In this paper, a simple 4-dimensional hyperchaotic system is introduced. The proposed system has no equilibria points, so it admits hidden attractor which is an interesting feature of chaotic systems. Another interesting feature of the proposed system is the coexisting of attractors where it shows periodic and chaotic coexisting attractors. After introducing the system, the system is analyzed dynamically using numerical and theoretical techniques. In this analysis, Lyapunov exponents and bifurcation diagrams have been used to investigate chaotic and hyperchaotic nature, the ranges of system parameters for different behaviors and the route for chaos and coexisting attractors regions. In the next part of our work, a synchronization control system for two identical systems is designed. The design procedure uses a combination of simple synergetic control with adaptive updating laws to identify the unknown parameters derived basing on Lyapunov theorem. Microcontroller (MCU) based hardware implementation system is proposed and tested by using MATLAB as a display side. As an application, the designed synchronization system is used as a secure analog communication system. The designed MCU system with MATLAB Simulation is used to validate the designed synchronization and secure communication systems and excellent results have been obtained.

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In this article, a novel three dimensional chaotic systems is presented. An extensive analysis including Lyapunov exponents, dissipation, symmetry, rest points with their properties is introduced. An adaptive tracking control system for the proposed chaos system has been designed. Also, synchronization system for two identical systems has been designed. The simulation results showed the effectiveness of the designed tracking and synchronization control systems.

In this research a system has been designed depending on the optimization intelligence programming problems using the integer genetic algorithm in order to measure the collage efficiency in performing the teaching services. A genetic module has been designed for measuring the college efficiency following two styles: the first one is the integer genetic algorithm for solving direct integer constrained linear optimization and transformation style through transforming the problem from a complex formula into a simple one indirectly and hence through the latter, a zigzag crossover method has been used in the crossover process. Also the mutation function was used. It was obvious that the second method is more efficient than the first method by comparing the results of both.   في هذا البحث تم  تصميم نظام معتمد على مسائل البرمجة الأمثلية باستخدام الخوارزمية الجينية الصحيحة في مجال  التعليم وذلك لغرض قياس كفاءة احد الأقسام العلمية بإحدى الكليات في محافظة البصرة،  في أداء الخدمات التعليمية ، حيث صمم نموذج جيني لقياس كفاءة الكلية.  ويتضمن هذا البحث التفصيل الكامل للنموذج الجيني لتقييم المستوى التعليمي الذي يقدمه  قسم علوم الحاسبات إلى الطلبة المنتسبين وتعريف بعض الرموز المستخدمة في تكوين النموذج . والمعلومات التي يتطلبها هذا النموذج وتشمل درجات التقييم والوقت الكلي المتوفر لأداء الخدمة والوقت اللازم لتقديم الخدمات التعليمية للطالب الواحد ولجميع الدروس.  . وقد تم تنفيذ النموذج الجيني باستخدام الخوارزمية الجينية الصحيحة بأسلوبين الأسلوب المباشر للدوال الصحيحة المشروطة والثاني الأسلوب غير المباشر ( أسلوب التحويل) أي حل المسائل المشروطة بشكل غير مباشر بطريقة مبسطة، وبهذا الأسلوب تم استخدام تقنية  التزاوج المتعرج (Zigzag Crossover Method) وأيضا تم إضافة تعديل على دالة الطفرة (Mutation) وقد ظهر أن الأسلوب الثاني أكثر كفاءةً من الأسلوب الأول من حيث السرعة في  الحصول على النتائج .

In this paper, an optimal speed controller for dc motor is considered using a PID controller and tuned its parameters of gain to offer an optimal solution by using a modified camel algorithm MCA approach. The proposed MCA scheme was applied to solve the difficulty of getting the optimum gains of PID parameters. The MCA has good evolutionary speed with the simple construction of optimization depend on camel searching performance. The characteristics of the MCA algorithm were confirmed by optimizing the gains parameters of proportional, integral, derivative PID controller. The performance of PID-MCA is comparing with a classic PID controller enhanced with GA genetic algorithm optimization method to tune the gain parameters of the speed controller system. It was shown that the utilize of optimization processes indicated better performance for the MCA procedure in term of speed of execution and the size of memory compared with the GA method by applying computer simulations analysis. The proposed scheme has an efficient feature that includes the ease of implementation, good efficiency of computational performances with stable convergence characteristics. The results indicated that the proposed MCA scheme is a useful tool for search ability, produced efficient outcomes compared with the GA optimized method when applied in the proposed system.

In this article, a PD-type iterative learning control algorithm (ILC) is proposed to a nonlinear time-varying system for cases of measurement disturbances and the initial state errors. The proposed control approach uses a simple structure and has an easy implementation. The iterative learning controller was utilized to control a constant current source inverter (CSI) with pulse width modulation (PWM); subsequently the output current trajectory converged the sinusoidal reference signal and provided constant switching frequency. The learning controller's parameters were tuned using particle swarm optimization approach to get best optimal control for the system output. The tracking error limit is achieved using the convergence exploration. The proposed learning control scheme was robust against the error in initial conditions and disturbances which outcome from the system modeling inaccuracies and uncertainties. It could correct the distortion of the inverter output current waveform with less computation and less complexity. The proposed algorithm was proved mathematically and through computer simulation. The proposed optimal learning method demonstrated good performances.