Methods for synthesis of multiple-input translinear element networks

Translinear circuits are circuits in which the exponential relationship between the output current and input voltage of a circuit element is exploited to realize various algebraic or differential equations. This thesis is concerned with a subclass of translinear circuits, in which the basic translinear element, called a multiple-input translinear element (MITE), has an output current that is exponentially related to a weighted sum of its input voltages. MITE networks can be used for the implementation of the same class of functions as traditional translinear circuits. The implementation of algebraic or (algebraic) differential equations using MITEs can be reduced to the implementation of the product-of-power-law (POPL) relationships, in which an output is given by the product of inputs raised to different powers. Hence, the synthesis of POPL relationships, and their optimization with respect to the relevant cost functions, is very important in the theory of MITE networks. In this thesis, different constraints on the topology of POPL networks that result in desirable system behavior are explored and different methods of synthesis, subject to these constraints, are developed. The constraints are usually conditions on certain matrices of the network, which characterize the weights in the relevant MITEs. Some of these constraints are related to the uniqueness of the operating point of the network and the stability of the network. Conditions that satisfy these constraints are developed in this work. The cost functions to be minimized are the number of MITEs and the number of input gates in each MITE. A complete solution to POPL network synthesis is presented here that minimizes the number of MITEs first and then minimizes the number of input gates to each MITE. A procedure for synthesizing POPL relationships optimally when the number of gates is minimal, i.e., 2, has also been developed here for the single--output case. A MITE structure that produces the maximum number of functions with minimal reconfigurability is developed for use in MITE field--programmable analog arrays. The extension of these constraints to the synthesis of linear filters is also explored, the constraint here being that the filter network should have a unique operating point in the presence of nonidealities. Synthesis examples presented here include nonlinear functions like the arctangent and the gaussian function which find application in analog implementations of particle filters. Synthesis of dynamical systems is presented here using the examples of a Lorenz system and a sinusoidal oscillator. The procedures developed here provide a structured way to automate the synthesis of nonlinear algebraic functions and differential equations using MITEs.Ph.D.Committee Chair: Anderson, David; Committee Member: Habetler, Thomas; Committee Member: Hasler, Paul; Committee Member: McClellan, James; Committee Member: Minch, Bradle

Synthesis of Translinear Analog Signal Processing Systems

Even in the predominantly digital world of today, analog circuits maintain a significant and necessary role in the way electronic signals are generated and processed. A straightforward method for synthesizing analog circuits would greatly improve the way that analog circuits are currently designed. In this dissertation, I build upon a synthesis methodology for translinear circuits originally introduced by Bradley Minch that uses multiple-input translinear elements (MITEs) as its fundamental building block. Introducing a graphical representation for the way that MITEs are connected, the designer can get a feel for how the equations relate to the physical circuit structure and allows for a visual method for reducing the number of transistors in the final circuit. Having refined some of the synthesis steps, I illustrate the methodology with many examples of static and dynamic MITE networks. For static MITE networks, I present a squaring reciprocal circuit and two versions of a vector magnitude circuit. A first-order log-domain filter and an RMS-to-DC converter are synthesized showing two first-order systems, both linear and non-linear. Higher order systems are illustrated with the synthesis of a second-order log-domain filter and a quadrature oscillator. The resulting circuits from several of these examples are combined to form a phase-locked loop (PLL). I present simulated and experimental results from many of these examples. Additionally, I present information related to the process of programming the floating-gate charge for the MITEs through the use of Fowler-Nordheim tunneling and hot-electron injection. I also include code for a Perl program that determines the optimum connections to minimize the total number of MITEs for a given circuit.NSF Career award CCR-998462

Large scale reconfigurable analog system design enabled through floating-gate transistors

This work is concerned with the implementation and implication of non-volatile charge storage on VLSI system design. To that end, the floating-gate pFET (fg-pFET) is considered in the context of large-scale arrays. The programming of the element in an efficient and predictable way is essential to the implementation of these systems, and is thus explored. The overhead of the control circuitry for the fg-pFET, a key scalability issue, is examined. A light-weight, trend-accurate model is absolutely necessary for VLSI system design and simulation, and is also provided. Finally, several reconfigurable and reprogrammable systems that were built are discussed.Ph.D.Committee Chair: Hasler, Paul E.; Committee Member: Anderson, David V.; Committee Member: Ayazi, Farrokh; Committee Member: Degertekin, F. Levent; Committee Member: Hunt, William D

Low Power Adaptive Circuits: An Adaptive Log Domain Filter and A Low Power Temperature Insensitive Oscillator Applied in Smart Dust Radio

