Parameter Optimization of Decentralized OS-CFAR System Based Modified PSO Method

2012 ◽  
Vol 532-533 ◽  
pp. 881-886
Author(s):  
Pan Zhi Liu ◽  
Ruo Yu Pan ◽  
Guo Fang Guo
Keyword(s):  
Optimization Problem ◽  
Detection System ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Fusion Center ◽  
Threshold Values ◽  
Cfar Detection ◽  
Computation Technique ◽  
And Performance ◽  
Ordered Statistics

For decentralized ordered statistics (OS) constant false alarm ration (CFAR) detection system, the parameter estimation and performance analysis in complicated detection condition is a typical nonlinear optimization problem. Owing to the nonlinear property of distributed OS-CFAR detection system, it is seriously difficult to obtain optimal threshold values using some optimization method at the fusion center. This paper provides a novel solution based on an effective and flexible particle swarm optimization (PSO) algorithm. As a novel evolutionary computation technique, PSO has attracted much attention and wide applications, owing to its simple concept, easy implementation and quick convergence. Using this approach, all system parameters can be optimized simultaneously. The simulation results show that the proposed approach can achieve effective performances with the above method.

Quantitative Feedback Theory control design using particle swarm optimization method

2011 ◽  
Vol 34 (4) ◽  
pp. 463-476 ◽  
Author(s):  
Hazem I Ali ◽  
Samsul Bahari B Mohd Noor ◽  
SM Bashi ◽  
Mohammad Hamiruce Marhaban
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Design Procedure ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Quantitative Feedback Theory ◽  
Swarm Optimization ◽  
Servo Actuator ◽  
Actuator System ◽  
And Performance

In this paper, a particle swarm optimization (PSO) method is proposed to design Quantitative Feedback Theory (QFT) control. This method minimizes a proposed cost function subject to appropriate robust stability and performance QFT constraints. The PSO algorithm is simple and easy to implement, and can be used to automate the loop shaping procedures of the standard QFT. The proposed method is applied to the high uncertainty pneumatic servo actuator system as an example to illustrate the design procedure of the proposed algorithm. The proposed method is compared with the standard QFT control. The results show that the superiority of the proposed method in that it can achieve the same robustness requirements of standard QFT control with simple structure and low order controller.

Dexterity Analysis based on Jacobian and Performance Optimization for Multi-segment Continuum Robots

2021 ◽  
pp. 1-13
Author(s):  
Jiao Wang ◽  
Henry Y K Lau
Keyword(s):  
Performance Optimization ◽  
Optimization Problem ◽  
Jacobian Matrix ◽  
Pso Algorithm ◽  
Optimal Length ◽  
Continuum Robots ◽  
Swarm Optimization ◽  
Global Indices ◽  
Reachable Workspace ◽  
And Performance

Abstract This study presents the performance analysis of multi- segment continuum robots. Since continuum robots are designed to provide excellent dexterity, two local indices, axiality and angularity dexterity, are introduced to study the dexterity that is inspired by separating Jacobian matrix. A Monte Carlo Method is adopted to simulate the distribution of local dexterity over the workspace. On this basis, the corresponding global indices in axiality and angularity are defined to compare global dexterity performance. To investigate the optimal kinematic performance, an objective function related to the segment lengths is designed under the consideration of reachable workspace as well as dexterity performance. Particle Swarm Optimization (PSO) algorithm is adopted to solve the optimization problem successfully. The optimal length distributions for two-segment and three-segment continuum robots are discovered. It is found that this method can also apply to general multi-segment continuum robots.

scholarly journals A Multiobjective Optimal Operation of a Stand-Alone Microgrid Using SAPSO Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Guoping Zhang ◽  
Weijun Wang ◽  
Jie Du ◽  
Hua Liu
Keyword(s):  
Optimization Model ◽  
Optimization Problem ◽  
Search Algorithm ◽  
Pso Algorithm ◽  
Optimization Method ◽  
Optimal Operation ◽  
Renewable Energy Resources ◽  
Diesel Generator ◽  
Pareto Solution ◽  
Operation Optimization

