Michael T. DiRenzo

Microwatt embedded processor platform for medical system-on-chip applications

A medical system-on-chip (SoC) that integrates an ARM Cortex-M3 processor is presented. Ultra-low power operation is achieved via 0.5–1.0 V operation, a 28 fW/bit fully differential subthreshold 6T SRAM, a 90%-efficient DC-DC converter, and a 100-nJ fast Fourier transform (FFT) accelerator to reduce processor workload. Using a combination of novel circuit design, system architecture, and SoC implementation, the first sub-microwatt per channel electroencephalograph (EEG) seizure detection is demonstrated.

Microwatt Embedded Processor Platform for Medical System-on-Chip Applications

Battery life specifications drive the power consumption requirements of integrated circuits in implantable, wearable, and portable medical devices. In this paper, we present an embedded processor platform chip using an ARM Cortex-M3 suitable for mapping medical applications requiring microwatt power consumption. Ultra-low-power operation is achieved via 0.5-1.0 V operation, a 28 fW/bit fully differential subthreshold 6T SRAM, a 90%-efficient DC-DC converter, and a 100-nJ fast Fourier transform (FFT) accelerator to reduce processor workload. Using a combination of novel circuit design, system architecture, and SoC implementation, the first sub-microwatt per channel electroencephalograph (EEG) seizure detection is demonstrated.

Nonlinear induced disturbance rejection in inertial stabilization systems

A frequent problem in inertial stabilization control systems is the rejection of disturbances associated with moving components. Very often such disturbances are nonlinear and time varying. A prime example is the relative motion of components within a gimbal; in this case, nonlinear bearing friction induces a destabilizing torque from base motion to the component being stabilized. This paper presents a linear quadratic Gaussian algorithm, based on a simple first-order linear stochastic differential equation, for estimating and compensating in real time a particular class of disturbances that can be modeled as a plus or minus unknown slowly changing random value which is characterized by nonlinear Coulomb friction. Results of computer simulations testing the control algorithm are presented along with actual measurements from a laboratory brassboard system. The results reveal a noteworthy improvement in disturbance rejection as compared with a conventional PI controller with notch filters.

Switched reluctance motor control techniques

This paper provides a basic tutorial on SRMs, how they are controlled, and potential applications. A review of the equations governing the operation of the SRM is given and the operation of the SRM is described. Current control, commutation algorithms, and techniques for reducing torque ripple and linearizing the SRM torque response are discussed. Algorithms which allow motor operation without aid of a shaft position sensor are introduced.

Self-trained commutation algorithm for an SR motor drive system without position sensing

For a variety of reasons, eliminating the rotor position sensor typically used to operate a switched reluctance (SR) motor is desirable. In this paper, the authors describe a method for the commutation of an SR motor requiring no rotor position sensor and no detailed prior knowledge of the motors magnetic characteristics. The method employs a calibration routine to learn the magnetization characteristics of each motor phase at its aligned position, From this information, the flux-current characteristics at some appropriate switching angle can be approximated. Commutation is accomplished by estimating the flux-linked in an active phase and comparing the estimate to the flux approximated for the switching angle. This method is particularly well suited for relatively heavy duty loading, such as a fan. Experimental results are presented which compare the position sensorless technique to a conventional control which uses position feedback.

Nonlinear-induced disturbance rejection in inertial stabilization systems

A frequent problem in inertial stabilization control systems is the rejection of disturbances associated with moving components. Very often such disturbances are nonlinear and time varying. A prime example is the relative motion of components within a gimbal; in this case, nonlinear bearing friction induces a de-stabilizing torque from base motion to the component being stabilized. This paper presents an LQG algorithm, based on a simple first order linear stochastic differential equation, for estimating and compensating in real time a particular class of disturbances that can be modeled as a plus or minus unknown slowly changing random value such as is characterized by nonlinear Coulomb friction. Results of computer simulations testing the control algorithm are presented along with actual measurements from a laboratory brassboard system. The results reveal a noteworthy improvement in disturbance rejection as compared with a conventional PI controller with notch filters.

Mode estimation and adaptive feedforward control for stabilization of a flexible gun tube

In this paper we describe an approach for designing a pointing and stabilization system for an unbalanced, flexible gun. Our approach is based upon classical control techniques as well as system identification and adaptive feedforward techniques. Adaptive algorithms identify the flexible modes of the system and estimate the dynamics unbalance. This information is used to update the control law in order to improve the stabilization accuracy of the system.