Compiling an Optimized Decision Tree for Dispatch Functions in Automatic Process Control System

This paper aims to discuss the design and implementation of automatic control system for chemical production line based on PLC. With the rapid development of chemical industry and the intensification of market competition, it has become an important demand for chemical enterprises to improve production efficiency, ensure product quality and realize automation and intelligence of production process. Firstly, this paper analyzes the characteristics and requirements of chemical production line, as well as the requirements and objectives of automatic control system. Then, the overall architecture design, hardware design, software design, system implementation and testing process of the automatic control system of chemical production line based on PLC are described in detail. The feasibility and effectiveness of the system are verified by the analysis of practical application cases. The research results show that the automatic control system of chemical production line based on PLC can significantly improve production efficiency, reduce production costs, ensure product quality and enhance the market competitiveness of chemical enterprises. The research in this paper provides new ideas and methods for the design and implementation of automatic control system in chemical industry.

The article offers mathematical tools for programming dispatcher tasks on programmable logic matrices, which allow to obtain closed axiomatic models of the dispatcher’s professional activity in the course of the dispatcher’s dialogue with the computer and implement it in the form of optimal combinational logic schemes with pairwise alternative outputs. These tools implement a user-friendly interface for modeling a logically complete consistent system of axioms written in the production language in a tabular form that resembles decision tables with a limited input. The modeling dialog completely frees the dispatcher from the need to know the properties of axiomatic models and requires only professional skills of dispatcher management. Its function in this dialogue is only to specify the desired action in a specific situation that occurs during the object management process. Such situations are constantly formed during the field work in crop production. Sudden failure of power units, two or three-day period of adverse weather increases the risk of violation of agricultural deadlines. This requires prompt decision - making on re-completing units, changing the plan of mechanized work. The search of all possible situations and obtaining on their basis an optimal set of consistent products closing the axiomatic model is provided exclusively by the interface software, which is developed using algorithms for negating and minimizing disjunctive normal forms of logical functions and includes software tools for modeling logically complete consistent decision tables and optimizing them in order to obtain optimal combinational logical devices with their subsequent hardware implementation in the form of microchips. In addition, these software tools are offered as one of the tools for software implementation of branched algorithms with high complexity indicators according to M. V. Arapov in the automated design of control systems for various purposes.

Current development of power engineering in Russia is characterized by deployment of power units with distributed multifunctional automatic process control systems (APCS) based on software and hardware systems (I&C) complex with hierarchical network structure. I&C is the backbone of this structure and APCS creates common information and technological environment of the power unit. Key issues of the multifunctional APCS are associated with lack of the technical efficiency of the I&C, usage of unproven control algorithms and immaturity of the system development technology. Overcoming the identified key issues in the development of the technology of creating I&C and APCS as a whole is associated with the formation of special functionality developed by I&C, their capabilities to use mathematical models of control objects and processes in real time (RT), assessing the information properties of controlled and uncontrolled parameters and generated signals. Performance paradigm (price/quality) of the APCS which answers on these questions can be received only after putting system in the operation and caring additional work on the assessment and optimization of information-functional and technical structures of APCS. The report discusses some new results in solving the indicated issues as part of improving the technology of modern APCS and prospects for their development as the main scientific direction of the Department of Automatic control Systems of ISPU.

A program for handling multiple phases of the design cycle in process control system design

 Abstract—Nowadays, the method of data mining, widely known as KDD (Knowledge-discovery in databases), is researched actively due to increasing amount of data. Decision tree, which is human-readable and understandable, is widely used in the field of rule extraction, data mining, and pattern recognition. Although decision tree is easy for quickly understanding the data, it has many faults in algorithm itself. In this paper, to compensate for these faults, we combined decision table (rough set theory) and ANN (Artificial Neural Network). With this combined algorithm, we could easily obtain more precise rules from iris data. Our experiment was in this order: 1) Find weights by using back propagation (bp) algorithm. (ANN). 2) Use dimensionality reduction method to delete huge amount of irrelevant data. (Rough set theory and decision table). 3) Make decision tree with pruned weights and rules. With ANN algorithm and decision table (dimensionality reduction method), we could easily notice the most influential (high entropy) character of iris data. With this algorithm, we could extract more precise and pruned rule from iris data sets.

