This tutorial paper provides an overview of where techniques based on hybrid dynamic models are suitable or promising for designing controllers of industrial plants, in particular chemical processing systems. After su...
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ISBN:
(纸本)0780395670
This tutorial paper provides an overview of where techniques based on hybrid dynamic models are suitable or promising for designing controllers of industrial plants, in particular chemical processing systems. After summarizing the typical control tasks prevalent in the hierarchical automation structure of industrial plants, the paper focusses on two techniques employing hybrid models that recently have gained much attention by the research community: the algorithmic verification of safety-related discrete controls, and the optimal control of large transitions, like startup, shutdown, or product switch-over.
Number estimation of controllers is a fundamental question in pinning synchronization of complex networks. This paper studies the problem of controller number in synchronizing a complex network of coupled dynamical sy...
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Number estimation of controllers is a fundamental question in pinning synchronization of complex networks. This paper studies the problem of controller number in synchronizing a complex network of coupled dynamical systems by means of pinning. For a complex network with a symmetric coupling matrix and full coupling between the nodes, we formulate network synchronization via pinning as a linear matrix inequality criterion, and provide a lower bound and an upper bound of the controller number for a given complex network with fixed architecture. Several numerical examples with Barabási-Albert network topologies are provided to verify our theoretical results.
The technology readiness levels of cloud infrastructure and edge devices have increased significantly in recent years. This means that companies now have a growing number of computing environments at their disposal th...
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The authors present a knowledge-based approach to the satisfactory solution in optimization problems. Both operations-research algorithms and knowledge-engineering technology are used and supplemented with each other ...
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ISBN:
(纸本)7800030393
The authors present a knowledge-based approach to the satisfactory solution in optimization problems. Both operations-research algorithms and knowledge-engineering technology are used and supplemented with each other in this approach. To develop this approach, an essential theorem, i.e., a dividing optimization principle, and a concept, i.e., a turning region, have been proposed. The major steps of the knowledge-based approach to the satisfactory solution for linearly constrained optimization problems are as follows: give an initial dividing hyperplane and move it in one direction step by step to find the turning region, which then should be compressed till the criterion of the satisfactory solution is satisfied. Finally, a numerical example in industrial systems illustrates that the proposed approach can effectively provide the satisfactory solution with less computer time.
The authors present a novel heuristic optimization technique called the heuristic path propagating algorithm, in which the search procedure is based on the path extending mode determined by the path evaluation functio...
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ISBN:
(纸本)7800030393
The authors present a novel heuristic optimization technique called the heuristic path propagating algorithm, in which the search procedure is based on the path extending mode determined by the path evaluation function and the constraint deviation vector. The procedures carried out by algorithm include discretization of the parameter space, partitioning of the control functions, computation of the path evaluation function and the constraint deviation vector, and construction of the heuristic rule base. The advantages of the algorithm are its high searching efficiency and its reduced computation and memory requirement. The algorithm does not require the calculation of the heuristic function for every node in the problem solution space. The use of the algorithm to solve the temperature-set-point optimization problem of continuous reheating furnaces is shown in detail. It has been successfully applied to a real-time computer control system for a production-scale reheating furnace.
In the era of Industry 4.0 (I4.0), Cyber Physical Production Systems (CPPS) and upcoming industrial transformations, there's a great impulse for smarter, more connected, and adaptable industries. To support this s...
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The authors propose a fast predicate pattern matching algorithm based on a modified constraint satisfaction algorithm and Rete match algorithm. An illustrative example shows that the proposed algorithm could effective...
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ISBN:
(纸本)7800030393
The authors propose a fast predicate pattern matching algorithm based on a modified constraint satisfaction algorithm and Rete match algorithm. An illustrative example shows that the proposed algorithm could effectively improve the real-time performance of expert systems. It can also be used for the purpose of AI (artificial intelligence) programming.
Signed Directed Graphs (SDGs) are among the very beneficial, and well-known tools for fault diagnosis in chemical process plants. Based on the size of the process plant, their corresponding SDGs can be very large in s...
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Presented is a novel time-domain optimal model reduction method that could lead to each state variable of the reduced model approaching to the corresponding one of the original model in the sense of minimizing the qua...
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Presented is a novel time-domain optimal model reduction method that could lead to each state variable of the reduced model approaching to the corresponding one of the original model in the sense of minimizing the quadratic error. A 15th-order ingot-pit system model is reduced effectively to a 4th-order one by using the method proposed. The method has been applied to establishing a state space model with low order from experimental data of a pilot binary distillation column. In addition, the microcomputer-based optimal state feedback control is implemented successfully. Advantages of the model reduction method proposed include: 1. better agreement between the original model and the reduced one, 2. clearer physical meaning, and 3. more convenience for applications. Simulation results also show that the method can be applied to reducing a high-order continuous time model into a low-order discrete-time model directly.
作者:
Najim, KPoznyak, ASIkonen, EUniv Oulu
Dept Process & Environm Engn Syst Engn Lab FIN-90014 Oulu Finland ENSIACET
Proc Control Lab F-31077 Toulouse 4 France CINVESTAV
INP Dept Automat Control Mexico City 07300 DF Mexico
This paper presents an algorithm for optimization of a multimodal scalar-argument function based on a team of learning stochastic automata with binary actions (outputs) 0 or 1. The action of the team of automata consi...
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This paper presents an algorithm for optimization of a multimodal scalar-argument function based on a team of learning stochastic automata with binary actions (outputs) 0 or 1. The action of the team of automata consists of a digital number which represents the environment input. The probability distribution associated with each automaton is adjusted using a modified version of the Bush-Mosteller reinforcement scheme with a continuous environment response and a time-varying correction factor. The asymptotic properties of this optimization algorithm are presented. An example illustrates the feasibility of this optimization algorithm. (C) 2004 Elsevier Ltd. All rights reserved.
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