Abstract – This paper introduces the Slice Genetics Algorithm SGA which representsthe proposed modification to the classic Genetic Algorithm GA scheme. The proposedalgorithm has reduced the population size and maximum iteration in order to get fastand an optimal solution. This algorithm has been used for determining the optimalproportional- integral- derivative PID controller parameters. The proposed algorithmhas versatile features, including, fast, stable rate convergence characteristic also it hasgood computational efficiency in improving the dynamic behavior for the system interm of reducing the maximum overshoot, rise time, settling time and steady-stateserror. The algorithm not only has benefit to improve the convergence characteristic,accuracy but it also shortened the processing time towards the optimal value basedreducing the number of iteration from 40 to 4 or 6 iteration as clear in the MATLABsimulation results..

PID Controller --- Slice Genetic algorithm.

This paper presents a ball position tracking control tuning algorithm for single axis magnetic levitation system using slice genetic optimization technique based nonlinear neural controller. As simple and fast tuning technique, slice genetic optimization algorithm is used to tune the nonlinear neural controller's parameters in order to get the best control action for the magnetic levitation system through the tracking of pre-defined location of the steel ball. Pollywog wavelet activation function is used in the structure of the nonlinear neural controller. The obtained results (using MATLAB program) show that the effectiveness of the proposed controller in minimizing the tracking error to zero value and also, in the softness of the control action with the lowest amount of fitness evaluation number.

ان هذا البحث يقدم خوارزمية تنغيم المسيطر تتابع موقع كرة لنظام التعليق المغناطيسي احادي الأتجاه بستخدام تقنية الشرائح الجنية الأمثلية اساسها المسيطر العصبي اللاخطي. لقد تم استخدام خوارزمية الشرائح الجنية لانها تقنية سهلة و سريعة في تنغيم عناصر المسيطر العصبي اللاخطي لكي يحصل على افضل فعل للمسيطر لنظام التعليق المغناطيسي من خلال تتابع الموقع المعرف مسبقا لكرة الأستيل. ان الدالة الفعالة (Polywog Wavelet)استخدمت في هيكلية المسيطر العصبي اللاخطي. لقد تم الحصول على النتائج بأستخدام الحقيبة البرمجة ماتلاب وتبينت فعالية المسيطر المقترح في تقليل الخطأ التتابعي الى قيمة الصفر وكذلك فينعومة فعل المسيطر مع اقل عدد ممكن لأستدعاء دالة التقيم.

Magnetic Levitation System --- Neural Controller --- Slice Genetic Algorithm

Abstract – The main core of this paper is to design an experimental method for estimating of the nonlinearity, calibrating and testing of the different types of thermocouples temperature sensors (J, K, T, S and R) using multi-layer perceptron (MLP) neural network based on slice genetic (SG) optimization learning algorithm. Temperature sensor has a nonlinearity behavior nature in its output response but it requires a linear behavior output with accepts approximation in accuracy level, noise and measurement errors. Therefore, neural network topology is proposed with five main steps algorithm to reduce the effected noise and minimize the measured errors. Matlab simulation results and laboratory work (LabVIEW) validate the preciously of the proposed cognitive neural linearization algorithm in terms of calculating the temperature from the different types of thermocouples temperature sensors and minimizing the error between the actual temperature output and neural linearization temperature output as well as overcoming the problem of the over learning in the linearization model with the minimum number of fitness evaluation for the learning algorithm..

– Thermocouple Temperature Sensors --- Neural Network Topology --- Slice Genetic Algorithm --- Matlab --- LabVIEW.