In this paper, we consider the security issue in a wireless sensor network (WSN). We investigate distributed state estimation over a WSN under hostile attacks. To defend against malicious attacks, we propose a novel e...
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A double-layered model predictive control(MPC), which is composed of a steady-state target calculation(SSTC)layer and a dynamic control layer, is a prevailing hierarchical structure in industrial processcontrol. Base...
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A double-layered model predictive control(MPC), which is composed of a steady-state target calculation(SSTC)layer and a dynamic control layer, is a prevailing hierarchical structure in industrial processcontrol. Based on the reason analysis of the dynamic controller infeasibility, an on-line constraints softening strategy is given. At first, a series of regions of attraction(ROA) of the dynamic controller is calculated according to the softened constraints;then a minimal ROA containing the current state is chosen and the corresponding softened constraint is adopted by the dynamic controller. Note that, the above measures are performed on-line because the centers of the above ROA are the steady-state targets calculated at each instant. The effectiveness of the presented strategy is illustrated through two examples.
This study provides insights into the distillation sequence optimization of refinery system in a methanol to propylene plant with extractive distillation under multiple conditions. The simulated annealing algorithm(SA...
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This study provides insights into the distillation sequence optimization of refinery system in a methanol to propylene plant with extractive distillation under multiple conditions. The simulated annealing algorithm(SA) with relative cost function was used to solve a meaningful optimization problem. It was observed that different conditions had differed on the flowsheet. Case study shows the effectiveness of the proposed method.
Problem statement: The aim of this study was to find the empirical model that describes the growth kinetics of Dunaliella salina, with low production cost and to estimate parameters of this model. Approach: In this st...
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This paper focuses on the problem of adaptive output feedback tracking control for a class of nonstrict-feedback nonlinear systems with unknown control coefficients and quantized input. The difficulty from the unknown...
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ISBN:
(纸本)9781538629185
This paper focuses on the problem of adaptive output feedback tracking control for a class of nonstrict-feedback nonlinear systems with unknown control coefficients and quantized input. The difficulty from the unknown control direction is solved by using the linear state transformation and the Nussbaum gain function(NGF) approach. Based on the combination of input-driven observer, backstepping technique, neural network(NN) parametrization and variable separation method, a novel adaptive output feedback quantized control scheme involving only one adaptive parameter is developed for such systems. The designed quantized controller ensures that all signals of closed-loop systems are semi-globally uniformly ultimately bounded(SGUUB), and the tracking error converges to an adjustable neighborhood of the origin. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed control design.
Traditional level measurements based on sensors were easily affected by circumstance especially in severe industrial process,whose accuracy of measurement cannot meet the control *** order to deal with the problem,a n...
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ISBN:
(纸本)9781509046584
Traditional level measurements based on sensors were easily affected by circumstance especially in severe industrial process,whose accuracy of measurement cannot meet the control *** order to deal with the problem,a new level measurement method based on randomized Hough Transform was *** pre-processing,noise-reduction and filtering to the original image,the randomized Hough Transform was used to recognize the liquid *** results showed that the error of the proposed method is within 2%and the average recognition time is within 0.1 *** proposed method can meet the requirement in industrial fields.
Many systems composed by several interacting subsystems are usually controlled by a distributed control framework. Distributed Model Predictive control(DMPC) strategy, in which each subsystem is controlled by a local ...
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ISBN:
(纸本)9781479947249
Many systems composed by several interacting subsystems are usually controlled by a distributed control framework. Distributed Model Predictive control(DMPC) strategy, in which each subsystem is controlled by a local MPC controller, has advantages of accommodating constraints, less computational cost and high flexibility. In order to improve the global performance and guarantee the system stability, a stabilized DMPC strategy is proposed in this paper, in which subsystems interact through inputs. At first, local initial feasible solutions are achieved based on a Minkowski functional to guarantee the local closed-loop system stabilization. And then the global optimal solutions are obtained through coordination strategy for the sake of reducing iteration time and accelerating the convergence speed efficiently. Finally, the accuracy and efficiency of the proposed scheme is put to test through simulation.
Quality-related fault detection has received extensive attention in recent years. It requires an appropriate supervisory relationship between process variables and quality variables. While the traditional principal co...
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ISBN:
(纸本)9781509046584
Quality-related fault detection has received extensive attention in recent years. It requires an appropriate supervisory relationship between process variables and quality variables. While the traditional principal component analysis(PCA) doesn't consider the relationships between them. Thus we proposed the mutual information principal component analysis(MIPCA) to detect the quality-related faults. MIPCA fully integrates the advantages of mutual information(MI) and PCA. With MIPCA, process variables can be utilized to monitor the process under the supervision of quality variables and judge a fault is whether related to the quality or not. Finally, the feasibility and effectiveness of the MIPCA are verified in Tennessee Eastman process(TEP).
In this paper,a neural network based model predictive control(MPC) strategy is proposed to for the cellular uptake(as a function of space and time) of a ***,a time/space separation method is used to transform the ...
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ISBN:
(纸本)9781538629185
In this paper,a neural network based model predictive control(MPC) strategy is proposed to for the cellular uptake(as a function of space and time) of a ***,a time/space separation method is used to transform the high-dimensional spatiotemporal data into low-dimensional temporal ***,the MPC strategy is posed using the identified temporal radial basis function neural network *** the solution of NN-based MPC is obtained by a golden section method that can shorten the solution time of the optimization *** accuracy and effectiveness of this approach are demonstrated on an example motivated by tissue engineering.
In this paper,we consider the privacy preserving problem of consensus ***,we introduce a privacy preserving scheme,where each node produces and transmits a sequence of random values with their mean equaling to the nod...
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ISBN:
(纸本)9781538629185
In this paper,we consider the privacy preserving problem of consensus ***,we introduce a privacy preserving scheme,where each node produces and transmits a sequence of random values with their mean equaling to the node's initial *** show that the network can reach average consensus with privacy preserving scheme,and provide a sufficient condition under which the initial state of one node can be inferred ***,we study the privacy preserving performance when there exists an attacker who can intercept the data transmitted on the *** a ring network,aiming at the attacker with limited power,we find the optimal attacking strategy to maximize the probability of the privacy ***,the simulations verify the derived theoretical results.
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