Computer Architectures to Close the Loop in Real-time Optimization

© 2015 IEEE.Many modern control, automation, signal processing and machine learning applications rely on solving a sequence of optimization problems, which are updated with measurements of a real system that evolves in time. The solutions of each of these optimization problems are then used to make decisions, which may be followed by changing some parameters of the physical system, thereby resulting in a feedback loop between the computing and the physical system. Real-time optimization is not the same as fast optimization, due to the fact that the computation is affected by an uncertain system that evolves in time. The suitability of a design should therefore not be judged from the optimality of a single optimization problem, but based on the evolution of the entire cyber-physical system. The algorithms and hardware used for solving a single optimization problem in the office might therefore be far from ideal when solving a sequence of real-time optimization problems. Instead of there being a single, optimal design, one has to trade-off a number of objectives, including performance, robustness, energy usage, size and cost. We therefore provide here a tutorial introduction to some of the questions and implementation issues that arise in real-time optimization applications. We will concentrate on some of the decisions that have to be made when designing the computing architecture and algorithm and argue that the choice of one informs the other

The power of wavelets in analysis of transit and phase curves in presence of stellar variability and instrumental noise III. Accuracy of transit parameters

Correlated noise in exoplanet light curves, such as noises from stellar activity, convection noise, and instrumental noises distorts the exoplanet transit light curves, and leads to biases in the best-fit transit parameters. An optimal fitting algorithm is stable against the presence of correlated noises and lead to statistically consistent results, i.e. the actual biases are usually within the error interval. This is not automatically satisfied by most of the algorithms in everyday use, and the testing of the algorithms is necessary. In this paper, we describe a bootstrapping-like test to handle with the general case, and apply this to the wavelet-based TLCM (Transit and Light Curve Modeller) algorithm, testing it for the stability against the correlated noise. We contrast the results to the FITSH algorithm that is based on a white noise assumption. We simulated transit light curves with previously known parameters in the presence of a correlated noise model generated by an ARIMA (Autoregressive Integretad Moving Average) process. Then we solved the simulated observations, and examined the resulting parameters and error intervals. We have found that the assumption of FITSH that only white noise is present led to inconsistencies in the results: the distribution of best-fit parameters is by a factor of 3--6 broader then the determined error intervals. On the other hand, the wavelet-based TLCM algorithm handles the correlated noise properly, leading to properly determined parameter and error intervals which are perfectly consistent with the actual biases.Comment: Submitted to A&A, favorable referee report received, 11 pages, 8 figure

In - situ PMD Monitoring Using Coherent Detection and Polarization Tracking

Polarization mode dispersion (PMD) is a major impairment in high bit rate optical communication systems, causing system degradation. Although the random nature of PMD makes it difficult to be characterized, many measurement techniques have been developed to measure PMD and its effects on network reliability. However, the lack of in situ measurement techniques that can measure PMD on traffic carrying fibers has made it difficult for engineers to characterize the effects of PMD on wide bandwidth wavelength division multiplex (WDM) optical systems. The objective of this research is to develop an in situ PMD monitoring technique for long haul fiber optic links and use this technique to characterize the magnitude and distribution of PMD on these links. Towards this end, a systematic approach was followed to develop a monitoring equipment that can measure PMD on traffic carrying links. First, an earlier implementation of the PMD monitoring equipment based on coherent detection and polarization scrambling\cite{hui2007nbp} was improved in terms of size, speed and accuracy to make it more suitable for field measurements of PMD in traffic carrying fiber optic links. The coherent PMD monitor can measure differential group delay (DGD) values in the range of 0 to 50 ps. Secondly, using theoretical analysis, it was ascertained that the magnitude of PMD, the DGD measured by the PMD monitor, is the apparent DGD of the fiber and not its true DGD. Mathematical analysis was used to derive a relationship between the true DGD and the apparent DGD of the fiber. Also, it was found that the distribution of the apparent DGD is Rayleigh, unlike the true DGD which is Maxwellian. Thirdly, the hardware and software for implementing a polarization tracking algorithm to measure PMD was developed and tests were conducted to validate the algorithm in terms of speed, accuracy and the characteristics of the measured DGD. The polarization tracking algorithm has a higher measurement speed and lesser memory requirements than polarization scrambling. A number of laboratory experiments and field trials on traffic carrying fibers were conducted for a comparative analysis of polarization scrambling and polarization tracking. Using the polarization tracking algorithm to measure DGD, the measurement speed was found to be 20 times higher and the memory requirements about 80 times less than the memory required for DGD measurements using polarization scrambling. Results of the laboratory experiments and field trials agree with our theoretical analysis and the two algorithms have similar statistics for the measured DGD. Finally, the possibility of a more efficient implementation of polarization tracking was explored to measure PMD in real time. A run time implementation with the existing hardware and software was developed where the advantages of polarization tracking over polarization scrambling was made evident. The use of the in-situ PMD monitoring technique will enable network engineers to monitor the impact of PMD in live traffic carrying links and to select the wavelength bands that are relatively less affected by PMD

