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In this paper, in order to replace a conventional electric linear actuator which is consist of rotary PM machine and ball screw, a novel double-sided five-phase modular linear permanent magnet synchronous machine (MLPMSM) is proposed and designed with the same volume. The basic structure of the machine is firstly described and the major dimensions of one module are then optimized to acquire the largest...
Particle swarm optimization (PSO) has been proven to be a simple yet effective algorithm for searching the optimal solutions of objective functions. The main advantage of PSO is its simplicity, but it easily gets stuck in local optima. In order to remain the original merit and raise its performance, a novel idea is proposed in this paper, which selects the best model of PSO based on the previous performance...
The growing amount of intermittent renewables in power generation creates challenges for real-time matching of supply and demand in the power grid. Emerging ancillary power markets provide new incentives to consumers (e.g., electrical vehicles, data centers, and others) to perform demand response to help stabilize the electricity grid. A promising class of potential demand response providers includes...
Single image dehazing with its ill-posted characteristics has been a popular challenge in low-level vision. In this paper, an alternative approach of solving a single hazy image is presented. Initially, we propose a new haze model in consideration of multiple scattering during light propagation. Compared with the traditional dichromatic atmospheric scattering model, our new model requires fewer restrictive...
To accommodate the new features of modern protein mass spectra with Nobel-prize-winner electrospray ionization, Zhixin Tian, et al. developed isotopic Mass-to-charge ratio and Envelope Fingerprinting (iMEF) algorithm for in situ interpretation and database search of protein tandem mass spectra. The creation of the customized theoretical database of both proteins and their dissociated fragment ions...
The paper presents optimal control modeling study for energy-saving of belt conveyor system. Given the transport operations process of bulk terminals, belt conveyor is studied. Firstly, based on the simplified energy calculation model of the belt conveyor, an objective optimization model with the aim to improve transport efficiency and reduce transportation energy consumption is established. In the...
Given the pose adjustment and path planning of the welding mobile robot during seam tracking process, mobile welding robot and welding torch are studied. Kinematics modeling of the mobile welding robot is established, which is constrained with the slider moving area, welding torch length and so on. And then, physical System is designed and multi-objective optimization model is presented with the aims...
In this paper, a performance limit is derived for a distributed Bayesian parameter estimation problem in sensor networks where the prior probability density function of the parameter is known. The sensor observations are assumed conditionally independent and identically distributed given the parameter to be estimated, and the sensors employ independent and identical quantizers. The performance limit...
Distributed detection with dependent observations is always a challenging problem. The problemof detectionwith shared information has many applications when sensors have overlapped measurements, e.g., when distributed detection is performed in a security system where sensors have overlapped coverages. For this shared information scenario, we investigate the distributed detection problem in parallel...
With the development of smart grid technology, FACTS devices, such as SVC and STATCOM, are widely applied in practice. Since the FACTS devices possess fast dynamic response characteristics, they can provide effective support to power systems stability even during the transient process after severe contingencies. It is helpful to take into account the transient process stability constraints into reactive...
In this paper, a grouping genetic algorithm based approach is proposed for dividing stocks into groups and mining a set of stock portfolios, namely group stock portfolio. Each chromosome consists of three parts. Grouping and stock parts are used to indicate how to divide stocks into groups. Stock portfolio part is used to represent the purchased stocks and their purchased units. The fitness of each...
To improve the spectral efficiency of a cognitive radio system, sensing based spectrum sharing (SBSS) technique combines the advantages of spectrum overlay and spectrum underlay. In this paper, we study the performance of SBSS under primary users' (PUs') rate loss constraint. To be specific, efficient algorithms are introduced to find the optimal sensing time and power allocation in both single-carrier...
This paper concerns the balance between exploration and exploitation for the uncertain environment based on the particle swarm optimizer. Furthermore, the empirical analysis is based on the proposed membership function AEr and AEi, which can measure the distinctions between exploration and exploitation more precisely than before. The experiments are orthogonal designed under different circumstances...
Since various objective functions should be considered for optimizing the portfolio, this study proposes a multi-objective genetic portfolio optimization approach with user's requests for deriving Pareto solutions. The two objective functions used in this study are return on investment and suitability of a portfolio. The suitability of a chromosome consists of a portfolio penalty and an investment...
In designing reliable power distribution networks (PDN) for power integrity (PI), it is essential to stabilize voltage supply to devices on chip. We usually employ decoupling capacitor (decap) to suppress the noise generated by the switching of devices. There have been numerous prior works on how to select/insert decaps in chip, package, or board to maintain PI, however optimal decap selection is...
In recent years there is a growing interest in the research of applying genetic algorithms (GAs) for dynamic optimization problems (DOPs), and several approaches have developed to deal with DOPs. Cloud model is a model of transforming a qualitative concept to a set of quantitative numerical values. A new hybrid genetic algorithm based on cloud model is proposed in this paper, cloud model is used to...
Under the background of the balance of exploration and exploitation, this paper analyzes the causes of the optimization hardness by using the concepts of effective ratio of exploration and exploitation. Then, a novel method is proposed to estimate the optimal feature factor, which is the essential part of optimal contraction theorem. At last, the method is tested with eight test functions. Some disadvantages...
The whole mechanical design process is redefined with image representing each key conception and procedure. Image is considered to be the basic element in design process and also a medium for bridging the gap between the human and machine design. Besides, the knowledge and experience on which mechanical design is strongly based are described as a store of high dimensional images in human mind and...
This paper proposes a predator-prey cellular genetic algorithm to solving dynamic optimization problems. A predator-prey model replaces the evolution rule in regular cellular genetic algorithm, which is more similar to the evolution scheme in real world. It contains two different populations: predator and prey, both of them are dynamic changes with predatory operation. The predators and preys are...
A new 2D walking pattern generation method is proposed for biped robots in this paper. The key feature of the proposed method is to obtain an optimal walking pattern on-line with the largest stability in the sense of zero moment point (ZMP) subject to the constraints of torque and velocity of the joint actuators. With the aids of a 3-link dynamic model of the robot legs and third-order spline interpolation,...
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