Microgrid is an effective way to utilize renewable energy resources, especially for satisfying the electricity requirements in remote islands. The operation optimization of an island microgrid is critical to ensure the effective performance of the whole microgrid system, and it is usually a multiconstrained and multiobjective optimization problem. The main contribution of this study is an operation optimization method for the stand-alone microgrid system in a remote island, which includes wind, PV, battery, and diesel generator. In this paper, a novel operation optimization model for stand-alone microgrid is proposed, in which the battery system is considered separately; the multiobjective day-ahead optimization model considering economic cost, battery depreciation cost, and environmental protection cost is established. In the optimization, the output power of diesel generator and energy storage system are chosen as the decision variables. For this purpose, an efficient search algorithm combining the particle swarm optimization (PSO) algorithm and the simulated annealing (SA) algorithm is developed. The hybrid algorithm is applied to search for the Pareto solution set of the optimization problem. The search results are compared with those from traditional PSO algorithm. Also, a grey target decision-making theory based on the entropy weight method is proposed to identify the best trade-off scheduling scheme among all the solutions, and the results are compared with those from two other commonly used subjective and objective methods. The results show that the proposed optimization method can be applied to the day-ahead operation optimization of the microgrid system and help the user obtain the best compromise operation scheme for stand-alone microgrid.

scholarly journals New Auxiliary Function with Properties in Nonsmooth Global Optimization for Melanoma Skin Cancer Segmentation

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Idris A. Masoud Abdulhamid ◽  
Ahmet Sahiner ◽  
Javad Rahebi
Keyword(s):  
Global Optimization ◽  
Skin Cancer ◽  
Optimization Problem ◽  
Optimization Method ◽  
Local Minimizer ◽  
High Accuracy ◽  
Auxiliary Function ◽  
Threshold Values ◽  
Filled Function ◽  
Melanoma Skin

In this paper, an algorithm is introduced to solve the global optimization problem for melanoma skin cancer segmentation. The algorithm is based on the smoothing of an auxiliary function that is constructed using a known local minimizer and smoothed by utilising Bezier curves. This function achieves all filled function properties. The proposed optimization method is applied to find the threshold values in melanoma skin cancer images. The proposed algorithm is implemented on PH2, ISBI2016 challenge, and ISBI 2017 challenge datasets for melanoma segmentation. The results show that the proposed algorithm exhibits high accuracy, sensitivity, and specificity compared with other methods.

Angular Resolved Electron Spectroscopy with Parallel Recording

1990 ◽  
Vol 48 (2) ◽  
pp. 370-371
Author(s):  
Huang Min ◽  
P.S. Flora ◽  
C.J. Harland ◽  
J.A. Venables
Keyword(s):  
Electron Spectroscopy ◽  
Low Voltage ◽  
Solid Angle ◽  
Detection System ◽  
Voltage Electron ◽  
Cylindrical Mirror ◽  
Inner Radius ◽  
Channel Plate ◽  
And Performance ◽  
Type Detector

A cylindrical mirror analyser (CMA) has been built with a parallel recording detection system. It is being used for angular resolved electron spectroscopy (ARES) within a SEM. The CMA has been optimised for imaging applications; the inner cylinder contains a magnetically focused and scanned, 30kV, SEM electron-optical column. The CMA has a large inner radius (50.8mm) and a large collection solid angle (Ω > 1sterad). An energy resolution (ΔE/E) of 1-2% has been achieved. The design and performance of the combination SEM/CMA instrument has been described previously and the CMA and detector system has been used for low voltage electron spectroscopy. Here we discuss the use of the CMA for ARES and present some preliminary results.The CMA has been designed for an axis-to-ring focus and uses an annular type detector. This detector consists of a channel-plate/YAG/mirror assembly which is optically coupled to either a photomultiplier for spectroscopy or a TV camera for parallel detection.