PHASOR MEASUREMENT UNIT TESTING AND CHARACTERIZATION

The power grid is a complex system composed of many different elements. Knowledge of electrical waveform content across the grid is key to managing power and maintaining stability. Electrical waveforms can be represented mathematically as time-varying phasors. Electrical phasors give information pertaining to the magnitude of the waveform as well as the phase relationship of the waveform to a reference. A Phasor Measurement Unit (PMU) is a device that is installed at a node on the power grid and measures electrical phasors. The potential of near real time phasor information is powerful and has driven PMU application technology forward at a rapid pace over the last decade. The IEEE C37.118 standard establishes requirement guidelines for PMU performance. Before PMUs are implemented in real time applications researchers may wish to test PMUs to obtain specific device behavior. This thesis will describe the development of a robust PMU test bench that is capable producing dynamic input signals. Dynamic testing and analysis will reveal time domain and frequency domain characteristics of the PMU under test. A discussion on the reported response and the real time response of PMUs will be covered to give more insight into the real time behavior and application of PMUs. Conclusions will take one last look at the project and discuss the potential of this work as a starting point for future PMU testing

HIGH CAPACITY AND OPTIMIZED IMAGE STEGANOGRAPHY TECHNIQUE BASED ON ANT COLONY OPTIMIZATION ALGORITHM

The tremendous development of digital technology, it is mandatory to address the security while transmitting information over network in a way that observer couldn’t depict it. Measures to be taken to provide the security by establishing hidden communication using steganography principle which is help to camouflage the secret information in some carrier file such as text, image, audio and video. In this era of hidden data communication, image becoming an effective tool on account of their frequency, capability and accuracy. Image steganography uses an image as a carrier medium to hide the secret data. The main motive of this article is that the uses the combination of frequency domain and optimization method inorder to increasing in robustness. In this article, Integer Wavelet transform is performed into the host image and coefficients have been transformed. ACO optimization algorithm is used to find the optimal coefficients where to hide the data. Furthermore, sample images and information having been demonstrated which proved the increased robustness as well as high level of data embedding capacity

Development of low cost spectrum qualifier for new iot technologies

With the evolution of radio technologies during the last decades, the companies are replacing equipment with individual components with particular functions by systems where most signals are treated digitally through digital signal processing techniques. With this, engineers can develop many applications at the software level, enabling new analyses to exists. With the growth of the internet of things, companies are deploying new solutions around the world. Most of these solutions are wireless applications that use the unlicensed frequency spectrum band, which increases the density of wireless devices in a location. In environments with numerous wireless equipment transmitting simultaneously, it is essential to detect how busy the frequency spectrum is before deploying a new solution. A spectrum analyzer can analyze this, but the cost of acquiring suitable equipment can be very high. Besides that, these devices only allow users to analyze the frequency spectrum, not the technology itself, packet loss, data rate, and coverage, without purchasing expensive software licenses. This thesis presents the development of a software-defined radio application capable of evaluating the performance of radio technologies, such as Bluetooth or Wi-SUN, and shows their behavior in a noisy environment

Image-Based Lateral Position, Steering Behavior Estimation, and Road Curvature Prediction for Motorcycles

International audienceThis letter presents an image-based approach to simultaneously estimate the lateral position of a powered-two-wheeled vehicle on the road, its steering behavior and predict the road curvature ahead of the motorcycle. This letter is based on the inverse perspective mapping technique combined with a road lanes detection algorithm capable of detecting straight and curved lanes. Then, a clothoid model is used to extract pertinent information from the detected road markers. Finally, the performance of the proposed approach is illustrated through simulations carried out with the well-known motorcycle simulator “BikeSim.” The results are very promising since the algorithm is capable of estimating, in real time, the road geometry and the vehicle location with a better accuracy than the one given by the commercial GPS