PID Controller Tuning Using Soft Computing Techniques - Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE-2012) - page 265

accurate mathematical models. The key issue for PID controllers is the accurate
and efficient tuning of parameters. In practice, controlled systems usually have
some features, such as nonlinearity, time-variability, and time delay, which make
controller parameter tuning more complex. Moreover, in some cases, system
parameters and even system structure can vary with time and environment. As a
result, the traditional PID parameter tuning methods are not suitable for these
difficult calculations.
As a popular optimization algorithm, the GA had been widely used to turn
PID parameters. Soltoggio [ 2 ] proposed an improved GA for tuning controllers
in classical, first and second order plants with actuator nonlinearities. Chen and
Wang [ 3 ] used the population-based distribution GA to optimize a PID controller,
and found that the search capability of the algorithm was improved by competition
among distribution populations in order to reduce the search zone. The PID
controllers based on GAs have good performance and have been applied in
practice.
The aim of this paper is to design a plant using Genetic Algorithm. Genetic
Algorithm or in short GA is a stochastic algorithm based on principles of natural
selection and genetics. Genetic algorithms (GAs) are a stochastic global search
method that mimics the process of natural evolution. Genetic algorithms have been
shown to be capable of locating high performance areas in complex domains
without experiencing the difficulties associated with high dimensionality or false
optima may occur with normal PID techniques. Using genetic algorithms to per-
form the tuning of the controller will result in the optimum controller being
evaluated for the system every time.
In order to solve this problem a PID controller under Genetic Algorithm with
self-tuning is applied, which will perform high efficiency position control. The
efficiency of Control Algorithm is presented through a simulation and compared
with the quality of PID controller.
Mathematical Modeling of DC Motor
Modeling Scheme
As reference we consider a DC shunt motors as is shown in Fig. 1 . DC shunt
motors have the field coil in parallel (shunt) with the armature. The current in the
field coil and the armature are independent of one another. As a result, these
motors have excellent speed and position control [ 1 ]. Hence DC shunt motors are
typically used applications that require five or more horse power.
The input voltage V is applied to the field winding which has a resistance and
inductance of R and L, respectively. The armature current supplied to the armature
is kept constant and thus the motor shaft is controlled by the input voltage.
The field current produces a flux in the machine which in turn produces a torque at