Scope of this analysis is to tune the proportional-integral-derivative (PID) parameters autonomously for controlling the moisture content in the paper industry by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. The GA and PSO based PID tuning results are compared with the Conventional based PID tuning to examine the performance of time domain specifications; hence,...

In this paper, determining the optimal proportionalintegral-derivative (PID) controller gains of an single-area load frequency control (LFC) system using genetic algorithm (GA) is presented. The LFC is notoriously difficult to control optimally using conventionally tuning a PID controller because the system parameters are constantly changing. It is for this reason the GA as tuning strategy was ...

Three design methodologies, such as Internal Model Control (IMC), Generalized Predictive Control (GPC) and Two Degree-of-Freedom (TDF), for automatic tuning of PID parameters, have been reviewed, compared and applied to a laboratory plant with dead time. Tuning parameters are derived as a First-Order-Plus-Dead-Time (FOPDT) model. Dead time compensating PID controllers are assessed not only from...

Abstract. Proportional-integral-derivative (PID) control is the most popular control architecture used in industrial problems. Many techniques have been proposed to tune the gains for the PID controller. Over the last few years, as an alternative to the conventional mathematical approaches, modern metaheuristics, such as evolutionary computation and swarm intelligence paradigms, have been given...

PID control plays an important role in industrial system. As known that tuning PID parameters have strong effect on the control performance, therefore, many tuning PID parameters schemes have appeared, such as model based design methods which are still used in practical applications. However, in some sophisticated systems like thermal processes and chemical processes, experiments are required m...

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...

Parametric uncertainty is the one of the challenging task in many dynamical systems. In this paper QFT based PID Controller is developed to improve the performance for a pitch control of uncertain aircraft system. The controller is designed based on the dynamic modeling of system begins with a derivation of suitable mathematical model to describe the longitudinal motion of an aircraft. Genetic ...

It is commonly believed that for SISO systems, well tuned PID controllers work as well as model-based controllers and that PID controllers are more robust to model errors. In this paper we present a novel offset-free constrained LQ controller for SISO systems, which is implemented in an efficient way so that the total controller execution time is similar to that of a PID. The proposed controlle...

This paper covers practical study of responses of the systems which are under control. The auto tune proportional-integral – derivative (PID) controller is used for controlling of systems. The auto tune algorithm is implemented using the successive approximation method. The auto tuner has been checked with various plant models in MATLAB environment that causes only minor perturbation on the nor...

A PID-deadtime controller is realized by inserting a time delay into the integral feedback circuit. Such a controller possesses a transfer function similar to a Smith predictor or an internal-model controller. Effective tuning of PID deadtime controllers remains unsolved even though they give better regulatory performance than a conventional PID control algorithm for processes with a long pure ...