Jitter-Aware Economic PDN Optimization With a Genetic Algorithm

This paper describes effect of designing resonant free power delivery network (PDN) on the performance of voltage regulator modules (VRM) commonly used in microprocessor systems. The performance parameters of the VRM as a result of decoupling capacitors (DECAPS) added at different stages of the PDN to realize the resonant free target impedance is described using the output impedance as a key parameter. Parametric curves and simulation results are presented to support the validity of the design oriented analysis with special emphasis on the performance of the VRM considering voltage sensing for feedback at different stages of the microprocessor PDN

The paper describes optimization Non-GEO satellite constellation design with satellite diversity using genetic algorithm. This algorithm is called as genetic satellite constellation algorithm. A rank fitness assignment method of multiobjective optimization is proposed to capture a number of solutions simultaneously. The non-dominated in GA’s is sorted to find the multiple Pareto optimal points. The genetic satellite constellation algorithm is investigated to produce the optimum satellite constellation design with the minimum number of satellites while minimizing the maximum orbit’s altitude, to minimize the angle shift between satellites, to maximize the angle between planes and the inclination angle with satellite diversity. Illustrative results of satellite constellation components and dual satellite diversity statistics for LEO and MEO constellation are presented. The simulation results are compared to ICO for MEO constellation and to Globalstar for LEO constellation. Using genetic algorithm, satellite constellation design can be achieved the visibility of dual satellite diversity statistics whilst reducing the total number of satellites. Genetic algorithm is a robust method ideally suited for satellite constellation design.

As the complexity increases, power delivery network (PDN) optimization becomes a more important step in a modern design. In order to construct a robust PDN, most classic PDN optimization methods focus on adjusting the dimensions of power stripes. However, this approach becomes infeasible when voltage violation regions also have severe routing congestion. Hence, this paper proposes a delicate procedure to insert additional power stripes to reduce voltage violation while maintaining routability. In the beginning, IR-drop high related regions are identified to reveal those locations which are thirsty for more currents. Then, we solve a minimum-cost flow problem to find the topologies of power delivery paths (PDPs) from power sources to these regions and determine the widths of edges in each PDP so that enough currents can be provided to these regions. Moreover, vertical power stripes (VPSs for short) are inserted to the locations which have less routing congestion and severe voltage violations by the dynamic programming to reduce a probability to deteriorate routability. Finally, more wires will be inserted to IR-drop high related regions if there still exist voltage violations. Experimental results show that our method can use much less routing resource and induce less routing congestion to meet IR-drop constraint in industry designs.

본 논문에서는 전원무결성(Power Source Integrity) 해석을 기반으로 PCB(Printed Circuit Board)내부 전원 선로의 RLC 공진(Resonance)현상을 해석하고 PCB내부 공진현상 감쇄를 위한 설계기법을 제시한다. 제시하는 기법은 PCB의 구조적 특성으로 형성되는 공진주파수를 예측하며, 공진현상 감쇄를 위한 디커플링 캐패시터의 적용위치 및 용량을 결정할 수 있다. 본 논문에서는 산업용 제어기 내부의 메인보드 회로 시뮬레이션 모델을 통해서 PCB 공진현상 감쇄 설계기법에 대한 타당성을 검증하였다. 본 연구결과는 향후, PCB 회로 설계에서 PDN(Power Delivery Network)구조의 안정도 향상에 기여할 것으로 기대된다. This paper introduces the reduction design technique of the resonance phenomenon of the inner PCB based on power integrity from the analysis about the inner power supply line generating RLC resonance. With the technique, the resonant frequency resulted from the structural characteristics of the PCB can be analyzed and allows to predict and the capacitor for resonance phenomenon reduction can be decided as a decoupling capacitor. From the simulation result, it was confirmed that the PCB's resonance phenomenon reduction design technique should have the reduction effect in the inner motherboard of the industrial controller. This research will be contributed to the improvement of the safety of a PDN (Power Delivery Network) structure in the layout design technique of the PCB.

본 논문에서는 GNSS(Global-Navigation Satellite Service)에서 사용되는 단말기의 PCB(Printed Circuit Board) 전원안정화를 위해서 PCB 내층에 삽입될 EBG(Electromagnetic Band Gap) 구조체를 제안한다. 버섯모양의 제안된 EBG 구조체를 통한 PCB에서의 관심 금지대역폭/저지대역폭 주파수는 GNSS와 이동통신 관련 주파수를 포함하는 1.55GHz에서 1.81GHz이었으며, 시뮬레이션 결과, 이 구간에서 삽입손실(S21)이 약 -40dB 이하로 형성됨을 볼 수 있었다. 본 연구결과는 향후, PCB 회로 설계의 PDN(Power Delivery Network)구조의 안정화 향상 및 EMI(Electro Magnetic Interference) 대책에 효과적 대응이 유용할 것으로 기대된다. In this paper, a mushroom typed electromagnetic band gap (EBG) structure to be inserted in the printed circuit board (PCB) inner layer in order to stabilize the PCB power line is proposed for global-navigation satellite service (GNSS). In designing the proposed EBG structure, the target stop-bandwidth was designed from 1.55GHz to 1.81GHz including GNSS and mobile communication-related frequency bandwidth. In this bandwidth, the insertion loss(S21) was observed below about -40dB. From the simulation results, it is expected that the stabilization of power delivery network (PDN) structure in the PCB circuit design should be improved and the effective correspondence to EMI will be helpful.

