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Table of Contents
Metamaterials, Characteristics, Design and Microwave Applications
System Identification and Neural Network Based PID Control of Servo - Hydraulic Vehicle Suspension System
Error Source Identification and Stability Test of a Precision Capacitance Measurement System
Metamaterials, Characteristics, Design and Microwave Applications by B. Jokanovic, R.H. Geschke, T.S. Beukman and V. Milosevic
Abstract: We present an overview of unique properties of metamaterials, especially negative index materials. These have allowed novel applications, concepts and devices to be developed in the past decade. A review of the progress made in this field is presented with a focus on microwave devices and applications in wireless communications. Since a metamaterial can be regarded as a continuous medium with effective dielectric permittivity and effective magnetic permeability, we present the procedure for the extraction of effective electromagnetic parameters for a guided wave structure with split-ring resonators. As examples, our own designs of bandpass and triple-band filters, which are constructed using metamaterial-inspired resonator elements, are presented and discussed.
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System Identification and Neural Network Based PID Control of Servo - Hydraulic Vehicle Suspension System by O.A. Dahunsi, J.O. Pedro and O.T. Nyandoro
Abstract: This paper presents the system identification and design of a neural network based Proportional, Integral and Derivative (PID) controller for a two degree of freedom (2DOF), quarter-car active suspension system. The controller design consists of a PID controller in a feedback loop and a neural network feedforward controller for the suspension travel to improve the vehicle ride comfort and handling quality. Nonlinear dynamics of the servo-hydraulic actuator is incorporated in the suspension model. A SISO neural network (NN) model was developed using the input-output data set obtained from the mathematical model simulation. Levenberg-Marquardt algorithm was used to train the NN model. The NN model achieved fitness values of 99.98%, 99.98% and 99.96% for sigmoidnet, wavenet and neuralnet neural network structures respectively. The proposed controller was compared with a constant gain PID controller in a suspension travel setpoint tracking in the presence of a deterministic road disturbance. The NN-based PID controller showed better performances in terms of rise times and overshoots.
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Error Source Identification and Stability Test of a Precision Capacitance Measurement System by S. Nihtianov and X. Guo
Abstract: An experimental study is reported for low-frequency noise behavior and identifying the error source of a capacitance measurement system. A test set-up and a special test strategy for this measurement were applied to differentiate between the kinds of external low-frequency interference. The set-up and strategy allowed accurate measurement of the low-frequency component of the intrinsic input noise of the capacitance measurement system. The capacitance measurement system reported was found in the study along with an extremely low value for the low-frequency (1/f) noise with a corner frequency of 2 mHz, and a very high thermal stability of 2 ppm/K, which confirm the design target of this capacitance measurement system.
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