In this paper, a PID fuzzy controller structure is presented. To be successful in implementing fuzzy PID controllers in large applications we must also considered their operating principles. Fuzzy logic controllers are based on empirical control rules. A study case for the validation of the proposed tunning mechanism is presented and analyzed with control application for a synchronous generator...

In process industries, PID control schemes have been widely used due to their simple structures and easiness of comprehending the physical meanings of control parameters. However, the good control performance cannot be obtained by simply using PID controlschemes, since most processes are considered as nonlinear multivariable systems with mutual interactions. In this paper, a design method of mu...

This paper presents the comparison of tracking control performance of fuzzy PI Controller with fuzzy PID and conventional PID controllers. Fuzzy PI controller and Fuzzy PID controller composes of Mamdani type fuzzy controllers and parameters are adjusted to meet the desired control system performances both in transient state and steady state. Computer simulations are done for controlling the ti...

This paper presents the comparison of tracking control performance of fuzzy PI Controller with fuzzy PID and conventional PID controllers. Fuzzy PI controller and Fuzzy PID controller composes of Mamdani type fuzzy controllers and parameters are adjusted to meet the desired control system performances both in transient state and steady state. Computer simulations are done for controlling the ti...

In this paper, an improved cascade control methodology for superheated processes is developed, in which the primary PID controller is implemented by neural networks trained by minimizing error entropy criterion. The entropy of the tracking error can be estimated recursively by utilizing receding horizon window technique. The measurable disturbances in superheated processes are input to the neur...

Proportional Integral Derivative (PID) controller is the most preferable controller in industries that does not require precise analytical model of the system to be controlled. Implementation of PID controllers has gone through several stages of evolution from the early mechanical and pneumatic designs to the microprocessor based systems. Recently “Field Programmable Gate Array” has become an a...

As the air-conditioning control system has the nonlinearity, large time delay and time variation and other characteristics.In this paper,we put forward a method of self-adjusting PID algorithm based on the modified Elman neural network, and the output of the network adjust the three parameters of the PID controller online, so that it has the high controlling precision, good dynamic characterist...

This paper suggests an inverse optimal proportional–integral–derivative (PID) control design method to track trajectories in Lagrangian systems. The inverse optimal PID controller exists if and only if the Lagrangian system is extended disturbance input-to-state stable. First, we find the Lyapunov function and the control law that satisfy the extended disturbance input-to-state stability by usi...

This study deals with one of frequently encountered tasks in process industry – accurate water level control. Proportional Integral Derivative (PID) control is often used for this purpose. Since control parameters of PID controller are fixed and tank system is inherently nonlinear, PID controller should not be used on wider level range. Therefore this study analyzes the effectiveness of water l...

In this paper, a novel method for designing PID controller is proposed. It uses Iterative Learning Control (ILC) for producing an optimum control signal for the plant and then by using a regression method (Least Squared Error), adjusts PID coefficients so that it acts like the ILC. Then PID is implemented on the plant. This method is simulated on automatic voltage regulating system and results ...