The Improvement of Newton Method and the Validation of Optimization Idea of Blind Walking Repeatedly

2011 ◽  
Vol 250-253 ◽  
pp. 4061-4064
Author(s):  
Chun Ling Zhang
Keyword(s):  
Saddle Point ◽  
Newton Method ◽  
Optimization Problem ◽  
Initial Point ◽  
Optimization Method ◽  
Maximum Point ◽  
Optimal Result ◽  
Feasible Domain ◽  
Parallel Arithmetic ◽  
Newton Direction

The existence of maximum point, oddity point and saddle point often leads to computation failure. The optimization idea is based on the reality that the optimum towards the local minimum related the initial point. After getting several optimal results with different initial point, the best result is taken as the final optimal result. The arithmetic improvement of multi-dimension Newton method is improved. The improvement is important for the optimization method with grads convergence rule or searching direction constructed by grads. A computational example with a saddle point, maximum point and oddity point is studied by multi-dimension Newton method, damped Newton method and Newton direction method. The importance of the idea of blind walking repeatedly is testified. Owing to the parallel arithmetic of modernistic optimization method, it does not need to study optimization problem with seriate feasible domain by modernistic optimization method.

High-Performance Image Filters via Sparse Approximations

2020 ◽  
Vol 3 (2) ◽  
pp. 1-19
Author(s):  
Kersten Schuster ◽  
Philip Trettner ◽  
Leif Kobbelt
Keyword(s):  
High Performance ◽  
Hardware Acceleration ◽  
Optimization Method ◽  
Translation Invariant ◽  
Approximation Quality ◽  
Trade Offs ◽  
Sparse Approximations ◽  
Image Filters ◽  
Good Trade ◽  
And Performance

We present a numerical optimization method to find highly efficient (sparse) approximations for convolutional image filters. Using a modified parallel tempering approach, we solve a constrained optimization that maximizes approximation quality while strictly staying within a user-prescribed performance budget. The results are multi-pass filters where each pass computes a weighted sum of bilinearly interpolated sparse image samples, exploiting hardware acceleration on the GPU. We systematically decompose the target filter into a series of sparse convolutions, trying to find good trade-offs between approximation quality and performance. Since our sparse filters are linear and translation-invariant, they do not exhibit the aliasing and temporal coherence issues that often appear in filters working on image pyramids. We show several applications, ranging from simple Gaussian or box blurs to the emulation of sophisticated Bokeh effects with user-provided masks. Our filters achieve high performance as well as high quality, often providing significant speed-up at acceptable quality even for separable filters. The optimized filters can be baked into shaders and used as a drop-in replacement for filtering tasks in image processing or rendering pipelines.

scholarly journals In-Orbit Operational Parameter Calculation and Performance Optimization in KOMPSAT-6 Synthetic Aperture Radar

2021 ◽  
Vol 13 (12) ◽  
pp. 2342
Author(s):  
Jin-Bong Sung ◽  
Sung-Yong Hong
Keyword(s):  
Synthetic Aperture Radar ◽  
Performance Optimization ◽  
Pulse Repetition Frequency ◽  
Optimization Method ◽  
Synthetic Aperture ◽  
Operational Parameters ◽  
Operational Parameter ◽  
Design Methodologies ◽  
And Performance ◽  
Aperture Radar

A new method to design in-orbit synthetic aperture radar operational parameters has been implemented for the Korean Multi-purpose Satellite 6 mission. The implemented method optimizes the pulse repetition frequency when a satellite altitude changes from its nominal one, so it has the advantage that the synthetic aperture radar performances can satisfy the requirements for the in-orbit operation. Other commanding parameters have been designed to conduct trade-off between those parameters. This paper presents the new optimization method to maintain the synthetic aperture radar performances even in the case of an altitude variation. Design methodologies to determine operational parameters, respectively, at nominal altitude and in orbit are presented. In addition, numerical simulation is presented to validate the proposed optimization and the design methodologies.

