الفهرس 
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Abstract
The present work introduced two proposed Genetic and Neuro-Genetic control Algorithms for controlling Multi Input Multi Output systems, where many of these systems are suffering from parameters variation and the effect of the external disturbances, which cannot be overcome by the traditional control theory. Two cases have been studied : the first is Permanent Magnet Synchronous Motor, and the second is Continuous Stirred Tank Reactor, which is more complex and highly nonlinear. This thesis is subdivided into six-chapters. Computer simulation was used to implement the proposed algorithms for controlling Permanent Magnet Synchronous Motor speed and Continuous Stirred Tank Reactor ’s temperature. The external disturbances are about ± 20% of the steady state value (SSV) of the system. Traditional controllers as Proportional (P), Proportional Integral (PI), and Proportional Integral and Derivative (PID) were used. Those controllers were unable to overcome effect of the external disturbances ; In contrast, the new proposed control algorithms were effective in overcoming the effect of the external disturbances. Comparative analysis between the results of the proposed algorithms and the traditional controllers showed the superiority and effectiveness of the proposed algorithms compared with traditional controllers. Another comparison between the simulation results of proposed algorithms and those of controllers proposed in previous researches, showed the superiority and effectiveness of the proposed algorithms.