Planar Array Radiation Pattern Synthesis Using Relative Elements Axial Rotation

Far-field pattern synthesis of small antenna arrays is a nontrivial problem. Typically radiation patterns are required to exhibit low sidelobe levels, whilst maintaining the ability to scan the main beam in space. Mutual coupling is a pertinent problem when the number of antenna elements is small, often precluding the use of conventional tapering algorithms. In this paper a technique previously employed to compensate for mutual coupling in linear arrays is extended to include small planar antenna arrays. The method consists of the calculation of the coupling coefficients between the array elements, which are then formed into a matrix and used to compensate for the effects of mutual coupling. It is then shown that this method is not suitable for all planar array configurations and a new technique is developed which allows the calculation of coupling matrices for these element configurations. Measured data from a small planar antenna array is presented, with the outlined methods employed to produce low sidelobe sum and difference beams.

Pattern synthesis of non-uniform elliptical antenna arrays is presented in this paper. Only the element positions of the antenna arrays are optimized by the combination of differential evolution (DE) and invasive weed optimization (IWO) to reduce the peak side lobe level (PSLL) of the radiation pattern. In order to avoid the overlap of the array elements, the minimum spacing of the adjacent elements is constrained. Also, the beam width of the radiation pattern can be constrained effectively. Three elliptical antenna arrays that have 8, 12, and 20 elements are investigated. The synthesis results show that the introduced method can present a good side lobe reduction for the radiation pattern. Compared with other optimization methods, the method proposed in this paper can obtain better performance.

An efficient search technique based on a touring ant colony optimization algorithm is presented for the shaped-beam pattern synthesis of a linear antenna array. The element excitations of equally spaced array and the element positions of uniformly excited array are determined to closely approximate the desired pattern. In the touring ant colony optimization algorithm, the frequency memory feature of tabu search is used. Illustrative examples of cosecant, flat-topped and pencil beam patterns are given to verify the validity and accuracy of the technique.

A flexible search technique based on a tabu search algorithm is presented for the shaped‐beam pattern synthesis of linear antenna arrays. To synthesize a desired pattern, element excitations and/or positions are optimally determined. Examples of cosecant, flat‐topped, and pencil beam patterns are given to illustrate the achievable performance. © 2002 Wiley Periodicals, Inc. Microwave Opt Technol Lett 36: 16–20, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.10657

Planar antenna array design is one of the most important electromagnetic optimization problems of current interest. This paper introduces a recently developed metaheuristic algorithm, known as the Invasive Weed Optimization (IWO), to the pattern synthesis of planar antenna arrays with desired pattern nulls and sidelobe level by amplitude-only and position-only optimization. The steps in the problem formulation are presented along with a design example that illustrates the performance of the IWO algorithm. Three examples have been presented and solved. Simulation results are proposed to compare with published ones to verify the efiectiveness of the IWO algorithm for planar arrays.

In this paper, we present a comprehensive and in-depth investigation on the optimization of Proportional-Integral (PI) controller tuning for achieving stability and desired overshoot in the step response. The main objective of this study is to compare the effectiveness of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) techniques in finding the optimal parameters for the PI controller. The PI controller is a widely used control algorithm that plays a crucial role in many industrial processes. Its tuning greatly affects the system's performance, particularly in terms of stability and overshoot. Therefore, finding the optimal tuning parameters is of utmost importance. To address this optimization problem, we propose the utilization of two popular metaheuristic algorithms, GA and PSO. These algorithms are known for their ability to efficiently search through large solution spaces and find near-optimal solutions. By applying these algorithms to the PI controller tuning problem, we aim to determine which technique yields better results in terms of stability and overshoot tuning. In our comparative study, we provide a detailed explanation of both GA and PSO algorithms, focusing on their working principles and mathematical formulations. We also describe how these algorithms can be applied to the PI controller tuning problem. Furthermore, we highlight the key differences between GA and PSO, shedding light on their strengths and weaknesses. To assess the performance of GA and PSO, we conduct several experiments using different benchmark functions and step response models. We measure the stability and overshoot metrics for various parameter settings obtained through GA and PSO. By thoroughly analyzing the obtained results, we draw meaningful conclusions regarding the effectiveness of each technique. Our findings demonstrate that both GA and PSO exhibit promising results in optimizing PI controller tuning. These observations provide valuable insights and guidelines for choosing the appropriate algorithm based on specific control requirements. In conclusion, this comparative study is thought to contribute to the field of control systems engineering by offering a comprehensive analysis of GA and PSO techniques in the context of PI controller tuning. By highlighting their strengths and weaknesses, it is aimed to provide researchers and practitioners with valuable information for making informed decisions when optimizing control parameters for stability and overshoot reduction purposes.

Beam synthesis remains one of the most difficult problems for an antenna array designer, this task being made more difficult when one limits the number of elements to a handful. Pattern synthesis in planar arrays is often achieved by the sampling of a continuous aperture distribution at the element locations. In the case of arrays of limited numbers of elements this produces errors that can unacceptably distort the radiation pattern. When one also then considers the effects of mutual coupling between the antenna elements, the application of ideal element weights derived in this way are no longer valid. In the paper a technique is presented, using the concept of retrodirective beams, that can achieve a low sidelobe beam from a continuous distribution on a circular aperture. The theory is then extended to include a planar array of antenna elements. This is achieved by the addition of retrodirective beams to the uniform beam pattern of the array. Measured data is presented for a small planar array antenna using the derived method. A method for correction of the element weights, to minimise the effects of mutual coupling, producing low sidelobe radiation patterns is then applied. No knowledge of the antenna array's coupling coefficients are required.

