Modeling And Optimization Method Of Continuous Process Production Scheduling Based On Controlled Hybrid Petri Nets

Process industry is the mainstay of the national economy and acts as a very important function. So the nation has invested a lot of money, manpower and material resources to modernize the process industry enterprise in existence and the implementation of CIPS (Computer Integrated Processing System) is popularized. Production scheduling lies in the middle level of the structure of CIPS and it is the command center of the process industry production. Improving the quality and efficiency of production scheduling is very important to increase the economic and social benefit. So the research of the modeling and optimization method of production scheduling for process industry has significant meanings.Process industry is composed of two kinds of production process—continuous process and batch process. In the continuous process, such as oil refining, chemical fertilizer and nitric acid industry, the raw material, semi-product and final product are almost liquid and the production process is longtime continuous. Its production process has physical and chemical transformations and it has the characteristics of complexity, uncertainty, nonlinearity, multi-constrain and multi-resource collaboration. Its scheduling problem has highly coupling characteristic in mathematics and can be hardly solved. At the same time, the material flow in continuous process is continuous and the buffer is limited. So the production scheduling has more demand for the immediateness, coordination and reliability. Therefore this paper takes the modeling and optimization of continuous process production scheduling as the main research object.To solve the scheduling problem of complex continuous process, single model can not get correct description and analysis, so multi-model is needed. Based on this idea, this paper proposes a kind of "simulation plus optimization" modeling structure for continuous process static scheduling and proposes a dynamic scheduling modeling method based on controlled hybrid Petri nets and event logic nets which combines controlled hybrid Petri nets, logic programming and experience rules together. The scheduling modeling based on controlled hybrid Petri nets not only can realize the visualization and simulation of the production process, but also can do some analysis and computation. Therefore an effective method to solve the problems of continuous process production scheduling is found. This paper did some research from the following respects.1. Although continuous process mainly runs continuously, but it also has discrete events such as scheme switch and equipment failure, so it is a hybrid system in nature. The simulation modeling of continuous process not only need to reflect the hybrid characteristic in the production process but also need to embody the influence of the scheduling scheme for the production process. Therefore, this paper proposes a new kind of controlled hybrid Petri nets, which extend the existing hybrid Petri nets and introduce control places for continuous transitions and discrete transitions. This kind of controlled hybrid Petri nets not only can embody the characteristics of the continuou process, but also can fulfill the modeling requirements of the production scheduling. In the controlled hybrid Petri nets, the continuous places and the continuous transitions represent the continuous material flow and the continuous running of the equipments respectively. The discrete places and the discrete transitions represent the states of the equipments and the occurrence of discrete events respectively. The continuous control places and the discrete control places represent the optimal control for the corresponding continuous transitions and discrete transitions.2. The concept of this kind of controlled hybrid Petri nets is given. The rules of enabling and firing and the dynamic characteristic are researched. The method of constructing the controlled hybrid Petri nets under the environment of Matlab Simulink/Stateflow is introduced in detail. The simulation model of continuous process can be constructed by using controlled hybrid Petri nets. This simulation model not only can reflect the continuous characteristic of continuous process, but also can embody the impact of discrete events such as equipment failure and equipment restore for the production. This simulation model offers a uniform expression form for different kinds of continuous process and establishes the base for the scheduling model. The introduction of the control for the transitions offers conditions for the implement of the scheduling scheme and the validation for the scheduling results.3. A static scheduling modeling method based on controlled hybrid Petri nets is proposed. After constructing the simulation model of production equipments and storing equipments by using controlled hybrid Petri nets, the simulation model of the whole continuous process production system can be got. The constrains of the production ability of production equipments, the storing ability of storing equipments, the processing recipes, the production plan and the supply of raw materials can be got by analyzing controlled hybrid Petri nets. Combined with certain objective, the static scheduling model of continuous process can be got. Simulating the continuous process by using controlled hybrid Petri nets not only can simplify the analyzing procedure of the complex constrain relation in continuous process, but also can testify the implement effect of the scheduling scheme and visualize the modeling procedure.4. To deal with the nonlinearity characteristic commonly existing in the scheduling model of continuous process, a hybrid particle swarm optimization algorithm with local chaos search is proposed. This hybrid algorithm takes the basic particle swarm optimization algorithm as the main body. It combines the chaos search mechanism to enhance the search ability of the overall situation and gets rid of the attraction of local extremum. As the precision of the resolution and the speed of convergent are improved, this algorithm gets better effect in resolving the scheduling model of continuous process.5. A static scheduling model of hydrogen balance in a refinery is constructed by using the static scheduling modeling method based on controlled hybrid Petri nets. This model takes the influence of the hydrogen price and the repair plan of the equipments for the hydrogen utilization into account. The hybrid particle swarm optimization algorithm with local chaos search is used to resolve the static scheduling model of hydrogen balance in one month. The balance of hydrogen production and utilization is achieved, and at the same time, the cost of hydrogen utilization is reduced as much as possible.6. As the sudden events such as equipment failure often occur in continuous process, a dynamic scheduling model based on controlled hybrid Petri nets and event logic nets is constructed. In this model, controlled hybrid Petri nets are used to construct the simulation model of continuous process. The constraints of the dynamic scheduling model can be got from this simulation model. According the experience rules in the production process, some logic variables are added into the constraints to represent the switch choice of the constraints, and then the logic programming model can be got. A kind of special Petri nets called event logic nets is defined to realize the conversion from the sudden event in the production process simulation model to the logic variable in the logic programming model. It takes the event output places in controlled hybrid Petri nets as the input places and the discrete control places in controlled hybrid Petri nets as the output places. The ratiocination of the logic proposition is achieved through the logic transitions in the event logic nets. It can response to the sudden events occurring in controlled hybrid Petri nets and control the discrete transition in controlled hybrid Petri nets according to experience rules. At the same time, the logic output places in event logic nets are associated with the logic variables in the logic programming model. The corresponding logic constraints in the logic programming model are chose and the dynamic updating of the scheduling model is realized. The resolution of the logic programming model is taken as the marking of the continuous control places in controlled hybrid Petri nets to realize the control for the controlled continuous transitions. Under the control of the discrete control places and the continuous control places, controlled hybrid Petri nets run steadily in the new scheduling scheme.7. A typical chemical production process is taken as an example to illustrate the dynamic scheduling modeling method based on controlled hybrid Petri nets. To reduce the influence for other equipments when sudden events occur in the production process and make the whole production system running continuously and steadily, we summarize 16 experience rules and convert them into the form of event logic nets. This can realize the automatic procedure of "event occur—logic ratiocination—control output". The objective in the logic programming model takes the maximum of the profit and the long steady running of the system into account altogether. By comparison of different scheduling models, although this model reduces the short-term profit a little, it has obvious advantage in keeping the production longtime steadily running. This is more important for continuous process, so the scheduling results of this model are more feasible.Finally, the research of this paper is summarized and the problems that need to research next are put forward.