Parameter study and optimization design of a hat oblique tunnel portal

2021 ◽  
pp. 095440972110140
Author(s):  
Zijian Guo ◽  
Tanghong Liu ◽  
Wenhui Li ◽  
Yutao Xia
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Pareto Front ◽  
Optimization Problem ◽  
Optimization Method ◽  
Design Parameters ◽  
Parameter Study ◽  
Buffer Structure ◽  
Tunnel Entrance ◽  
The Ideal

The present work focuses on the aerodynamic problems resulting from a high-speed train (HST) passing through a tunnel. Numerical simulations were employed to obtain the numerical results, and they were verified by a moving-model test. Two responses, [Formula: see text] (coefficient of the peak-to-peak pressure of a single fluctuation) and[Formula: see text] (pressure value of micro-pressure wave), were studied with regard to the three building parameters of the portal-hat buffer structure of the tunnel entrance and exit. The MOPSO (multi-objective particle swarm optimization) method was employed to solve the optimization problem in order to find the minimum [Formula: see text] and[Formula: see text]. Results showed that the effects of the three design parameters on [Formula: see text] were not monotonous, and the influences of[Formula: see text] (the oblique angle of the portal) and [Formula: see text] (the height of the hat structure) were more significant than that of[Formula: see text] (the angle between the vertical line of the portal and the hat). Monotonically decreasing responses were found in [Formula: see text] for [Formula: see text] and[Formula: see text]. The Pareto front of [Formula: see text] and[Formula: see text]was obtained. The ideal single-objective optimums for each response located at the ends of the Pareto front had values of 1.0560 for [Formula: see text] and 101.8 Pa for[Formula: see text].

scholarly journals An Optimization Method for the Configuration of Inter Array Cables for Floating Offshore Wind Farm

2017 ◽  
Author(s):  
Yann Poirette ◽  
Martin Guiton ◽  
Guillaume Huwart ◽  
Delphine Sinoquet ◽  
Jean Marc Leroy
Keyword(s):  
Wind Farm ◽  
Optimization Problem ◽  
Initial Point ◽  
Trust Region ◽  
Optimization Method ◽  
Global Optimum ◽  
Offshore Wind ◽  
Finite Element Software ◽  
Constrained Problems ◽  
Floating Offshore Wind Turbines

IFP Energies nouvelles (IFPEN) is involved for many years in various projects for the development of floating offshore wind turbines. The commercial deployment of such technologies is planned for 2020. The present paper proposes a methodology for the numerical optimization of the inter array cable configuration. To illustrate the potential of such an optimization, results are presented for a case study with a specific floating foundation concept [1]. The optimization study performed aims to define the least expensive configuration satisfying mechanical constraints under extreme environmental conditions. The parameters to be optimized are the total length, the armoring, the stiffener geometry and the buoyancy modules. The insulated electrical conductors and overall sheath are not concerned by this optimization. The simulations are carried out using DeepLines™, a Finite Element software dedicated to simulate offshore floating structures in their marine environment. The optimization problem is solved using an IFPEN in-house tool, which integrates a state of the art derivative-free trust region optimization method extended to nonlinear constrained problems. The latter functionality is essential for this type of optimization problem where nonlinear constraints are introduced such as maximum tension, no compression, maximum curvature and elongation, and the aero-hydrodynamic simulation solver does not provide any gradient information. The optimization tool is able to find various local feasible extrema thanks to a multi-start approach, which leads to several solutions of the cable configuration. The sensitivity to the choice of the initial point is demonstrated, illustrating the complexity of the feasible domain and the resulting difficulty in finding the global optimum configuration.

Sign in / Sign up

Export Citation Format

Share Document