PID controllers using fuzzy logic seminar report/pdf/ppt download
Introduction: In spite of developed modern control techniques like fuzzy logic controllers or neural networks controllers, PID controllers constitute an important part at industrial control systems so any improvement in PID design and implementation methodology has a serious potential to be used at industrial engineering applications.
At industrial applications the PID controllers are preferred widespread due to its robust characteristics against changes at the system model.
From the other side at industry the exact plant models can not be obtained due to too much nonlinear parts and uncertainties so at practice engineers usually find an appropriate model for the dynamic system.
For example, when a thermal system is taken into consideration, the systemís overall gain changes from season to season. Changes in dynamic system parameters and unknown system variables directly affect the performance of the system.
So for obtaining a better performance the controller parameters have to be renewed in some time interval.
A lot of methods have been developed over the last forty years for setting the parameters of a PID controller.
Some of these methods are based on characterizing the dynamic response of the dynamic system to be controlled with a first-order model or second-order model with a time delay 1.22..2CIDMAXLKTLTL.
All general methods for control design can be applied to PID control. A number of special methods that are tailor made for PID control have also been developed, these methods are often called tuning methods.
The most well known tuning methods are those that are stated by Ziegler and Nichols. These methods do not need any mathematical calculation to find PID parameters.
The Ziegler-Nichols Oscillation Method, Ziegler-Nichol Process Reaction Method and Frequency Response method, and Cohen-Coon Reaction Curve Method are basic Self-Tuning methods.
Oscillation method is based on system gain, in other words, system gain is redounded until the system makes oscillation, then PID parameters can be found from system response graphic.
Practically, this method is useless for too many sort of real systems, because oscillation at the output of the system can easily damage the system. Frequency response uses frequency domain rules to find PID parameters.
Cohen-Coon method uses system step response for an open loop system to find PID parameters. Also Ziegler and Nichols proposed PID parameters for a group of system due to its system parameter values 1111PIDPIDTszGKKK.
In this seminar paper, Ziegler-Nichols process reaction method (PRM) is used to determine PID controller parameters; Kc, Ti and Td.
The Ziegler-Nichols process reaction method works well in a large variety of industrial systems. However, this method rarely can find insufficient PID parameters, and system response makes high overshoots or oscillations before entering in steady state.
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