This paper presents the development of an on-line self-tuning algorithm for PID Controller to control the Governor using Successive approximation method. The successive approximation method is purely based on computational technique. The conventional PID controller is replaced by self tuning PID controller; to make them more general and to achieve minimum steadystate error, also to improve the ...

The application of a self-organizing fuzzy proportional–integral–derivative (SOF-PID) controller to a multiple-input–multiple-output (MIMO) nonlinear revolute-joint robot arm is studied in this paper. The SOF controller is a learning supervisory controller, making small changes to the values of the PID gains while the system is in operation. In effect, the SOF controller replaces an experienced...

A Maglev system was modeled by the exact feedback linearization to achieve two same linear subsystems. The proportional-integral-differential controllers (PID) based on particle swarm optimization (PSO) algorithm with four different inertia weights were then used to regulate both linear subsystems. These different inertia weights were Fixed Inertia Weight (FIW), Linear Descend Inertia Weight (L...

In this paper, the interval type-2 fuzzy proportional-integral-derivative controller (IT2F-PID) is proposed for controlling an inverted pendulum on a cart system with an uncertain model. The proposed controller is designed using a new method of type-reduction that we have proposed, which is called the simplified type-reduction method. The proposed IT2F-PID controller is able to handle the effec...

this study on the design of pid controllers for flexible single-arm robot system optimizationpso method is focused so that the coefficients of the pid controller are reduced. in this study,pid controller and pso algorithm have been described and then by using matlab, pidcontrol was simulated. then by pso algorithm, attempts to reduce the pid coefficients are givenby simulation. finally pid coef...

This paper introduces an optimal fuzzy proportional–integral–derivative (PID) controller. The fuzzy PID controller is a discrete-time version of the conventional PID controller, which preserves the same linear structure of the proportional, integral, and derivative parts but has constant coefficient yet self-tuned control gains. Fuzzy logic is employed only for the design; the resulting control...

This paper presents an online two-stage Q-learning based multi-agent (MA) controller for load frequency control (LFC) in an interconnected multi-area multi-source power system integrated with distributed energy resources (DERs). The proposed control strategy consists of two stages. The first stage is employed a PID controller which its parameters are designed using sine cosine optimization (SCO...

Artificial neural networks (ANNs) are parallel architectures for processing information even though they are usually realized on general-purpose digital computers. This research has been focused on the design, analysis and real-time realization of artificial neural networks using programmable analog hardware for control and classification. We have investigated field programmable analog arrays (...

This paper deals with the designing of neural PID speed controller of Permanent Magnet synchronous Motor (PMSM). The conventional Proportional-Integral-Derivative (PID) controller is largely used in industry because of the robustness this regulator procures. ANN is developed controller in this work, offer inherent advantages over conventional PID controller for PMSM, Reduction of the effects of...

Proportional Integral derivative (PID) controllers are widely used in industrial process control. With its three term functionality providing regulation to both transient and steady state responses, PID control offers the simplest and most efficient solution to many industrial control problems. Tuning of PID gain parameters continuous to be important as these parameters has great influence on t...