Intelligent switching system methodology and its application in complex process control system

We study the issue of robustness of supervisors for discrete event systems. The control objective is to synthesize a supervisor such that the closed-loop behavior lies within a prespecified range whose lower and upper bounds are given as prefix-closed languages. In general, there exists more than one supervisor which satisfies the specification for the nominal plant. We first synthesize the most robust supervisor which maximizes the set of plants for which the specification is satisfied under the supervision. However, the most robust supervisor may be restrictive for the nominal plant, and one may want a more permissive supervisor for the nominal plant at the price of robustness. We characterize the performance of a supervisor in terms of permissiveness for the nominal plant and robustness. We then present techniques to improve each of these two performance measures for a given supervisor.

Aiming at the longitudinal temperature was affected by many reasons, and the control principle of combining the intermittent heating control with the heating gas flow adjustment was adopted.Control strategy and an integrated model of coke oven heating based on hybrid intelligent control methods were built.According to artificial operation and actual condition, fuzzy controller was designed.Intelligent control methods were used to compute the proper amount of stopping heating time and heating gas flow.The application of the system has resulted in energy saving by 2~4%, coke quality improvement by 3~5% and enhanced coke oven life.Obvious economic and social benefinits are obtained.

The article discusses a mathematical model of a control system for exoskeleton electric drives with nonlinear elements. The development of a exoskeleton dynamic model includes five links with two legs and a body, taking into account non-linear electric drives as a control object. Modeling mechanical systems is an important step in the practical design and application of control systems. The nonlinear approach to modeling is due to the use of a control system for the exoskeleton electric drives in various conditions, which is a multi-mass rotating in two directions with nonlinearities of the viscous and Coulomb friction, elasticity. A method of subordinate control (SC) of exoskeleton nonlinear electric drives for tracking control of the exoskeleton joints trajectory is presented. Also, the results of the experiment on the Matlab / Simulink program were obtained to illustrate the effectiveness of the proposed control strategy.

Control of turbocharged diesel engines is a challenging task due to system nonlinearities and constraints on the inputs and process variables. In this paper nonlinear model predictive control is applied to control a diesel engine with a variable geometry turbocharger and an exhaust gas recirculation valve. The overall control objective is to regulate the setpoints of the air-fuel ratio and the amount of recirculated exhaust gas in order to obtain low exhaust emission values and low fuel consumption without smoke generation. Simulation results are presented to study the advantages and disadvantages of nonlinear model predictive control. The achieved performance is compared in simulations with a linear state feedback controller and an input-output linearization based control method. As shown, nonlinear model predictive control achieves good overall control performance and constraint satisfaction.

摘要: 工业过程运行的优化控制的目标是将反应产品在加工过程中的质量、效率、消耗的工艺指标控制在目标值范围内. 由于复杂工业过程的工艺指标难于在线测量且与控制回路输出之间的动态特性具有强非线性、强耦合、难以用精确模型描述、随生产边界条件变化而变化的综合复杂性,因此, 难以采用已有优化控制方法, 运行控制只能采用人工设定的控制方式. 由于人工控制不能及时准确地随运行工况调整设定值, 难以将工艺指标控制在目标值范围内, 甚至造成故障工况.本文提出了根据运行工况实时调整控制回路设定值, 通过控制系统跟踪调整后的设定值, 将工艺指标控制在目标值范围内的过程优化运行的混合智能控制方法. 该方法由控制回路预设定模型、前馈补偿与反馈补偿器、工艺指标预报模型、故障工况诊断和容错控制器组成. 在某选矿厂22台竖炉组成的焙烧过程的应用案例, 证明了所提出方法的有效性. 关键词: 复杂工业过程 / 过程运行 / 工艺指标 / 智能优化控制

