8,888 research outputs found
Recommended from our members
Automatic synthesis of analog layout : a survey
A review of recent research in the automatic synthesis of physical geometry for analog integrated circuits is presented. On introduction, an explanation of the difficulties involved in analog layout as opposed to digital layout is covered. Review of the literature then follows. Emphasis is placed on the exposition of general methods for addressing problems specific to analog layout, with the details of specific systems only being given when they surve to illustrate these methods well. The conclusion discusses problems remaining and offers a prediction as to how technology will evolve to solve them. It is argued that although progress has been and will continue to be made in the automation of analog IC layout, due to fundamental differences in the nature of analog IC design as opposed to digital design, it should not be expected that the level of automation of the former will reach that of the latter any time soon
Load-independent characterization of trade-off fronts for operational amplifiers
Abstract—In emerging design methodologies for analog integrated circuits, the use of performance trade-off fronts, also known as Pareto fronts, is a keystone to overcome the limitations of the traditional top-down methodologies. However, most techniques reported so far to generate the front neglect the effect of the surrounding circuitry (such as the output load impedance) on the Pareto-front, thereby making it only valid for the context where the front was generated. This strongly limits its use in hierarchical analog synthesis because of the heavy dependence of key performances on the surrounding circuitry, but, more importantly, because this circuitry remains unknown until the synthesis process. We will address this problem by proposing a new technique to generate the trade-off fronts that is independent of the load that the circuit has to drive. This idea is exploited for a commonly used circuit, the operational amplifier, and experimental results show that this is a promising approach to solve the issue
Keep Rollin' - Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots
We show dynamic locomotion strategies for wheeled quadrupedal robots, which
combine the advantages of both walking and driving. The developed optimization
framework tightly integrates the additional degrees of freedom introduced by
the wheels. Our approach relies on a zero-moment point based motion
optimization which continuously updates reference trajectories. The reference
motions are tracked by a hierarchical whole-body controller which computes
optimal generalized accelerations and contact forces by solving a sequence of
prioritized tasks including the nonholonomic rolling constraints. Our approach
has been tested on ANYmal, a quadrupedal robot that is fully torque-controlled
including the non-steerable wheels attached to its legs. We conducted
experiments on flat and inclined terrains as well as over steps, whereby we
show that integrating the wheels into the motion control and planning framework
results in intuitive motion trajectories, which enable more robust and dynamic
locomotion compared to other wheeled-legged robots. Moreover, with a speed of 4
m/s and a reduction of the cost of transport by 83 % we prove the superiority
of wheeled-legged robots compared to their legged counterparts.Comment: IEEE Robotics and Automation Letter
A Powerful Optimization Tool for Analog Integrated Circuits Design
This paper presents a new optimization tool for analog circuit design. Proposed tool is based on the robust version of the differential evolution optimization method. Corners of technology, temperature, voltage and current supplies are taken into account during the optimization. That ensures robust resulting circuits. Those circuits usually do not need any schematic change and are ready for the layout.. The newly developed tool is implemented directly to the Cadence design environment to achieve very short setup time of the optimization task. The design automation procedure was enhanced by optimization watchdog feature. It was created to control optimization progress and moreover to reduce the search space to produce better design in shorter time. The optimization algorithm presented in this paper was successfully tested on several design examples
Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition
Hierarchical uncertainty quantification can reduce the computational cost of
stochastic circuit simulation by employing spectral methods at different
levels. This paper presents an efficient framework to simulate hierarchically
some challenging stochastic circuits/systems that include high-dimensional
subsystems. Due to the high parameter dimensionality, it is challenging to both
extract surrogate models at the low level of the design hierarchy and to handle
them in the high-level simulation. In this paper, we develop an efficient
ANOVA-based stochastic circuit/MEMS simulator to extract efficiently the
surrogate models at the low level. In order to avoid the curse of
dimensionality, we employ tensor-train decomposition at the high level to
construct the basis functions and Gauss quadrature points. As a demonstration,
we verify our algorithm on a stochastic oscillator with four MEMS capacitors
and 184 random parameters. This challenging example is simulated efficiently by
our simulator at the cost of only 10 minutes in MATLAB on a regular personal
computer.Comment: 14 pages (IEEE double column), 11 figure, accepted by IEEE Trans CAD
of Integrated Circuits and System
Neuro-memristive Circuits for Edge Computing: A review
The volume, veracity, variability, and velocity of data produced from the
ever-increasing network of sensors connected to Internet pose challenges for
power management, scalability, and sustainability of cloud computing
infrastructure. Increasing the data processing capability of edge computing
devices at lower power requirements can reduce several overheads for cloud
computing solutions. This paper provides the review of neuromorphic
CMOS-memristive architectures that can be integrated into edge computing
devices. We discuss why the neuromorphic architectures are useful for edge
devices and show the advantages, drawbacks and open problems in the field of
neuro-memristive circuits for edge computing
Smart Microgrids: Overview and Outlook
The idea of changing our energy system from a hierarchical design into a set
of nearly independent microgrids becomes feasible with the availability of
small renewable energy generators. The smart microgrid concept comes with
several challenges in research and engineering targeting load balancing,
pricing, consumer integration and home automation. In this paper we first
provide an overview on these challenges and present approaches that target the
problems identified. While there exist promising algorithms for the particular
field, we see a missing integration which specifically targets smart
microgrids. Therefore, we propose an architecture that integrates the presented
approaches and defines interfaces between the identified components such as
generators, storage, smart and \dq{dumb} devices.Comment: presented at the GI Informatik 2012, Braunschweig Germany, Smart Grid
Worksho
- …