An ethylene plant employs multiple cracking furnaces in parallel to convert various hydrocarbon feedstocks to smaller hydrocarbon molecules. The continuous operational performance of cracking furnaces gradually decays...
详细信息
The problem of output feedback adaptive stabilization is addressed for a class of stochastic nonlinear systems with unknown time-varying delays and unknown control directions in this paper. Firstly, the unknown contro...
详细信息
ISBN:
(纸本)9789881563897
The problem of output feedback adaptive stabilization is addressed for a class of stochastic nonlinear systems with unknown time-varying delays and unknown control directions in this paper. Firstly, the unknown control coefficients are lumped together by using a linear state transformation, and the original system is transformed into a new system for which control design becomes feasible. Then, after the design of a novel neural observer, an output feedback adaptive neural network(NN) controller is developed for such systems by combining the Dynamic Surface control(DSC) technique, the Nussbaum gain function(NGF)method and the Lyapunov-Krasovskii method. The proposed controller ensures that all signals in the closed-loop systems are bounded in probability. Finally, a simulation example is given to verify the effectiveness and applicability of the proposed control design.
The application of appropriate advanced treat- ment process in the municipal wastewater treatment plants （WWTPs） has become an important issue considering the elimination of emerging contaminants, such as pharma- ce...
详细信息
The application of appropriate advanced treat- ment process in the municipal wastewater treatment plants （WWTPs） has become an important issue considering the elimination of emerging contaminants, such as pharma- ceutical and personal care products （PPCPs）. In the present study, the removal of 13 PPCPs belonging to different therapeutic classes by the sequential ultraviolet （UV） and ozonation process in a full-scale WWTP in Beijing was investigated over the course of ten months. Most of the target PPCPs were effectively removed, and the median removal efficiencies of individual PPCPs, ranging from -13% to 89%, were dependent on their reaction rate constants with molecular ozone. Noticeable fluctuation in the removal efficiencies of the same PPCPs was observed in different sampling campaigns. Nevertheless, the sequential UV and ozonation process still made a significant contribution to the total elimination of most PPCPs in the full-scale WWTP, by compensating for the poor or fluctuant removal performance of PPCPs by biologic treatment process.
To solve the premature convergence problem of particle swarm optimization(PSO) in dealing with complex high dimensional function optimization, a novel hybrid particle swarm optimization algorithm merging crossover mut...
详细信息
Petrochemical industry plays an important role in the development of the national economy. Purified terephthalic acid(PTA) is one of the most important intermediate raw materials in the petrochemical and chemical fibe...
详细信息
Petrochemical industry plays an important role in the development of the national economy. Purified terephthalic acid(PTA) is one of the most important intermediate raw materials in the petrochemical and chemical fiber industries. PTA production has two parts:p-xylene(PX) oxidation process and crude terephthalic acid(CTA) hydropurification process. The CTA hydropurification process is used to reduce impurities, such as 4-carboxybenzaldehyde, which is produced by a side reaction in the PX oxidation process and is harmful to the polyester industry. From the safety and economic viewpoints, monitoring this process is necessary. Four main faults of this process are analyzed in this study. The common process monitoring methods always use T^2 and SPE statistic as control limits. However, the traditional methods do not fully consider the economic viewpoint. In this study, a new economic control chart design method based on the differential evolution(DE) algorithm is developed. The DE algorithm transforms the economic control chart design problem to an optimization problem and is an excellent solution to such problem. Case studies of the main faults of the hydropurification process indicate that the proposed method can achieve minimum profit *** method is useful in economic control chart design and can provide guidance for the petrochemical industry.
In this paper, explicit model predictive control (MPC) schemes for discrete-time linear-invariant multi-rate systems with constraints on inputs and states are studied. The optimization problem of multi-rate predictive...
详细信息
In this paper, explicit model predictive control (MPC) schemes for discrete-time linear-invariant multi-rate systems with constraints on inputs and states are studied. The optimization problem of multi-rate predictive control systems can be formulated by solving a multiparametric linear program (mp-LP), and the explicit state feedback control laws are developed. Further, based on the closed-loop multi-rate piecewise affine (PWA) structure, stability analysis is presented by linear matrix inequality (LMI). The simulation results show the effectiveness of the explicit MPC for multi-rate system.
Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety...
详细信息
Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging informa- tion technologies such as arti cial intelligence (AI) are quite promising as a means of overcoming these dif culties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety;② knowledge-based reasoning for process safety;③ accurate fusion of heterogeneous data from various sources;and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.
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...
详细信息
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.
Particle swarm optimization methods for optimization problems tend to search premature solutions. This paper presents an improved particle swarm optimization algorithm merging chaotic and harmony searches. The chaos p...
详细信息
Particle swarm optimization methods for optimization problems tend to search premature solutions. This paper presents an improved particle swarm optimization algorithm merging chaotic and harmony searches. The chaos particle swarm optimization method is stable, robust and adaptable. The harmony search algorithm is a meta heuristic algorithm for simulating band tuning to obtain an optimal harmonized process with a global search. Results for four standard test functions show that this chaos particle swarm optimization algorithm with a harmony search (CPSO-HS) can jump out of local optimums with fast convergence and good stability. This algorithm has been successfully applied to parameter estimates for a heavy oil thermal cracking model.
暂无评论