TACL - a timeshared hybrid system for control laboratories

A generalized control-system model encompassing a wide variety of systems has been programmed on the analog portion of a hybrid computation system. Five terminals with storage oscilloscopes are con nected to the hybrid computer and are serviced on a round-robin basis. The generalized system can be configured in milliseconds to a specific problem by setting the values of the digital coefficient units and switches of the analog system. A library of specific problems is kept on the system's digital disk. Students use the system by referencing a problem in the library and entering parameter values to define the problem from their terminals. The per-solution time varies with the time scale seZect ed, but averages around a few hundred milliseconds. A user-oriented compiler helps the instructor define new problems to be added. Digital values are assigned by the student to select ed parameters of specific problems, and families of curves representing system performance as a function of control settings may be displayed on the student's terminal. The terminals also display digital data and alphanumerical information.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68305/2/10.1177_003754977502500203.pd

Teaching Memory Circuit Elements via Experiment-Based Learning

The class of memory circuit elements which comprises memristive, memcapacitive, and meminductive systems, is gaining considerable attention in a broad range of disciplines. This is due to the enormous flexibility these elements provide in solving diverse problems in analog/neuromorphic and digital/quantum computation; the possibility to use them in an integrated computing-memory paradigm, massively-parallel solution of different optimization problems, learning, neural networks, etc. The time is therefore ripe to introduce these elements to the next generation of physicists and engineers with appropriate teaching tools that can be easily implemented in undergraduate teaching laboratories. In this paper, we suggest the use of easy-to-build emulators to provide a hands-on experience for the students to learn the fundamental properties and realize several applications of these memelements. We provide explicit examples of problems that could be tackled with these emulators that range in difficulty from the demonstration of the basic properties of memristive, memcapacitive, and meminductive systems to logic/computation and cross-bar memory. The emulators can be built from off-the-shelf components, with a total cost of a few tens of dollars, thus providing a relatively inexpensive platform for the implementation of these exercises in the classroom. We anticipate that this experiment-based learning can be easily adopted and expanded by the instructors with many more case studies.Comment: IEEE Circuits and Systems Magazine (in press

Data Acquisition and Control System of Hydroelectric Power Plant Using Internet Techniques

Vodní energie se nyní stala nejlepším zdrojem elektrické energie na zemi. Vyrábí se pomocí energie poskytované pohybem nebo pádem vody. Historie dokazuje, že náklady na tuto elektrickou energii zůstávají konstantní v průběhu celého roku. Vzhledem k mnoha výhodám, většina zemí nyní využívá vodní energie jako hlavní zdroj pro výrobu elektrické energie.Nejdůležitější výhodou je, že vodní energie je zelená energie, což znamená, že žádné vzdušné nebo vodní znečišťující látky nejsou vyráběny, také žádné skleníkové plyny jako oxid uhličitý nejsou vyráběny, což činí tento zdroj energie šetrný k životnímu prostředí. A tak brání nebezpečí globálního oteplování. Použití internetové techniky k ovladání několika vodních elektráren má velmi významné výhody, jako snížení provozních nákladů a flexibilitu uspokojení změny poptávky po energii na straně spotřeby. Také velmi efektivně čelí velkým narušením elektrické sítě, jako je například přidání nebo odebrání velké zátěže, a poruch. Na druhou stranu, systém získávání dat poskytuje velmi užitečné informace pro typické i vědecké analýzy, jako jsou ekonomické náklady, predikce poruchy systémů, predikce poptávky, plány údržby, systémů pro podporu rozhodování a mnoho dalších výhod. Tato práce popisuje všeobecný model, který může být použit k simulaci pro sběr dat a kontrolní systémy pro vodní elektrárny v prostředí Matlab / Simulink a TrueTime Simulink knihovnu. Uvažovaná elektrárna sestává z vodní turbíny připojené k synchronnímu generátoru s budicí soustavou, generátor je připojen k veřejné elektrické síti. Simulací vodní turbíny a synchronního generátoru lze provést pomocí různých simulačních nástrojů. V této práci je upřednostňován SIMULINK / MATLAB před jinými nástroji k modelování dynamik vodní turbíny a synchronního stroje. Program s prostředím MATLAB SIMULINK využívá k řešení schematický model vodní elektrárny sestavený ze základních funkčních bloků. Tento přístup je pedagogicky lepší než komplikované kódy jiných softwarových programů. Knihovna programu Simulink obsahuje funkční bloky, které mohou být spojovány, upravovány a modelovány. K vytvoření a simulování internetových a Real Time systémů je možné použít bud‘ knihovnu simulinku Real-Time nebo TRUETIME, v práci byla použita knihovna TRUETIME.Hydropower has now become the best source of electricity on earth. It is produced due to the energy provided by moving or falling water. History proves that the cost of this electricity remains constant over the year. Because of the many advantages, most of the countries now have hydropower as the source of major electricity producer. The most important advantage of hydropower is that it is green energy, which mean that no air or water pollutants are produced, also no greenhouse gases like carbon dioxide are produced which makes this source of energy environment-friendly. It prevents us from the danger of global warming. Using internet techniques to control several hydroelectric plants has very important advantages, as reducing operating costs and the flexibility of meeting changes of energy demand occurred in consumption side. Also it is very effective to confront large disturbances of electrical grid, such as adding or removing large loads, and faults. In the other hand, data acquisition systems provides very useful information for both typical and scientific analysis, such as economical costs reducing, fault prediction systems, demand prediction, maintenance schedules, decision support systems and many other benefits. This thesis describes a generalized model which can be used to simulate a data acquisition and control system of hydroelectric power plant using MATLAB/SIMULINK and TrueTime simulink library. The plant considered consists of hydro turbine connected to synchronous generator with excitation system, and the generator is connected to public grid. Simulation of hydro turbine and synchronous generator can be done using various simulation tools, In this work, SIMULINK/MATLAB is favored over other tools in modeling the dynamics of a hydro turbine and synchronous machine. The SIMULINK program in MATLAB is used to obtain a schematic model of the hydro plant by means of basic function blocks. This approach is pedagogically better than using a compilation of program code as in other software programs .The library of SIMULINK software programs includes function blocks which can be linked and edited to model. Either Simulink Real-Time library or TrueTime library can be used to build and simulate internet and real time systems, in this thesis the TrueTime library was used.