In the modern world with the advancement of technologies in solid-state electronics, the use of power electronics devices is playing a crucial role in the conversion and control of electric power. By using these innovative devices in 3-phase voltage source inverters, precise and smooth control over the conversion of electrical power can be achieved. But on the other hand, this leads to Total Harmonic Distortion (THD) leading to an adverse effect on the overall system performance. The optimization technique has emerged as a newly popular method for selective harmonic elimination. The main focus of this paper is on simulation study for harmonic analysis of 3-phase voltage source inverter by using particle swarm optimization (PSO) technique. By considering the expression of THD as an objective function, optimization is achieved in the PSO algorithm. This paper also discusses the harmonic analysis of the proposed inverter for conventional PWM techniques such as sinusoidal pulse width modulation (SPWM) and trapezoidal pulse width modulation (TPWM). The harmonic spectrum of the output voltage of the inverter is compared for SPWM, TPWM, and PSO by using MATLAB. From THD analysis, it is observed that PSO gives better performance than other conventional techniques.

This paper presents performance comparative study of various particle swarm optimization (PSO) techniques for the placement of generator units in the distributed generation (DG) system. For the installation of generator units in the distributed generation system, it is very important to know the generator sizing and its placement in the network system for reducing the line losses and hence the cost. Various PSO techniques such as Canonical PSO, Hierarchical PSO (HPSO), Time varying acceleration coefficient (TVAC) PSO, Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients (HPSO-TVAC), Stochastic inertia weight (Sto-IW) PSO and Time varying inertia weight (TVIW) PSO have been used for comparative study. Here the main objective function (OF) is to minimize the system cost. These techniques have been tested on the standard IEEE-14 bus, IEEE-30 bus and IEEE-57 bus network system by the use of MATLAB software.

In this paper, a novel method for pattern synthesis of antenna arrays based on dynamic cooperative gray wolf optimizer algorithm is proposed. By introducing the dynamic cooperative weight factor, positions of the three leader wolves are weighted, and then the positions of next generation are updated. The improved algorithm emphasizes the leading role of the leader wolf, but also does not neglect the cooperation between the leadership wolves. Global optimal and local optimal can be well balanced and converge to the optimal solution quickly and effectively. The proposed algorithm has been successfully used to reduce the sidelobe level and form deep null steerings at designated directions which meets the design requirements.

Far-Field Radiation Pattern Synthesis of Elliptical Antenna Arrays Using GA and PSO

PurposeThis paper aims to employ particle swarm optimization (PSO) technique for optimum design of single‐phase induction motor (SPIM) on the basis of maximizing the efficiency of the motor simultaneously satisfying a set of performance constraints.Design/methodology/approachThe design problem of a SPIM is presented as a nonlinear optimization problem on the basis of maximizing the efficiency of the motor. A set of performance constraints are imposed in the optimization procedure. Particle swarm optimization technique is used as an optimization tool for obtaining the motor dimensions corresponding to maximum efficiency. Incorporation of PSO as a derivative free optimization technique in solving SPIM optimum design problem significantly relieves the assumptions imposed on the optimized objective function.FindingsThis approach has been applied to two sample motors and the results are compared with the evolutionary programming (EP) results. It is observed that the proposed approach is effective and robust.Originality/valueThe fields of application of SPIMs are expanding day by day. The emphasis on energy conservation demands an improvement of the efficiency of single‐phase induction motors. Hence, the design optimization of these motors with efficiency as objective function assumes great importance.

There has been ongoing experiments on a two-wheeled self-balancing robot for several years, and it is almost similar to the model of an inverted pendulum on a cart. The presented paper describes the model, design, working and simulation of a two-wheeled self-balancing robot. Properties of the system under study are extremely non-linear. Moreover, there is a great deal of instability in the controller of proposed system. To improve the stability of mobile robots, this paper introduces fractional order PID (FOPID) or PI <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">λ</sup> D <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</sup> controller for a non-linear and high-order system and compares it with the conventional PID. FOPID controller is designed specifically to adjust the parameters of the system more accurately according to desired specifications. The factorrs of the considered controller are optimized using both Nelder-Mead (N-M) technique and Particle Swarm Optimization (PSO) technique. The results obtained by N-M technique are compared with those of PSO technique. N-M tuned FOPID controller significantly improves the quality of controller in contrast to PSO technique. Simulation results also indicate that Nelder-Mead tuned FOPID is a better and more stable controller as compared to classical PID or PSO tuned FOPID, for a non-linear system like a two-wheeled self-balancing robot.

This paper introduces a shaped radiation pattern from 2-D planar and 3-D conformal antenna arrays based on phase-only synthesis technique using particle swarm optimization. The 2-D planar sunflower and 3-D conformal arrays, cylindrical helical and spherical helical arrays are investigated. Different radiation pattern constrains are employed in the synthesis process for beam shaping. A single narrow and flat-top beams are estimated using the 2-D planar sunflower array. Using the same phase distribution, two narrow beams and flat-top beams are estimated in different planes. A 3-D conformal arrays, cylindrical and spherical helical arrays consist of four orthogonally oriented arms are proposed. The proposed structure introduces four independent beams in four different directions separately. Also, simultaneous four beams are obtained. The side lobe level (SLL) of the synthesized patterns is optimized below -17 dB. The analysis was implemented in a computer using home programmed MATLAB code which is based on the array theory formulation.

Investigating a hybrid of Tone-Model and Particle Swarm Optimization techniques in transcribing polyphonic guitar sound