This dissertation focuses on exploring two low power adaptive circuits. One is an adaptive filter at audio frequency for system identification. The other is a temperature insensitive oscillator for low power radio frequency communication. The adaptive filter is presented with integrated learning rules for model reference estimation. The system is a first order low pass filter with two parameters: gain and cut-off frequency. It is implemented using multiple input floating gate transistors to realize online learning of system parameters. Adaptive dynamical system theory is used to derive robust control laws in a system identification task. Simulation results show that convergence is slower using simplified control laws but still occurs within milliseconds. Experimental results confirm that the estimated gain and cut-off frequency track the corresponding parameters of the reference filter. During operation, deterministic errors are introduced by mismatch within the analog circuit implementation. An analysis is presented which attributes the errors to current mirror mismatch. The harmonic distortion of the filter operating in different inversion is analyzed using EKV model numerically. The temperature insensitive oscillator is designed for a low power wireless network. The system is based on a current starved ring oscillator implemented using CMOS transistors instead of LC tank for less chip area and power consumption. The frequency variance with temperature is compensated by the temperature adaptive circuits. Experimental results show that the frequency stability from 5°C to 65°C has been improved 10 times with automatic compensation and at least 1 order less power is consumed than published competitors. This oscillator is applied in a 2.2GHz OOK transmitter and a 2.2GHz phase locked loop based FM receiver. With the increasing needs of compact antenna, possible high data rate and wide unused frequency range of short distance communication, a higher frequency phase locked loop used for BFSK receiver is explored using an LC oscillator for its capability at 20GHz. The success of frequency demodulation is demonstrated in the simulation results that the PLL can lock in 0.5μs with 35MHz lock-in range and 2MHz detection resolution. The model of a phase locked loop used for BFSK receiver is analyzed using Matlab

On low-power analog implementations of particle filters for target tracking

We propose a low-power, analog and mixed-mode, implementation of particle filters. Low-power analog implementation of nonlinear functions such as exponential and arctangent functions is done using multiple-input translinear element (MITE) networks. These nonlinear functions are used to calculate the probability densities in the particle filter. A bearings-only tracking problem is simulated to present the proposed low-power implementation of the particle filter algorithm

Analog signal processing on a reconfigurable platform

The Cooperative Analog/Digital Signal Processing (CADSP) research group's approach to signal processing is to see what opportunities lie in adjusting the line between what is traditionally computed in digital and what can be done in analog. By allowing more computation to be done in analog, we can take advantage of its low power, continuous domain operation, and parallel capabilities. One setback keeping Analog Signal Processing (ASP) from achieving more wide-spread use, however, is its lack of programmability. The design cycle for a typical analog system often involves several iterations of the fabrication step, which is labor intensive, time consuming, and expensive. These costs in both time and money reduce the likelihood that engineers will consider an analog solution. With CADSP's development of a reconfigurable analog platform, a Field-Programmable Analog Array (FPAA), it has become much more practical for systems to incorporate processing in the analog domain. In this Thesis, I present an entire chain of tools that allow one to design simply at the system block level and then compile that design onto analog hardware. This tool chain uses the Simulink design environment and a custom library of blocks to create analog systems. I also present several of these ASP blocks, covering a broad range of functions from matrix computation to interfacing. In addition to these tools and blocks, the most recent FPAA architectures are discussed. These include the latest RASP general-purpose FPAAs as well as an adapted version geared toward high-speed applications.M.S.Committee Chair: Hasler, Paul; Committee Member: Anderson, David; Committee Member: Ghovanloo, Maysa

Multirate sampled-data yaw-damper and modal suppression system design

A multirate control law synthesized algorithm based on an infinite-time quadratic cost function, was developed along with a method for analyzing the robustness of multirate systems. A generalized multirate sampled-data control law structure (GMCLS) was introduced. A new infinite-time-based parameter optimization multirate sampled-data control law synthesis method and solution algorithm were developed. A singular-value-based method for determining gain and phase margins for multirate systems was also developed. The finite-time-based parameter optimization multirate sampled-data control law synthesis algorithm originally intended to be applied to the aircraft problem was instead demonstrated by application to a simpler problem involving the control of the tip position of a two-link robot arm. The GMCLS, the infinite-time-based parameter optimization multirate control law synthesis method and solution algorithm, and the singular-value based method for determining gain and phase margins were all demonstrated by application to the aircraft control problem originally proposed for this project

Adaptive Log Domain Filters Using Floating Gate Transistors

In this thesis, an adaptive first order lowpass log domain filter and an adaptive second order log domain filter are presented with integrated learning rules for model reference estimation. Both systems are implemented using multiple input floating gate transistors to realize on-line learning of system parameters. Adaptive dynamical system theory is used to derive robust control laws in a system identification task for the parameters of both a first order lowpass filter and a second order tunable filter. The log domain filters adapt to estimate the parameters of the reference filters accurately and efficiently as the parameters are changed. Simulation results for both the first order and the second order adaptive filters are presented which demonstrate that adaptation occurs within milliseconds. Experimental results and mismatch analysis are described for the first order lowpass filter which demonstrates the success of our adaptive system design using this model-based learning method

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0