The development of a hybrid simulator for power system control investigations

Imperial Users onl

Design and testing of a kinetic energy harvester embedded into an oceanic drifter

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A novel Kinetic Energy Harvester (KEH) has been developed for powering oceanic undrogued drifters. It consists on a double pendulum system capable of transforming the wave oscillations into rotation on a flywheel. This rotation is converted into DC current by an electrical generator and further processed by a power management unit (PMU). The PMU includes a “maximum power point tracking” system to maximize energy production by the generator. An oceanic drifter has also been designed to embed the KEH and a custom-made measurement system to perform real sea tests. It counts on an Inertial Measurement Unit to study the motion of the drifter and an embedded measurement system to estimate the rotation speed of the generator and the power at both the input and output of the PMU. A Wi-Fi connection is also included for data transfer at short distances. The generator was firstly characterized at the laboratory; the drifter was then placed on a linear shaker to assess its performance. Finally, the drifter was deployed in a controlled sea area with average values of wave height and frequency of 1.43 m and 0.29 Hz, respectively. In these conditions, the drifter showed horizontal and vertical oscillations with peak-to-peak accelerations of 0.8 g and power spectra centered around 1.5 Hz and 1 Hz, respectively. As a result, the KEH generated a mean output power of 0.18 mW, with peaks of 2.5 mW.Peer ReviewedPostprint (author's final draft

Analog Spiking Neuromorphic Circuits and Systems for Brain- and Nanotechnology-Inspired Cognitive Computing

Human society is now facing grand challenges to satisfy the growing demand for computing power, at the same time, sustain energy consumption. By the end of CMOS technology scaling, innovations are required to tackle the challenges in a radically different way. Inspired by the emerging understanding of the computing occurring in a brain and nanotechnology-enabled biological plausible synaptic plasticity, neuromorphic computing architectures are being investigated. Such a neuromorphic chip that combines CMOS analog spiking neurons and nanoscale resistive random-access memory (RRAM) using as electronics synapses can provide massive neural network parallelism, high density and online learning capability, and hence, paves the path towards a promising solution to future energy-efficient real-time computing systems. However, existing silicon neuron approaches are designed to faithfully reproduce biological neuron dynamics, and hence they are incompatible with the RRAM synapses, or require extensive peripheral circuitry to modulate a synapse, and are thus deficient in learning capability. As a result, they eliminate most of the density advantages gained by the adoption of nanoscale devices, and fail to realize a functional computing system. This dissertation describes novel hardware architectures and neuron circuit designs that synergistically assemble the fundamental and significant elements for brain-inspired computing. Versatile CMOS spiking neurons that combine integrate-and-fire, passive dense RRAM synapses drive capability, dynamic biasing for adaptive power consumption, in situ spike-timing dependent plasticity (STDP) and competitive learning in compact integrated circuit modules are presented. Real-world pattern learning and recognition tasks using the proposed architecture were demonstrated with circuit-level simulations. A test chip was implemented and fabricated to verify the proposed CMOS neuron and hardware architecture, and the subsequent chip measurement results successfully proved the idea. The work described in this dissertation realizes a key building block for large-scale integration of spiking neural network hardware, and then, serves as a step-stone for the building of next-generation energy-efficient brain-inspired cognitive computing systems