Power delivery network (PDN) design is already a challenging problem for single die designs using advanced process technologies. For systems created using stacked dies with TSVs, several additional issues that affect power delivery and reliability have to be addressed. In stacked die configuration, the dies higher up in the stack-up experience additional drop and noise in their power supply as it propagates through the TSV networks of one or more dies placed lower in the stack-up. For the lower dies, the presence of the TSV farm and associated metals/vias affects the homogeneity of their own power delivery network. And if multiple dies share power and ground domains, then there could be an inter-die propagation of supply noise. So it becomes important that a PDN design and optimization flow for stacked die designs models and analyzes the presence of multiple dies and also the switching and the noise impact from the dies on each other. The analysis could be concurrent or model based, depending upon whether full databases for all the chips are available or their electrically equivalent models such as Chip Power Model (CPM) are available, respectively. For both of these approaches, a DC and time-domain analysis has to be done at the chip layout level to accurately predict the power/ground noise in the stacked die design. These analyses need to done starting early, in order to enable prototyping and design trade-off decisions. In this paper, a prototyping and verification solution for multi-die TSV based designs is outlined along with results from various design decisions undertaken.

With the development of science and technology, there has been growing the grid size, the growing demand for electricity and the extent of increasing the electricity market.In this paper, a mathematical morphology and genetic algorithm based dynamic reactive power optimization method for distribution network is proposed.By means of constructing mathematical morphology filter, the binary image composed by allelic genes of chromosome is filtered and the problem that deals with the action times of voltage regulating devices for compensation is turned into filtering problem of discrete binary image.With further automate scheduling, distribution automation and unmanned substation reactive power optimization of distribution line running made an urgent request.Reactive power optimization can improve the voltage passing rate, increasing the reliability of the system, the power quality, and the system runs the security and economy of the perfect combination, very broad application prospects.

To acquire images in low-light environments, it is usually necessary to adopt long exposure times or to resort to flashes. Flashes, however, often induce color distortion, cause the red-eye effect and can be disturbing to the subjects. On the other hand, long-exposure shots are susceptible to subject-motion, as well as motion-blur due to camera shake when performed with a hand-held camera. A recently introduced technique to overcome the limitations of the traditional lowlight photography is the use of the multi-spectral flash. Multi-spectral flash images are a combination of UV/IR and visible spectrum information. The general idea is to retrieve the details from the UV/IR spectrum and the color from the visible spectrum. Multi-spectral flash images, however, are themselves subject to color distortion and noise. In this work, a method of computing multi-spectral flash images so as to reduce the noise and to improve the color accuracy is presented. The proposed method is a previously seen optimization method, improved by introducing a weight map used to discriminate the uniform regions from the detail regions. The optimization target function takes into account the output likelihood with respect to the ambient light image, the sparsity of image gradients, and the spectral constraints for the IR-red and UV-blue channels. The performance of the proposed method was objectively evaluated using longexposure shots as references.

In order to acquire images in low-light environments, it is usually necessary to adopt long exposure times or resort to flash lights. However, flahses often induce color distortion, cause the red-eye effect and can be disturbing to subjects. On the other hand, long-exposure shots are susceptible to subject-motion, as well as motion-blur due to camera shake when performed hand-held. A recently introduced technique to overcome the limitations of traditional low-light photography is that of multi-spectral flash. Multi-spectral flash images are a combination of UV/IR and visible spectrum information. The general idea is that of retrieving details from the UV/IR spectrum and color from the visible spectrum. However, multi-spectral flash images themselves are subject to color distortion and noise. This works presents a method to compute multi-spectral flash images so that noise can be reduced and color accuracy improved. The proposed approach is a previously seen optimization method, improved by the introduction of a weight map used to discriminate uniform regions from detail regions. The optimization target function takes into account the output likelihood with respect to the ambient light image, the sparsity of image gradients as well as the spectral constraints for the IR-red channels and UV-blue channels. The performance of the proposed method has been objectively evaluated using long-exposure shots as references.