Attribute reduction is one of the basic contents in decision table. And it has been proved that computing the optimal attribute reduction is NP-complete. A lot of algorithms for the optimal attribute reduction were proposed in consistent decision table. But most decision tables are inconsistent in fact. In this paper, the judgment theorem with respect to maximum distribution reduction is obtained and the significance of attributes is defined in decision table, from which a polynomial heuristic algorithm for the optimal maximum distribution reduction is proposed. Finally, the experimental results show that this algorithm is effective and efficient.

Aiming at the problems of long response time and poor anti-interference ability of traditional vacuum nano-coating automatic control system, a design of vacuum nano-coating automatic control system based on AVR single-chip microcomputer is proposed. The use of ATmega128L microcontroller and Harvard architecture improves the parallel processing efficiency of the microcontroller. Select the transient voltage suppression diode to protect the power supply of the single-chip microcomputer, optimize the communication circuit, connect an external encryptor to realize the data encryption function, increase the filtering program and optimize the binary code processing function. Using PID (Packet Identifier) control algorithm, the design of nano-coating vacuum automatic control system based on AVR single-chip microcomputer is realized. Compared with the traditional system, when the simulation model and system parameters of the control system constructed in the environment change, the proposed system can be stabilized within 15 seconds, and can be stabilized for 13 seconds after the interference signal is added. The response time of the system is longer. Shorter, stronger anti-interference ability, more suitable for automatic control of vacuum nano-coating.

Purpose. To improve simulation and design of Automatic Control Systems in the SPICE-compatible programs and to obtain separate economic and universal macromodels of PWM controller. Development of an PWM controller economical macromodel for the study of automatic control systems (ACS) in computer-aided design (ECAD) programs, which does not generate algorithmic failures in comparison with the existing models of PWM.Findings. Analysis of SPICE-family applications’ mathematical basis allowed to classifying existing models of PWM-controllers, defining their suitability for ACS simulation. The criteria for the synthesis of new models have been defined. For the SPICE 3G algorithms, the Switch and Averaged models based on behavioral elements has been developed. Universal and economical PWM controller macromodel based on the simple algorithm for determining the output signal with minimum numbers of input parameters has been designed. For the Automated Measuring magnetic susceptibility System, the macromodel of quasi-PWM signal generator have been designed, which is used in the compensation subsystem. This model is different from the existing ones: it synthesizes the staircase output signal instead the pulse one, thus, there is direct control of the amplitude of the output signal, which is taken averaged. The adequacy of the models is confirmed as comparison of the simulation results during investigations of the model already existing in the SPICE program, as well as the results of experiments with real ACS. The modeling of the PWM controller was carried out on the basis of behavioral elements from the ECAD library, simulation (solution of algebra-differential equations systems with programming elements) is based on SPICE algorithms. The object of the study was the simulation process of ACS with the pulse-width principle of adjusting the output value. The subject of the research are the models of PWM controllers.Originality. The new macromodel of PWM controller that meets the criteria of adequacy, reliability and economy, synthesized on the basis of a new approach in modeling objects at the macro level in accordance with the theory of automatic control. Macromodels based in capabilities of behavioral modeling in the program of computer-aided design in Electronics (ECAD). As part of the compensation system studying, the new controller model has been developed, that turns pulse-width modulated signal into amplitude-modulated signal by a certain algorithm. This approach (obtaining a quasi-PWM signal) made it possible to significantly simplify the control unit model, and the model of ACS at whole.Practical value. PWM macromodels expands the mathematical support of ECAD, reduces the probability of the appearance of algorithmic failures and accelerates the modeling of ACS in ECAD. Approach, which used during its synthesis, allows us to build similar models for other software (CAS, CAE).

