This paper presents a practical model for load frequency control (LFC) of two-area interconnected power system. The proposed model is a non-linear power system and is framed with thermal generating units including security constraint governor dead band imposed by the governor. A Proportional Integral Derivative (PID) controller is used for the design and analysis of the proposed model. The Part...

The controller attempts to minimize the error over time by adjustment of a control variable, such as the position of a control valve, a damper, or the power supplied to a heating element, to a new value determined by a weighted sum Where k p, K i and K d all non negative, denote the coefficients for the proportional, integral and derivative terms. Dead time’s producea decrease in the system pha...

In the context of reaching best way to control movement autonomous cars linearly and angularly, making them more stable balanced on different roads ensuring that they avoid road obstacles, this manuscript chiefly aims reach optimal approach for a fractional-order PID controller (or PIγDρ-controller) instead already classical one used provide smooth automatic parking electrical cars. The PIγDρ-c...

Demand and frequency deviation is gaining more popularity in power system research especially with multiple systems interconnections operations as a result of the complexity network, network upgrade renewable energy sources integration. However, stability respect to momentarily fault Load Frequency Control (LFC) models, terms time taken for settle, magnitude overshoot Steady-State Error (SSE) m...

Most of the process systems exhibits non-linear behaviour, so conventional controllers are not able to provide accurate data. At present, various soft computing techniques are used to overcome imprecision and uncertainty effects of conventional controllers. Various soft computing techniques like fuzzy logic, genetic algorithm and particle swarm optimization have been suggested for optimum setti...

Usually it is difficult to solve the control problem of a complex nonlinear system. In this paper, we present an effective control method based on adaptive PID neural network and particle swarm optimization (PSO) algorithm. PSO algorithm is introduced to initialize the neural network for improving the convergent speed and avoiding weights getting trapped into local optima. To adapt the initiall...

This Paper presents a novel Cultural Algorithm based particle swarm optimization (PSO) technique which is intended to assist in converging to a accurate solution in the control of Linear Brushless Direct Current motor (LBLDC). With the novel PSO-based approach the optimal Proportional-Integral-Derivative (PID) controller parameters are deduced for efficient speed control of Linear Brushless DC ...

To reduce the effect of non-linearity in air gap control active magnetic bearings (AMB). The PID controller for AMB is proposed this study, which optimized with a reformative artificial bee colony (RABC) algorithm. RABC algorithm balances exploitation and exploration capabilities ABC by introducing globally optimal solutions improved food source probabilities. Simulation six benchmark functions...

One of the most important problems today is robotics and its control, due to the vast application of inverted pendulum in robots.In this paper, by using a combination of "PSO" Algorithms, we have tried to optimally control the inverted pendulum by nonlinear equations. Here particle swarm optimization algorithm is used to refining parameters of PID controller The results of this simulation has b...