12,162 research outputs found
Designers manual for circuit design by analog/digital techniques Final report
Manual for designing circuits by hybrid compute
Tensor Computation: A New Framework for High-Dimensional Problems in EDA
Many critical EDA problems suffer from the curse of dimensionality, i.e. the
very fast-scaling computational burden produced by large number of parameters
and/or unknown variables. This phenomenon may be caused by multiple spatial or
temporal factors (e.g. 3-D field solvers discretizations and multi-rate circuit
simulation), nonlinearity of devices and circuits, large number of design or
optimization parameters (e.g. full-chip routing/placement and circuit sizing),
or extensive process variations (e.g. variability/reliability analysis and
design for manufacturability). The computational challenges generated by such
high dimensional problems are generally hard to handle efficiently with
traditional EDA core algorithms that are based on matrix and vector
computation. This paper presents "tensor computation" as an alternative general
framework for the development of efficient EDA algorithms and tools. A tensor
is a high-dimensional generalization of a matrix and a vector, and is a natural
choice for both storing and solving efficiently high-dimensional EDA problems.
This paper gives a basic tutorial on tensors, demonstrates some recent examples
of EDA applications (e.g., nonlinear circuit modeling and high-dimensional
uncertainty quantification), and suggests further open EDA problems where the
use of tensor computation could be of advantage.Comment: 14 figures. Accepted by IEEE Trans. CAD of Integrated Circuits and
System
Robust nonlinear control of vectored thrust aircraft
An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations
Analog, hybrid, and digital simulation
Analog, hybrid, and digital computerized simulation technique
Real time flight simulation methodology
An example sensitivity study is presented to demonstrate how a digital autopilot designer could make a decision on minimum sampling rate for computer specification. It consists of comparing the simulated step response of an existing analog autopilot and its associated aircraft dynamics to the digital version operating at various sampling frequencies and specifying a sampling frequency that results in an acceptable change in relative stability. In general, the zero order hold introduces phase lag which will increase overshoot and settling time. It should be noted that this solution is for substituting a digital autopilot for a continuous autopilot. A complete redesign could result in results which more closely resemble the continuous results or which conform better to original design goals
Mixed-signal CNN array chips for image processing
Due to their local connectivity and wide functional capabilities, cellular nonlinear networks (CNN) are excellent candidates for the implementation of image processing algorithms using VLSI analog parallel arrays. However, the design of general purpose, programmable CNN chips with dimensions required for practical applications raises many challenging problems to analog designers. This is basically due to the fact that large silicon area means large development cost, large spatial deviations of design parameters and low production yield. CNN designers must face different issues to keep reasonable enough accuracy level and production yield together with reasonably low development cost in their design of large CNN chips. This paper outlines some of these major issues and their solutions
Hybrid computer Monte-Carlo techniques
Hybrid analog-digital computer systems for Monte Carlo method application
Beyond Simulation: Computer Aided Control System Design Using Equation-Based Object Oriented Modelling for the Next Decade
After 20 years since their birth, equation-oriented and object-oriented modelling techniques and tools are now mature, as far as solving simulation problems is concerned. Conversely, there is still much to be done in order to provide more direct support for the design of advanced, model-based control systems, starting from object-oriented plant models. Following a brief review of the current state of the art in this field, the paper presents some proposals for future developments: open model exchange formats, automatic model-order reduction techniques, automatic derivation of simplified transfer functions, automatic derivation of LFT models, automatic generation of inverse models for robotic systems, and support for nonlinear model predictive control
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