The presented article discusses the problems of quality control of construction materials. As we know, the quality of construction materials is one of the most pressing issues at the moment. Quality control means checking whether the quality indicators of goods meet the requirements of the adopted technical normative documents (standards, specifications, etc.). Quality control – set of quality indicators of the material is to check compliance with the requirements. This article also studies analysis of recent research and publications, the effectiveness of quality control methods and structure of functional diagnostics of quality control system. One of the most important areas of quality control is the diagnosis of control problems. Diagnostics – the identification and study of features that characterize the condition of building, structures of buildings and structures in order to identify possible deviations and prevent violations of the normal mode of operation. There are two main types of diagnostics, functional and systematic diagnostics. The main directions of functional diagnostic are described in tabular form. The structure of concrete is also considered here. Execution of concrete structures is a complex process that includes various activities. The basic principle of the development and the application of quality control system during the execution of concrete structures is the process approach. Defining the processes, identification and interaction of sub-processes are performed with the objective of quality monitoring and control that are required in order to achieve concrete structures’ specifications. Quality control system in the area of execution of concrete structures must also comply with national acts, rules, regulations and standards that are essential for concrete structures design, execution and concrete production. The analysis of specific compositions is presented in terms of diagnosing that structure

In the current era of globalization, in the business world, it requires an important aspect to advance a company, one of which is human resources. To get competent and qualified human resources, companies need to ensure the welfare of workers by giving them rights, namely salaries, as reciprocity for the services they have given to the company. In each activity has control over activities that are being and have been carried out. Likewise with the employee payroll system and procedures within the company. The application of an internal control system in the company is very necessary. This research was conducted to find out whether the internal control system in the payroll system and procedures in the company has been running effectively. The object examined is PT Central Mitra Semesta Lamongan which is engaged in replanting services. The method used is descriptive qualitative. Research results show that the payroll system and procedures of PT Central Mitra Semesta Lamongan in fulfilling the elements and objectives of internal control over the payroll system have not been effective, this is characterized by a lack of functions in the organizational structure within the company resulting in a doubling of duties in procedures for making payroll salary payment procedure. less effective recording of employee attendance time so that fraud occurs when calculating working hours and work hours. Keywords: Salaries, systems and procedures, internal control systems

The aim of the work was to study applications of intelligent control systems in improving the fatigue life of structures in mechatronic machines. The study of intelligent control systems was mainly focused on possibilities of neural networks and fuzzy systems. As a result a control algorithm that increases the fatigue life was developed. The control algorithm was designed to be a part of the control system of a log crane. Design process begins with simulation models of the crane and the control algorithm. More tests were done with the physical prototype of the crane. As a result, the fatigue life of the crane was increased such that it will be many times longer than with the traditional control system. Furthermore, developed control algorithm damps substantially the vibrations of the log crane.

In order to solve the problems such as long time-delay, non-linear and the difficulty to establish an accurate mathematical model emerged in industrial field, we combine advanced intelligent control method with traditional automated devices, and put forward a Fuzzy Controller in accordance with the principle of fuzzy control and the characteristics of PLC. The Fuzzy Controller realized on the basis of Siemens S7-300 PLC and programmed in ladder diagram. And had an application in the sewage disposal electric control system of HuLunbeier DongNeng Chemical Plant. On-site debugging also proved that the fine efficiency, reliability and intelligentization of this fuzzy system are superior than traditional PLC automatic control system, which has broad application prospects.

In the control system application, the existence of noise measurement may impact on the performance degradation. The noise measurement of the sensor is produced due to several reasons, such as the low specification, external signal disturbances, and the complexity of measured state. Therefore, it should be avoided to achieve the good control performance. One of the solutions is by designing a signal filter. In this paper, the design of Kalman Filter (KF) algorithm for ultrasonic range sensor is presented. KF algorithm is designed to overcome the existence of noise measurement on the sensor. The type of ultrasonic range sensor used is HC-SR04 which is capable to detect the distance from 2 cm to 400 cm. The discrete KF algorithm is implemented using ATMega 328p microcontroller on Arduino Uno board. The algorithm is then tested with different three covariance values of process noise. The test result shows that the KF algorithm is able to reduce the measurement noise of the ultrasonic sensor. The analysis of variance conducted shows that the smaller value of covariance matrix of the process and measured noises, the better filtering process performed. However, this results in a longer generated response time. Thus, an optimization is required to obtain the best filtering performance.