Potential and Challenges of Analog Reconfigurable Computation in Modern and Future CMOS

In this work, the feasibility of the floating-gate technology in analog computing platforms in a scaled down general-purpose CMOS technology is considered. When the technology is scaled down the performance of analog circuits tends to get worse because the process parameters are optimized for digital transistors and the scaling involves the reduction of supply voltages. Generally, the challenge in analog circuit design is that all salient design metrics such as power, area, bandwidth and accuracy are interrelated. Furthermore, poor flexibility, i.e. lack of reconfigurability, the reuse of IP etc., can be considered the most severe weakness of analog hardware. On this account, digital calibration schemes are often required for improved performance or yield enhancement, whereas high flexibility/reconfigurability can not be easily achieved. Here, it is discussed whether it is possible to work around these obstacles by using floating-gate transistors (FGTs), and analyze problems associated with the practical implementation. FGT technology is attractive because it is electrically programmable and also features a charge-based built-in non-volatile memory. Apart from being ideal for canceling the circuit non-idealities due to process variations, the FGTs can also be used as computational or adaptive elements in analog circuits. The nominal gate oxide thickness in the deep sub-micron (DSM) processes is too thin to support robust charge retention and consequently the FGT becomes leaky. In principle, non-leaky FGTs can be implemented in a scaled down process without any special masks by using “double”-oxide transistors intended for providing devices that operate with higher supply voltages than general purpose devices. However, in practice the technology scaling poses several challenges which are addressed in this thesis. To provide a sufficiently wide-ranging survey, six prototype chips with varying complexity were implemented in four different DSM process nodes and investigated from this perspective. The focus is on non-leaky FGTs, but the presented autozeroing floating-gate amplifier (AFGA) demonstrates that leaky FGTs may also find a use. The simplest test structures contain only a few transistors, whereas the most complex experimental chip is an implementation of a spiking neural network (SNN) which comprises thousands of active and passive devices. More precisely, it is a fully connected (256 FGT synapses) two-layer spiking neural network (SNN), where the adaptive properties of FGT are taken advantage of. A compact realization of Spike Timing Dependent Plasticity (STDP) within the SNN is one of the key contributions of this thesis. Finally, the considerations in this thesis extend beyond CMOS to emerging nanodevices. To this end, one promising emerging nanoscale circuit element - memristor - is reviewed and its applicability for analog processing is considered. Furthermore, it is discussed how the FGT technology can be used to prototype computation paradigms compatible with these emerging two-terminal nanoscale devices in a mature and widely available CMOS technology.Siirretty Doriast

Computer-controlled autonomous model car: A mechatronics project

Mechatronics is a synthesis of mechanical engineering and electronic engineering, and computer engineering, distinct areas that overlap in the design of systems. It represents the interdisciplinary nature of design and development of today\u27s products.;The current research focuses on the design, construction and testing of a computer controlled autonomous model car which can exhibit intelligent behavior such as timed course execution, obstacle detection, and response to sensor inputs. The car is intended as a mechatronics design project that will be integrated into an existing one-semester mechanical engineering undergraduate instrumentation course.;The car was designed around a microprocessor board (Tern Analog Drive) controlled by a 16-bit microcontroller (Tern V104) and equipped with several sensor channels. Two stepper motors were used to propel and guide the car. Photocells were used to detect the path. The control program was written in Turbo C.;The car was tested on a path of reflective white tape about 2 inches wide. The path consists of a 36-inch straight portion followed by a 17-inch radius of curvature curved portion, and completed by a 6-inch straight section with an obstacle at the end. The autonomous car successfully traversed the path and stopped when it detected the obstacle.;It was concluded that a successful mechatronic design project could be developed around the construction and testing of an autonomous car