Introduction. Nowadays, communication systems are mostly digital. One of the tasks of automatic gain control in digital receivers is to maintain analog signals at the appropriately fixed level, which prevents saturation of the analogto-digital converter. Most numerical algorithms are based on floating point arithmetic, and digital automatic gain control is usually implemented using fixed-point arithmetic devices such as programmable logic chips and signal processors. As consequence of fixed-point arithmetic and hardware constraints usage, the out-put significant bits should be truncated correctly. Although many studies mention digital automatic gain control, its characteristics are not considered in detail in terms of the finite capacity of calculators.Objective. The purpose of the study is to analyze dynamic characteristics of digital automatic gain control implemented on a computer for operations on numbers with fixed-point.Materials and methods. Within the frames of the study in Matlab software was developed a mathematical model of digital automatic gain control. The model was implemented on a programmable logic chip.Results. The paper shows the difference in characteristics and features of the digital automatic gain control during operations on fixed-point numbers. The study provides the assessment of the effect of fixed-point signals on the stability of the digital automatic gain control and includes the analysis of causes of spurious oscillations of the control signal.Conclusion. The study proposes the algorithm for compensation of the control signal oscillations by means of correction of the reference level of the digital automatic gain control. Further is required to verify the proposed algorithm on real signals. The results of the study are relevant in development of digital receivers for communication systems of various purposes.

Knowledge is one of the most precious resources of an organization. Every organization wishes to preserve and fully utilize its knowledge. Within organization knowledge is present in various forms, may be in the minds of workers or in documented form. In documented form the knowledge has various representation schemes such as frames, scripts, lists, decision trees and decision tables etc. We have proposed a transformation method to optimally transform knowledge present in decision trees and decision tables into knowledge base. According to our proposal, the knowledge present in these two representation schemes should first be converted into corresponding set of human interpretable rules by using some existing transformation algorithms. The decision tree should be converted directly into set of human interpretable rules but for decision table transformation, two ways are adopted; either it should be converted first into decision tree and then to set of rules or, should be converted directly into set of rules. Once the set of rules is obtained then it will be optimized by using some existing optimization algorithms and unnecessary conditions will be omitted. After rules optimization process, comparison with the existing rules in the knowledge base is carried out. If these optimized rules are not found in the knowledge base, it should be added. If some rules need updation, then these should be added after updation. During comparison those rules which already exist in the knowledge base should be omitted.

This paper is concerned with the development of fully Autonomous Underwater Vehicles (AUVs) for deep ocean scientific and commercial applications. Specifically, it is regarding the design of automatic feedback control systems for AUV attitude control. The design method used in this paper formulates the AUV attitude control problem within the framework of the Optimal Control Theory. This approach determines an optimal control law that keeps the state of a dynamic system near a constant reference state while minimizing a quadratic cost functional. This study has developed four optimal control laws based on different performance criteria. First, the standard Linear Quadratic performance index was used to obtain a baseline control design. The LQR control law has been found to be undesirable because it resulted in a closed-loop system with fast and slow dynamics. In order to place the closed-loop eigenvalues close to each other, a pole placement algorithm has been used in connection with the LQR performance index. Two control laws have been designed based on this approach. Finally, a fourth design has been obtained by using a Hilbert Space Norm (also known as H/sub 2/ Norm or Root-Mean-Square) performance index. The main reason for designing a control law based on H/sub 2/ Norm performance index was to minimize the fuel consumption of the AUV for longer endurance. The stability and performance characteristics of the four optimal control laws have been analyzed via computer simulation and frequency response studies. All the closed-loop AUV systems exhibited overdamped response without any overshoot. Because the yaw and pitch channels have right hand zeros indicating the controllers have finite gain margins in these two channels. Hence, stability robustness of the AUV controllers can not be ignored and must be the subject of more detailed investigation in the future.

