In industries, overhead cranes are commonly employed to lift and lower materials or to move them horizontally. A combining sliding mode control method is proposed for overhead crane systems in this paper. The ideas be...
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In industries, overhead cranes are commonly employed to lift and lower materials or to move them horizontally. A combining sliding mode control method is proposed for overhead crane systems in this paper. The ideas behind the combining sliding mode are as follows. First, an intermediate variable is introduced by dividing the system states into two groups. Then, a sliding surface is defined on basis of the intermediate variable. The control law is deduced from Lyapunonv direct method to asymptotically stabilize the sliding surface. The stability of the system states is also proven. Simulation results demonstrate the feasibility of the presented method through transport control of an overhead crane system.
Forecasting of process outages for reducing downtime and machine scrap parts have been actively pursued in the manufacturing industries to ensure that maintenance is carried out only when required. In this paper, we p...
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Forecasting of process outages for reducing downtime and machine scrap parts have been actively pursued in the manufacturing industries to ensure that maintenance is carried out only when required. In this paper, we propose a precognitive maintenance framework based on mixed time- and condition-based models to predict both wear and degradation stage of realistic engineering systems. The decision-making framework performs stage classification using support vector machines and wear estimation using time-based autoregressive moving average with exogenous inputs models. Our proposed framework is supported by mathematical rigour, and its effectiveness is evaluated with experimental results on a high-speed industrial computer numerical control milling machine for tool wear stage identification and wear estimation.
A simple model for the contrast-detection autofocusing problem is considered. The variance of the image is examined as a focus function. We prove that the standard convergence rate of the variance estimate (empirical ...
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In recent years, the wireless Body Area Network (BAN) technology has made significant advances. There is a tremendous need for the development of this technology. However, wireless BANs require much higher reliability...
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Fault recovery is vital to WSNs since node death is a typical fault. Aiming to recover the "coverage hole", a Recovery Algorithm based on Minimum Distance Redundant Nodes (MDRN) is proposed in this paper. By...
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Fault recovery is vital to WSNs since node death is a typical fault. Aiming to recover the "coverage hole", a Recovery Algorithm based on Minimum Distance Redundant Nodes (MDRN) is proposed in this paper. By employing redundant nodes carefully, the recovery algorithm is deployed on the sink node with unconstrained energy consumption which knows the locations of all active nodes and redundant nodes in the WSNs. Simulation results demonstrate that, by choosing appropriate number of redundant nodes, this algorithm will have great recovery accuracy and coverage quality, also achieve the purpose of prolonging the lifecycle of WSNs.
Texture synthesis is the field of computer graphics and related basic core issues. Studies have shown that the MRF model-based two-dimensional image texture synthesis algorithm, the synthesis results are directly affe...
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The utilization of biomimicry of bacterial foraging strategy was considered to develop an adaptive control strategy for mobile robot, and a bacterial foraging approach was proposed for robot path planning. In the prop...
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The utilization of biomimicry of bacterial foraging strategy was considered to develop an adaptive control strategy for mobile robot, and a bacterial foraging approach was proposed for robot path planning. In the proposed model, robot that mimics the behavior of bacteria is able to determine an optimal collision-free path between a start and a target point in the environment surrounded by obstacles. In the simulation, two test scenarios of static environment with different number obstacles were adopted to evaluate the performance of the proposed method. Simulation results show that the robot which reflects the bacterial foraging behavior can adapt to complex environments in the planned trajectories with both satisfactory accuracy and stability.
Energy plants represent large energy consumers with a wide array of energy needs, assets (e.g. boilers, chillers, storage, on-site generation), and constraints on operations. An innovative energy management system for...
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Energy plants represent large energy consumers with a wide array of energy needs, assets (e.g. boilers, chillers, storage, on-site generation), and constraints on operations. An innovative energy management system for energy plants is presented in this paper. Through predictive optimization of plant assets, energy analytics, pricing signals, and historical and realtime data, the online energy management system supplies energy plants with salient hourly, real-time recommendations and enables “what-if” analysis to achieve improved economic efficiency. Within a systems context, the paper draws upon ideas from power systems and highlights technical issues related to plant optimization. The paper also describes actual implementations of the energy management solution at two energy plants in the US, providing economic details and an analysis of the savings achieved.
High-fidelity building energy simulation models are established on well-known physical laws and attempt to faithfully represent a real building. The numerical solution of differential algebraic equations that interpre...
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High-fidelity building energy simulation models are established on well-known physical laws and attempt to faithfully represent a real building. The numerical solution of differential algebraic equations that interpret thermal balance of buildings is included in building energy simulation models. It thereby leads to highly discontinuous systems that involve a large number of sub-routine calls and model switches during the execution. To acquire a building energy simulation model with good quality, parameter sensitivity analysis is well-advocated since it aims to target those parameters from the parameter pool in a specific building that hold more influence on the building thermal performance than others. Since building energy simulation models are given in a large piece of program codes and encapsulate a series of sub-models, the existing sensitivity analysis is built on Monte Carlo simulation and statistics-based random sampling methods only, e.g., Monte Carlo sampling and Latin Hypercube sampling methods, which are extremely time-consuming. We propose to perform the sensitivity analysis of a first-principle high-fidelity building energy simulation model via a straightforward differential sensitivity analysis method that relies on the estimation of derivatives. A key technical challenge is that the complexity of the model prohibits the analytical differentiation, while the numerical differentiation is sensitive to step size and suffers from the truncation error. We, hence, propose to adopt an automatic differentiation method, which exploits the operator overload feature of object oriented programming language, to obtain accurate numerical estimations of derivatives in an automated and computationally efficient way.
For the well-known buck converter, we replace the inductor and capacitor by a transmission line. In other words, the lumped reactive elements are substituted by a distributed element. This results in a completely diff...
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