Evolutionary computation based tuning of nonlinear PID controller for twin rotor MIMO system

Abstract

newline Proportional Integral Derivative PID controllers are the most widely used controller in Industries which offers easy and proficient solution in real world problems utilized for control of diverse dynamical systems ranged from industrial process to aircraft and ship dynamics Initially straight forward tuning of PID controllers carried out by Ziegler Nichols and Cohen Coon which are the normally used conventional methods and it needs further tuning to achieve optimality In order to enhance the performance of linear PID controllers many approaches have been developed to improve the adaptability and robustness by adopting the self tuning method general predictive control fuzzy logic and neural networks strategy Conventional PID controllers are linear combination which achieve a compromised performance in terms of system response speed and stability A nonlinear PID controller can provide additional degree of freedom to achieve a much improved system performance by introducing a nonlinear function in the conventional PID control structure Empirical rules are suggested for the implementing the nonlinear function Nonlinear PID controller employed for tuning Linear Piezoelectric motors Superconducting Magnetic Energy Storage and results disclose that Nonlinear PID controller shows better performance than conventional linear PID controller newline newline