SUMMARYArtificial neural networks (ANNs) have been often used for engineering design problems. In this work, an inverse model of a reconfigurable N-shaped microstrip patch antenna which is formed by ANN is considered to find design parameters. For this task, knowledge-based response correction consists of two steps, which include generating response using multilayer perceptron as a first step and correcting this response using knowledge based methods such as source difference, prior knowledge input, and prior knowledge input with difference as a second step. The proposed antenna has four states of operation controlled by two Positive-Intrinsic-Negative (PIN) diodes with ON/OFF states. The two-step ANN models are inversely trained using the optimum of the resonant frequency parameter as the input and the physical dimensions of the proposed antenna as outputs of the multilayer perceptron. The outputs and, in some methods, the input parameters of the multilayer perceptron are sent as input to the knowledge-based models while the obtained outputs from the two steps are the results of the new physical dimensions of the redesigned reconfigurable antenna that will be compared and analyzed. This input/output complexity of the proposed reconfigurable antenna allows an accurate and fast inverse model to be developed with less training data. Users may use this antenna and its ANN models to develop new products in the market where any frequency in the operating region can be given to the input to result an appropriate form of the new reconfigurable antenna.

This paper presents the use of inverse artificial neural networks (ANNs) to develop and optimize a reconfigurable 5-fingers shaped microstrip patch antenna. New solutions are produced by using three accurate prior knowledge inverse ANNs with sufficient amount of training data where the frequency information is incorporated into the structure of ANNs. The proposed antenna can operate with four modes, which are controlled by two PIN diode switches with ON/OFF states, and it resonates at multiple frequencies between 2-7 GHz. The complexity of the input/output relationship is reduced by using prior knowledge. Three independent methods of incorporating knowledge in the second step of the training process with a multilayer perceptron (MLP) in the first step are demonstrated and their results are compared to EM simulation.

In surrogate‐based optimisation methods, computationally burden yet precise fine model is utilised alongside less accurate however quick coarse model to decrease the general computational exertion. Surrogate‐based optimisation methods are firstly applied to reconfigurable antenna design problems in this work. Space mapping (SM) with inverse difference method enables productive procedure to decrease computational exertion while enhancing the convergence. Inverse difference mapping is constituted by difference knowledge that is obtained by input and output of the problem space. In addition, inverse coarse model that is obtained by feed forward multi‐layer perceptron can generate necessary knowledge to form inverse mapping. This mapping is used to eliminate the direct optimisation‐based parameter extraction process. The efficiency of SM with inverse difference technique will be demonstrated by reconfigurable antenna design examples in terms of their convergence and accuracy. Moreover, this technique will be compared to aggressive SM with regard to the convergence efficiency.

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There are many applications in communication and microwave hyperthermia are desirable where small lateral size and narrow band properties. Circular microstrip patch and the Archimedean spiral antenna were combined to affect positively on the performance of the exited antenna. The design includes the selection carefully of the dielectric material, the radius of circular microstrip patch, the empty space through the turned microstrip spiral, the width of the spiral and the number turns of the spiral. The simulation and the experimental results confirm that the small size of combined spiral and microstrip patch antennas can be operated over a wide range of frequencies. In addition to the techniques that are applied to obtain the results such as directivity, Half‐Power Beamwidth, S‐Parameters, and stands for Voltage Standing Wave Ratio (VSWR) for the new shape. The outputs are compared and analyzed with a numerical formulation for spiral and patch antennas and measured.