optimization , Convexity , Model predictive control , Nonlinear systems
Journal title :
Astroparticle Physics