3-phase induction motors are widely used in industrial applications such as pumps, blowers, compressors, conveyors, etc. In addition, single-phase motors also have domestic use. For this reason, the design of the induction motor is of great importance. During the design, according to the parameters given as input, there are many situations that are contradictory to each other in order to achieve the goal. For example, if high efficiency is required, the motor size and the price will increase, and if lower price is required, other performance characteristics should be ignored. In the practical design of an induction motor, the designer has to comply with a number of constraints because of the large number of input variables. For this reason manual calculation becomes a very long and difficult process. To overcome this tiresome process, it is necessary to create a computer aided program or simulation model to determine the induction motor design parameters. In induction motor design, many parameters directly affect motor performance. Therefore, the selection of these parameters is of great importance. The C0 coefficient, which takes place in the first steps of the design process, also has a great influence on the motor design. In this paper, a program for optimizing design of 3-phase induction motors written in MATLAB is presented. The structure of the program is modular and therefore can be modified for the various requirements of the induction motor design. C0 constant (output coefficient), one of the design parameters, also varies with some other parameters. The most important ones are the specific electrical loading coefficient (A1) and the specific magnetic loading coefficient (Bav), making dramatic effect on the output coefficient. The effect of the variation of the C0 constant on the performance of the induction motor was investigated in the study. Stator inner and outer diameter, stack length, stator and rotor slot parameters, equivalent circuit parameters, losses and efficiency was obtained according to the change of Bav and A1 values. The obtained results are given and interpreted in tables and graphs.

Generally three phase motors are better than single phase motors but three phase system cannot be used in many applications for house. Especially single phase motors are used in city centers because of structure of the single phase feeder system. In general, small powered single phase motors in the range of 0.18-1.5 kW are used in small workplaces, portable hand looms, homes, fans, kitchen equipment, vacuum cleaner, drills and etc. In this paper, characteristic performance features of the single phase electrical machines that named universal motors, single phase induction motors (IM), shaded pole motors and 24 V permanent magnet direct current (PMDC) motors are studied. These motors are grouped in special electrical machines. Operational principles of the motors, areas of the usages and performance characteristics are given comparatively. Tests are conducted for motors. Current, voltage, revolution per minute, powers are given in graphs. ANSYS Maxwell programme is used for computer aided design of transient motor performances. Electrical characteristics of the motors are simulated with programme. Dynamical transient analysis of the motors are conducted respectively. It should not be forgotten that the data, graphs and tables obtained will help the students to learn the motors better in the Special Electrical Machines Course and Laboratory.

An inverted pendulum system is designed, implemented, and stabilized on a short path. Proportional-Integral-Differential (PID) control algorithm is embedded on a digital signal processing card to achieve the stabilization in a real time. DC-motor dynamics of the inverted pendulum system and cart-track friction are unknown and their effects are taken into account by the incremental duty cycle approach. Experimental tests, conducted for various experimental conditions, have shown that the inverted pendulum system reached the desired state in the presence of friction and various external disturbances. Bu çalışmada, kısa bir hat üzerinde ters sarkaç sistemi tasarlanıp, uygulanmış ve kararlı bir şekilde kontrol edilmiştir. Kararlılığı sağlamak için gerçek zamanlı sayısal bir işaret işleme kartına Oransal-İntegral-Diferansiyel (PID) kontrol algoritması yerleştirilmiştir. Ters sarkaç sisteminin DC motor dinamiği ve araç yolu sürtünmesi bilinmemektedir ve sürtünme etkileri arttırılan serbest çevrim yaklaşımı ile dikkate alınmıştır. Sürtünme ve dış gürültü varlığında farklı deney koşulları için yapılan testler ters sarkacın istenen denge durumuna ulaştığını göstermiştir.

The transition to renewable energy, mainly via the use of PV (photovoltaic) systems, is essential for addressing global concerns related to climate change, energy security, and sustainability. Conventional Maximum Power Point Tracking (MPPT) techniques, particularly Perturb and Observe (P&O) and Incremental Conductance methods, rely on fixed-step gradient-based control, which leads to steady-state oscillations around the maximum power point, slow convergence during rapid irradiance and temperature variations, and inaccurate tracking under partial shading conditions. These technical limitations often cause the controller to deviate from the global maximum power point, resulting in reduced dynamic efficiency, increased power losses, and degraded power quality in practical PV applications. To overcome these limitations, this research proposes a hybrid optimization model that incorporates ACO (Ant Colony Optimization) and an ANN (Artificial Neural Network) to enrich the effectiveness of MPPT in PV systems. The proposed model is designed to dynamically adapt to variations in solar irradiance and temperature, effectively addressing the inadequacies present in the conventional techniques and also improving the MPPT efficiency in PV systems. By leveraging the unique strengths of both ACO and ANN, the model significantly improves energy extraction and also ensures robustness against environmental fluctuations. Simulation results demonstrate that the proposed ACO–ANN MPPT framework achieves a total harmonic distortion (THD) of 1.39%, representing a reduction of approximately 34–70% compared to conventional and recent AI-based MPPT techniques, while simultaneously delivering higher voltage stability, faster convergence, and increased maximum power extraction. This contribution is vital in paving the way for future advancements in renewable energy systems and provides a more reliable approach to solar power optimization, which can greatly aid in achieving sustainable energy goals.