The article considers the components of the target function of optimization of HUNDRED losses associated with the introduction of the post (posts) of acceptance-diagnosis with the increase of the set of diagnostic equipment. In particular, the target function of optimizing losses at the service station is presented in the form of an economic criterion that takes into account the maximum possible number of components on which depends the technological efficiency of the service station and the level of "satisfaction" of car owners with services. The object of research is a car service station. The purpose of the work is to conduct a study of the target function of optimization of HUNDRED losses associated with the type of organization of acceptance-diagnosis of cars and to find out algorithms for finding the components of the target function based on the representation of HUNDRED as a queuing system. Research method - analysis and formalization: quantitative indicators of the objective function, methods of forming a group of events, alternative solutions and calculation of the main components of optimization of HUNDRED losses as a queuing system. It is established that the target function of optimization of HUNDRED losses has economic essence and can be presented in the form of complex criterion. It is found that based on the theory of queuing for the area of reception-diagnosis it becomes possible to find solutions of the system of equations that describe its current state, namely: 1) the probability that the system has no requirements, ie free all "workers »Posts and no applications in the queue; 2) the probability of finding the system in a certain state; 3) the probability of denial of the received application for maintenance, ie the probability of finding the system in the last valid state; 4) the average number of occupied reception posts. Similar solutions were found for the TO-R zone. The formulas for determining the components of the duration of the application are considered and given. The formulas for determining the average value of the duration of work in the area of maintenance by the flow of faults and their share in the total flow of applications. The necessity of the 5th - 6th step of building the equipment in the reception-diagnostic area for detection of additional malfunctions (hidden defects) is substantiated. It is established that the average processing time of the application at the posts of acceptance-diagnosis includes three components: 1) the average time of acceptance-diagnosis of the declared ambiguous manifestation of the fault; 2) the average time of additional preliminary diagnosis on the application, which contained ambiguous manifestations of malfunctions. Depends on the number of diagnostic operations performed and the available equipment; 3) the average time of additional diagnosis on the application, which either did not contain ambiguous manifestations of malfunctions, or they did not fall within the capabilities of the existing diagnostic complex at the reception. The results of the article can be used to model the operation of the service station as a queuing system in computer software products and will reveal the low efficiency of diagnosing the main systems of cars in a particular service station. KEY WORDS: DIAGNOSTIC PARAMETER, APPLICATION, PROBABILITY, FAULT, EQUIPMENT, POST, PROFIT, ACCEPTANCE-DIAGNOSIS, SYSTEM.

Application of Monte Carlo stochastic optimization (MOST) to deep learning

Using Fruit Fly Optimization Algorithm (FOA) to optimize the Proportion Integration (PI) control parameters of the single-phase inverter. The transfer function model of the single-phase inverter is obtained by the state space averaging method, and the globally optimum solution to parameters of the PI controller has been searched by using FOA with total harmonic distortion (THD), gain margin and phase margin of the system open-loop function as optimal target functions. Compared with the initial system, the optimal target function marks optimized system has a better control stability; also, the waveform of its output voltage has a smaller THD. According to the Matrix Laboratory (MATLAB) simulation result, it shows that FOA possesses faster convergence speed than Particle Swarm Optimization (PSO), and FOA can effectively find out the globally optimum solution. Upon applying the optimized PI controller to a single-phase inverter, the system has a good stability with a small THD of the output voltage waveform. Thus, the feasibility and effectiveness of applying FOA to the control optimization of the power electronics system can be proven.

Linear combination rule in genetic algorithm for optimization of finite impulse response neural network to predict natural chaotic time series

The conventional approaches to economic dispatch optimization in virtual power plants (VPPs) predominantly focus on power generation dispatch variables, often yielding local optima that undermine overall optimization efficiency. To address this limitation, this study devises an innovative VPP economic dispatch optimization methodology grounded in enhanced genetic algorithms. By meticulously extracting the distinct power generation characteristics of VPP components and scrutinizing the operational dynamics of diverse generator types, a more nuanced understanding of the system is attained. An advanced optimization model is subsequently formulated using an improved genetic algorithm, which operates under the dual constraints of economic and technical viability to pinpoint the pinnacle operational states for each unit. This meticulous process serves to refine dispatch strategies, thereby enhancing the VPP’s economic dispatch optimization. Comparative experimental validations conclusively demonstrate the superiority of this novel optimization method, affirming its feasibility and significant potential for real-world implementation, thus contributing to a more efficient and optimized VPP management landscape.

Considering the low efficiency and instability of traditional genetic algorithm optimized PID controller, an improved algorithm named harmony search genetic algorithm to optimize PID controller’s parameters of mechanical arm is proposed in this paper. Using harmony search algorithm in the initial population generation process of genetic algorithm improved the algorithm’s performance. Harmony search genetic algorithm is more suitable to optimize PID controller’s parameters than traditional genetic algorithm in six degrees of freedom mechanical arm system. Compared to the traditional control optimization method, as shown in the simulation results, the new kind of optimization method is better in both validity and stability.