Nowadays Unmanned Aircraft Vehicle (UAV) technology has been developed rapidly, including in Indonesia. LAPAN Surveillance UAV (LSU)-02 is one of the fixed-wing UAVs in Indonesia. It has been developed by LAPAN, the national aerospace research agency of Indonesia, for mapping and surveillance. The UAV has been equipped with automatic flight control system. However, the automatic system was not made based on the flight dynamic characteristic of the UAV. Therefore, optimization in certain flight condition becomes difficult. Hence, the aim of this research is to develop a mathematical model of LSU-02 for automatic control and guidance system design. A 6-DOF (degree of freedom) non-linear mathematical model was build based on aerodynamics, weight and balance, and propulsion of the UAV. The model is then evaluated by performing numerical simulation on the designed cruise condition. The simulation results show a dynamically stable characteristics for longitudinal motion and an unstable characteristic for lateral-directional motion.

In this paper, a method for the automatic design of Fuzzy Control Systems is introduced. The method is based on the identification of the inverse model of the process to be controlled by using a Neural Network. The Neural Network which models the inverse process, is used again to obtain a set of tuples representing the fuzzy variables of the fuzzy controller. In order to obtain the fuzzy linguistic variables involved in the fuzzy controller, a Neural Network is used with the DCL algorithm. Finally, the fuzzy controller is implemented by a decision table. The method has been applied to the automatic development of a fuzzy controller for a highly non linear process.

The purpose of this study is to develop a new conceptual approach to the modernization of existing industrial operated automated process control systems (IOAP CS) in order to integrate them into the technology of building digital twins and digital factories with minimal expenditure of computing resources and reducing the amount of processed data. To solve this problem, it is proposed to modify existing automated process control systems (IOAP CS) sequentially by automation levels so that the volume of redundant information is reduced in the structures of the levels, as well as predicting the values of technological parameters based on the properties of control objects using artificial intelligence in order to use identical values in automated process control systems (IOAP CS) and in their models of digital twins. To obtain information about technological processes with a low degree of automation, it is proposed to use organizational and technical structures based on the theory of graphs with a finite vertex, reflecting the volume and quality of the products obtained using algorithms based on artificial intelligence tools, which make it possible to predict the result of subsequent ones based on the results of the previous stage, taking into account the accumulated experience, this will enable an expert assessment of the correctness of the technological process to achieve the required product properties and performance of the technological unit. The proposed concept of modification of automated control systems (IOAP CS) for technological processes in operation will make it possible to ensure the transition to building digital counterparts of technological processes with minimal time using available computing resources with minimal loss of the volume of products.

The article presents the results of the analysis of business processes of pasta production. According to the concept of lean production, types of losses during the production of pasta products were identified. Among the causes of losses are a high proportion of unregulated interruptions, cases of incomplete production in a shift, the presence of downtime due to technological equipment failures, and the laboriousness of manual operations. Taking into account the high importance of optimization of production business processes, emphasis is placed on the expediency of using lean production tools to eliminate losses. The standard SCADA system ‒ TRACE MODE with pre-developed functional schemes for processing grain into flour in the cross-platform Ramus system using CASE technologies was used to develop an automatic process control system. The description of the developed automatic control system for the technological process of flour disinfection using the energy of ultra-high frequency electromagnetic radiation is given. The proposed automatic technological process control system using a disinfectant will speed up and, accordingly, reduce the cost of production. a promising method of drying is proposed - with an infrared energy supply, which ensures obtaining a final product with high quality characteristics, reducing energy consumption and shortening the duration of the drying process. The use of silent heating elements will reduce the noise level at the enterprise; Modernization of technological equipment made it possible to ensure: the possibility of producing pasta products of higher quality; compaction of the structure of the semi-finished product and reduction of its fragility, while simultaneously increasing the strength limit of finished products by 20-25%; improvement of consumer properties, as well as sanitary and hygienic indicators of pasta products due to its pasteurization; decrease in moisture absorption and loss of nutritional value during storage.