In this paper, we present the integration of controller synthesis techniques in the environment through the description of a tool dedicated to the incremental construction of reactive controllers. The plant is specified in Signal and the control synthesis is performed on a logical abstraction of this program, named polynomial dynamical system (PDS) over \{-1,0,+1\}. The control of the plant is performed by restricting the controllable input values with respect to the control objectives. These restrictions are obtained by incorporating new algebraic equations into the initial system. This theory sets the basis for the verification and the controller synthesis tool, Signal. Moreover, we present a tool developed around the Signal environment allowing the visualization of the synthesized controller by an interactive simulation of the controlled system. In a first stage, the user specifies in Signal both the physical model and the control objectives to be ensured. A second stage is performed by the Signal compiler which translates the initial Signal program into a PDS, and the control objectives in terms of polynomial relations/operations. The controller is then synthesized using Signal. The result is a controller coded by a polynomial and then by a Ternary Decision Diagram (TDD). Finally, in a third stage, the obtained controller and some simulation processes are automatically included in the initial Signal program. It is then sufficient for the user to compile the resulting Signal program which generates executable code ready for simulation. Different academic examples are used to illustrate the application of the tool.

This paper describes a hierarchical intelligent integrated control system with three layers: a decision layer, a temperature optimisation and control layer, and a process control layer. An information fusion method is used in the decision layer to determine the operating state of the combustion process in real time. The control strategy includes the temperature optimisation control and process control. The parameters of fuzzy controllers are tuned by a multiple-objective optimisation method with an adaptive genetic algorithm to keep the temperature in the proper range. An intelligent method that combines fuzzy and expert control keeps the gas flow rate and air suction power at the settings.

Control of electric drive powertrain based on variable speed control in construction machinery

Considerable achievements in developing structural regulators as an important method for vibration control have been made over the last few decades. The use of large quantities of cables in traditional wired control systems to connect sensors, controllers, and actuators makes the structural regulators complicated and expensive. A wireless decentralized control experimental platform based on Wi-Fi unit is designed and implemented in this study. Centralized and decentralized control strategies as sample controllers are employed in this control system. An optimal control algorithm based on Kalman estimator is embedded in the dSPACE controller and the DSP controller. To examine the performance of this control scheme, a three-story steel structure is developed with active mass dampers installed on each floor as the wireless communication platform. Experimental results show that the wireless decentralized control exhibits good control performance and has various potential applications in industrial control systems. The proposed experimental system may become a benchmark platform for the validation of the corresponding wireless control algorithm.

The present study explores contemporary approaches to the analysis, modelling and assurance of cyber security of critical information infrastructure in the face of modern threats. This text focuses on the utilisation of intelligent methods and advanced technologies for the protection of critical information infrastructure (CII). The objective of the present study is to employ an integrative approach to analysing, modelling, and ensuring the cyber security of CII in the face of contemporary threats. The methodological foundation of the study is a comprehensive analysis of scientific literature dedicated to the application of intelligent methods and technologies for the protection of CII. This includes both fundamental theoretical developments and practical aspects of implementing modern cyber security approaches, as well as experimental modelling of fraud detection processes in the CII of the financial sector. This modelling was conducted by the authors using artificial intelligence (AI) methods. A comparative analysis of concepts proposed by modern researchers is given particular emphasis, with the objective of identifying the main trends, development prospects, and potential areas for improving existing CII protection systems. In relation to the outcomes of the extension of scientific sources, it was determined that intelligent methodologies founded on machine learning and AI represent pivotal technologies for the effective safeguarding of critical infrastructure within the financial sector against contemporary cyberattacks and security threats. The results of the modelling of fraud detection processes in the CII of the financial sector of the economy allow an assessment of the effectiveness of the methods used, determination of their advantages and limitations, and formulation of recommendations for further improvement of cyber protection systems for the CII of the financial sector of the economy. The employment of an integrative approach, encompassing threat analysis, simulation modelling, artificial intelligence, and contemporary cyber defence technologies, facilitates the enhancement of the security of critical infrastructure and the effective response to emergent threats. The proposed solutions have the potential to facilitate the development of highly effective cyber defence systems in various critical infrastructure industries, including the financial, energy, and government sectors.