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In this paper a direct adaptive neural-network control strategy for unknown nonlinear systems is presented. The system considered is described by an unknown NARMA model, and a feedforward neural network is used to learn the system. Taking the neural network as a neural model of the system, control signals are directly obtained by minimizing either the instant difference or the cumulative differences between a set point and the output of the neural model. Since the training algorithm guarantees that the output of the neural model approaches that of the actual system, it is shown that the control signals obtained can also make the real system output close to the set point. An application to a flow-rate control system is included to demonstrate the applicability of the proposed method and desired results are obtained.

This paper is focused in the development of a parallel control loop of the angular velocity and torque for Brushless Direct Current (BLDC) motors. This parallel loop is proposed as an improvement for the performance of those cascaded solutions commonly reported in the body of literature of the field. Performance is improved by reducing the steady state error of the speed considerably when compared with the typical cascaded loop solution under a commanded change of torque. In addition, the steady state response of the parallel loop is reached in a shorter time. Simulations were designed to carry out a comparison between both methodologies. The results of these simulations consider only changes in the set point for speed or torque and are reported here. The control signal was applied to a simulated driver using a switching method known as Direct Torque Control of 2 and 3 phases (DTC-2+3P). These preliminary results show that the parallel control loop outperforms the cascaded control of BLDC motors.

A low power RF amplifier circuit for ion trap applications is presented and described. The amplifier is based on a class-D half-bridge amplifier with a voltage mirror driver. The RF amplifier is composed of an RF class-D amplifier, an envelope modulator to ramp up the RF voltage during the ion analysis stage, a detector or amplitude demodulation circuit for sensing the output signal amplitude, and a feedback amplifier that linearizes the steady state output of the amplifier. The RF frequency is set by a crystal oscillator and the series resonant circuit is tuned to the oscillator frequency. The resonant circuit components have been chosen, in this case, to operate at 1 MHz. In testings, the class-D stage operated at a maximum of 78 mW at 1.1356 MHz producing 225 V peak.

In this work a characterization system for high energy-density capacitors is described and demonstrated. Capacitors are being designed using thin-film technology in an attempt to achieve higher energy-density levels by operating the devices at a high voltage. These devices are fabricated from layers of 100 nm aluminum and a layer of polyvinylidene fluoride-hexafluoropropylene on a polyethylene naphthalate plastic substrate. The devices have been designed to store electrical charge at up to 200 V. Characterizations of these devices focus on the measurement of capacitance vs bias voltage and temperature, equivalent series resistance, and charge/discharge cycles. For the purpose of the characterization of these capacitors, an electronic charge/discharge interface was designed and tested.