References in periodicals archive ?
The basic principle in PID tuning is to adjust the controller parameters fast and accurately as possible for aims of the control design.
Genetic Algorithm Based PID Tuning. It is summarized as follows.
However, in future work, these effects could be considered to form a comprehensive nonlinear model of DC motor and solve the problem of PID tuning based on the mentioned metaheuristic techniques because according to the best of our knowledge there has been a lot of research potential for the PID controller tuning by considering the nonlinearities of DC motor model.
In this paper, a new method is developed and implemented for the design of the PID tuning based on a New Modified Repetitive Control approach.
With the PID parameters tuning model based on AFW, simulation is carried out to test the performance of PID tuning index ITUE and optimizing capacity of AFW on the problem of PID controller parameter tuning.
However, most of the literatures focus on a single-objective optimization while the PID tuning problem is clearly a multiobjective optimization problem.
Also PID tuning for MIMO systems is difficult because it has little information about the model.
Also, hundreds of principles and methods for PI and PID tuning have been developed many of them are reffered in (O'Dwyer, 2009).
Several other approaches have been suggested for improved PID tuning, For instance, the Astrom-Hagglund phase margin method [8], the refined Ziegler-Nichols method by Cohen and Coon [9] as well as Hang et al.
Microprocessor controls standard on all systems and feature automated PID tuning setup with adaptive and self-tuning functions that give precise stable straight-line control.
It is the only PID tuning software equipped with the proprietary Non-Steady State (NSS) Innovation which enables users to accurately model oscillatory and noisy processes.
Other features include programmable soft start, automated PID tuning set-up, and automatic adaptive self-tuning operation.