This study aimed at the implementation and synchronization control of cardiac circuit. First, the MATLAB-Simulink was used to simulate the dynamic behavior of cardiac chaotic circuit, and simple electronic modules were used to implement the cardiac system. Then the Particle Swarm Optimization PSO was used to seek for the proportional, integral, and derivative gains of optimal PID controller, an...

This paper presents the position tracking performance of an electro-hydraulic hydraulic servo (EHS) system using sliding mode control (SMC) with proportional-integral-derivative (PID) sliding surface. In modelling process, a mathematical model of the EHS system is developed by considering its nonlinearities as represented by a Lu-Gre friction model. The control strategy is derived from the deve...

In maintenance field, prognostic is recognized as a key feature as the prediction of the remaining useful life of a system which allows avoiding inopportune maintenance spending. Assuming that it can be difficult to provide models for that purpose, artificial neural networks appear to be well suited. In this paper, an approach combining a Recurrent Radial Basis Function network (RRBF) and a pro...

The use of soft-computing algorithms in hardware-in-the-loop applications has been investigated. A Proportional-Integral-Derivative (PID) classical controller and a Fuzzy Logic Controller (FLC) were designed and successfully tested on the Turbine Technologies SR-30 turbojet engine for the main-stage operation of the engine. Transfer function model of the plant was obtained using frequency-respo...

In this paper, we use the fuzzy neural network (FNN) to develop a formula for designing the proportional-integral-derivative (PID) controller. This PID controller satisfies the criteria of minimum integrated absolute error (IAE) and maximum of sensitivity (Ms). The FNN system is used to identify the relationship between plant model and controller parameters based on IAE and Ms. To derive the tu...

This study presents the improvement in performance of Proportional-integral-derivative (PID) controller for position control antenna azimuth system subjected to external disturbance. The design PID is developed by adding arc tan function error instead direct an integral part controller, yielding a Nonlinear (NPID). A Particle Swarm Optimization (PSO) used this tune parameters and NPID controlle...

A novel intelligent multiple-controller framework incorporating a fuzzy-logic based switching supervisor is presented for adaptive control of non-linear systems . The proposed methodology provides the designer with an automated choice of using either: a conventional Proportional-Integral-Derivative (PID) controller, a PID structure based pole (only) placement controller, or a PID structure base...

The use of complex self tuning Proportional, Integral and Derivative (PID) controller, to drive the speed and direction in mini robot, is limited by calculus power and by the precision and noise of the on board input sensors, particularly severe problems arise in computing the derivative term. In this work a PID whose terms are computed from filtered input with a simple recursive Exponentially ...

In maintenance field, prognostic is recognized as a key feature as the prediction of the remaining useful life of a system which allows avoiding inopportune maintenance spending. Assuming that it can be difficult to provide models for that purpose, artificial neural networks appear to be well suited. In this paper, an approach combining a Recurrent Radial Basis Function network (RRBF) and a pro...

This paper proposes a novel controller design method based on using artificial bee colony (ABC) algorithms for an unstable nonlinear continuously stirred tank reactor (CSTR) chemical system. Such CSTR process is highly nonlinear and its dynamic is significantly dominated by system parameters. It is a good challenge to access the controller design performance when the controller is applied in th...