The p-xylene (PX) oxidation process is of great industrial importance because of the strong demand of the global polyester fiber. A steady-state model of the PX oxidation has been studied by many researchers. In our p...
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The computation burden in the model-based predictive control algorithm is heavy when solving QR optimization with a limited sampling step, especially for a complicated system with large dimension. A fast algorithm is ...
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Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks...
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Optimizing operational parameters for syngas production of Texaco coal-water slurry gasifier studied in this paper is a complicated nonlinear constrained problem concerning 3 BP(Error Back Propagation) neural networks. To solve this model, a new 3-layer cultural evolving algorithm framework which has a population space, a medium space and a belief space is firstly conceived. Standard differential evolution algorithm(DE), genetic algorithm(GA), and particle swarm optimization algorithm(PSO) are embedded in this framework to build 3-layer mixed cultural DE/GA/PSO(3LM-CDE, 3LM-CGA, and 3LM-CPSO) algorithms. The accuracy and efficiency of the proposed hybrid algorithms are firstly tested in 20 benchmark nonlinear constrained functions. Then, the operational optimization model for syngas production in a Texaco coal-water slurry gasifier of a real-world chemical plant is solved effectively. The simulation results are encouraging that the 3-layer cultural algorithm evolving framework suggests ways in which the performance of DE, GA, PSO and other population-based evolutionary algorithms(EAs) can be improved,and the optimal operational parameters based on 3LM-CDE algorithm of the syngas production in the Texaco coalwater slurry gasifier shows outstanding computing results than actual industry use and other algorithms.
This paper presents robust optimization models for a multi-product integrated problem of planning and scheduling (based on the work of Terrazas-Moreno & Grossmann (2011) [1]) under products prices uncertainty. Wit...
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This paper presents robust optimization models for a multi-product integrated problem of planning and scheduling (based on the work of Terrazas-Moreno & Grossmann (2011) [1]) under products prices uncertainty. With the objective of maximizing the total profit in planning time horizon, the planning section determines the amount of each product, each product distributed to each market, and the inventory level in each manufacturing site during each scheduling time period;the scheduling section determines the products sequence, start and end time of each product running in each production site during each scheduling time period. The uncertainty sets used in robust optimization model are box set, ellipsoidal set, polyhedral set, combined box and ellipsoidal set, combined box and polyhedral set, combined box, ellipsoidal and polyhedral set. The genetic algorithm is utilized to solve the robust optimization models. Case studies show that the solutions obtained from robust optimization models are better than the solutions obtained from the original integrated planning and scheduling when the prices are changed.
This paper investigates consensus of nonlinear multi-agent systems with stochastic disturbances. By sampling signals from the leader agent at discrete instants, leader-following consensus in the mean square is achieve...
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ISBN:
(纸本)9781479917631
This paper investigates consensus of nonlinear multi-agent systems with stochastic disturbances. By sampling signals from the leader agent at discrete instants, leader-following consensus in the mean square is achieved based on the theory of Ito stochastic differential equations and Lyapunov-Krasovskii functional stability theory with a sufficient condition derived. Then two special cases: 1) the transmittal delay is very small, which can be approximately regards as zero;2) the interconnections of agents are undirected are discussed, respectively. Finally, an example is given to verify the effectiveness of the theoretical results.
This paper investigates the problem of H∞ filter design for a class of nonlinear networked system based on T-S fuzzy model. Multiple stochastic time-varying delays and some incomplete information are considered simul...
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ISBN:
(纸本)9781467374439
This paper investigates the problem of H∞ filter design for a class of nonlinear networked system based on T-S fuzzy model. Multiple stochastic time-varying delays and some incomplete information are considered simultaneously. Incomplete information includes randomly occurring sensor saturation and packet dropouts. Stochastic time-varying delays are depicted as a sequence of stochastic and independent variables, which take values on 0 and 1. Two sets of Bernoulli distributed white noises are introduced to describe randomly occurring sensor saturation and packet dropouts. System conservatism is reduced due to introduce an approach of piecewise quadratic Lyapunov function. By solving a set of linear matrix inequalities(LMIs), the filter parameters are obtained. Finally, a simulation example is provided to illustrate the effectiveness of the proposed filter design approach.
The p-xylene(PX) oxidation process is of great industrial importance because of the strong demand of the global polyester fiber.A steady-state model of the PX oxidation has been studied by many *** our previous work,a...
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The p-xylene(PX) oxidation process is of great industrial importance because of the strong demand of the global polyester fiber.A steady-state model of the PX oxidation has been studied by many *** our previous work,a novel industrial p-xylene oxidation reactor model using the free radical mechanism based kinetics has been ***,the disturbances such as production rate change,feed composition variability and reactor temperature changes widely exist in the industry *** this paper,dynamic simulation of the PX oxidation reactor was designed by Aspen Dynamics and used to develop an effective plantwide control structure,which was capable of effectively handling the disturbances in the load and the temperature of the *** responses of the control structure to the disturbances were shown and served as the foundation of the smooth operation and advancedcontrol strategy of this process in our future work.
Without the explicit process identification, the authors propose a model-free adaptive control framework for unknown plant by using the concept of equivalent dynamic linearisation controller. The controller has linear...
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Batch process data are essentially *** existing methods on batch process monitoring such as multiway partial least squares(MPLS)and multiway principal component analysis(MPCA)are based on unfolding procedure which rep...
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Batch process data are essentially *** existing methods on batch process monitoring such as multiway partial least squares(MPLS)and multiway principal component analysis(MPCA)are based on unfolding procedure which represents three-way batch data as a vector in high-dimensional *** a result of destroying data structures,these methods may lead to information *** this article,batch data are considered as a third order tensor and HOPLS is introduced to deal with the data directly instead of performing unfolding procedure.A HOPLS-based online monitoring approach is developed and two new statistics:HO-SPE and HO-T2are constructed for fault detection and *** effectiveness of this approach is illustrated by a benchmark fed-batch penicillin fermentation *** comparison of monitoring results shows that the proposed approach is superior to MPLS,and it can achieve accurate detection of various types of process faults occurring in the batch operation.
This paper presents robust optimization models for a multi-product integrated problem of planning and scheduling (based on the work of Terrazas-Moreno & Grossmann (2011) [1]) under products prices uncertainty. Wit...
详细信息
This paper presents robust optimization models for a multi-product integrated problem of planning and scheduling (based on the work of Terrazas-Moreno & Grossmann (2011) [1]) under products prices uncertainty. With the objective of maximizing the total profit in planning time horizon, the planning section determines the amount of each product, each product distributed to each market, and the inventory level in each manufacturing site during each scheduling time period;the scheduling section determines the products sequence, start and end time of each product running in each production site during each scheduling time period. The uncertainty sets used in robust optimization model are box set, ellipsoidal set, polyhedral set, combined box and ellipsoidal set, combined box and polyhedral set, combined box, ellipsoidal and polyhedral set. The genetic algorithm is utilized to solve the robust optimization models. Case studies show that the solutions obtained from robust optimization models are better than the solutions obtained from the original integrated planning and scheduling when the prices are changed.
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