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Model Predictive control for systems with Limited State Variables

Russian Electrical Engineering 2023年第2期94卷 77-83页

作者： Bogdanov, A.N. Anuchin, A.S. Demidova, G.L. Department of Electric Drive Moscow Power Engineering Institute Moscow111250 Russia Faculty of Control System and Robotics ITMO University St. Petersburg197101 Russia

Abstract: Model predictive control are actively used in industry in high-power electric drives, in which it is permissible to use expensive programmable logic matrices that provide calculations with a prediction horizon of up to ten epochs and a forecast tree of several million variants. However, the computing power of microcontrollers is not enough to implement such systems in a low-power electric drive. The development of microcontrollers is following the path of increasing not only computing power, but also memory, which makes it possible to implement model predictive control systems in practice using lookup table methods for calculating control actions for all combinations of state variables and control actions. The paper shows the possibility of designing control with prediction for two types of electric drives—a DC electric drive and a switched reluctance electric drive—as objects with a small number of state variables, which allows one to fit the precalculated lookup tables of control actions in the memory of the microcontroller. Studies on mathematical models have shown that model predictive control with a finite control set and a single prediction horizon has disadvantages due to variable switching frequency, and control with a continuous control set implemented by the lookup table method allows one to perform control calculations immediately before the start of the next pulse width modulation period, reducing the algorithm execution time by hundreds of times. © 2023, Allerton Press, Inc.

关键词： Forecasting

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Application of Machine Learning Tools in Computer-Aided Design of Technological Processes (CAPP)

Application of Machine Learning Tools in Computer-Aided Desi...

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Neural Networks and Neurotechnologies (NeuroNT), II International Conference on

作者： Aleksandr A. Laptev Sergey D. Tretyakov Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia

ISBN: (数字)9798350363739

ISBN: (纸本)9798350363746

In this work, various methods of designing technological processes are highlighted, their comparative analysis is conducted and general stages are highlighted. Special attention was paid to the analysis of solutions in the information retrieval subsystem, where the search of parts-analogues in the existing systems of automated design of technological processes (CAD TP) is realized. On the basis of the conducted analysis, a new approach to the search for parts-analogues and unification of details with the use of tools and algorithms of machine learning has been proposed. The use of a new database format in CAD TP is also proposed, which allows to significantly simplify the process of search and unification of details. And also to improve the efficiency of the search by reducing the time and qualitative results. The obtained results and proposals can become the basis for improving the process design procedure in industry and increasing the efficiency of the use of computer-aided process design systems.

关键词： Process design Machine learning algorithms Databases Machine learning Manuals Proposals Task analysis

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Bond-Graph Simulation Toolbox

Bond-Graph Simulation Toolbox

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International Russian Automation Conference (RusAutoCon)

作者： Islam Bzhikhatlov Daniil Kotov Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

In the modeling of such dynamic systems as robots, the energy flow across multiple physical domains is challenging and frequently leads to difficulties, making model-based control methods less efficient. This software enables the efficient creation of multi-domain models in terms of bond graph methodology, allowing users to instantiate elements, ports, and bonds and seamlessly interconnect them. the internal algorithms automate the derivation of equations for each system component with respect to energy variables. the software supports the formulation of system equations in both Cauchy and state-space forms. by specifying system parameters and input signals, software performs numerical simulation, providing comprehensive insights into system dynamics. the powerful tool for multi-domain tools could help in the design and co-design of new multi-domain systems as well as in the synthesis of control algorithms in the energy domain for a wide range of applications.

关键词： Automation System dynamics Heuristic algorithms Software algorithms Numerical simulation Mathematical models Software Dynamical systems Robots

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Signal Adaptive Filtering Algorithm to Eliminate White Noise of Stationary and Non-Stationary Signals

Signal Adaptive Filtering Algorithm to Eliminate White Noise...

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International Russian Automation Conference (RusAutoCon)

作者： Kirill A. Shabanov Sergey M. Vlasov Control Systems and Robotics Faculty ITMO University Saint-Petersburg Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

This article aims to research and evaluate existing adaptive signal filtering algorithms. Filtering of signals removes noise and distortion, which is a crucial scientific and technical challenge. the authors specifically consider the problem of white noise filtering using an adaptive filter approach. To address this problem, classical adaptive filtering algorithms are selected as the primary techniques for investigation. the efficiency of the least mean squares and recursive least squares with forgetting factor algorithms is compared in white noise filtering tasks for stationary and non-stationary signals. As a result, the authors have successfully filtered multi-harmonic signals from white noise using both the least mean squares and recursive least squares with forgetting factor algorithms.

关键词： Automation Filtering Simulation Adaptive filters Interference Filtering algorithms White noise Distortion

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The Effect of Changing-Lane Prediction Algorithms on the Performance of ACC System Model in Matlab/Simulink

The Effect of Changing-Lane Prediction Algorithms on the Per...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Leila Suleiman Sergei Vlasov Control Systems and Robotics Faculty ITMO University Saint-Petersburg Russia

Self-driving vehicles are capturing the attention of numerous researchers, companies, and car enthusiasts. The automation of vehicles varies across multiple levels, depending on the tasks they perform and the techniques they employ. The Adaptive Cruise control (ACC) system is an automated vehicle at the first level. It checks the presence of other vehicles in its lane to adapt its velocity accordingly or maintain a constant speed. However, it does not include lane-changing capabilities. Nevertheless, the presence of other neighboring vehicles can affect the performance of the ACC based Model Predictive controller (MPC) system, leading to discomfort or collisions. In this paper, we will provide a brief description of the ACC system and the MPC controller. Subsequently, we will discuss the challenges that affect the performance of the ACC based MPC system and propose potential solutions using the Variable Time Headway (VTH) strategy or changing-lane prediction algorithms, such as Random Forest (RF), K- Nearest Neighbor (KNN) and Support Vector Machine (SVM). Simulation results of applying these methods to a sufficiently dangerous driving scenario will be illustrated, followed by a brief conclusion.

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Preprocessing Digital Images for Enhanced Detection and Classification of Surface Defects in Cold-Rolled Sheet Metal

Preprocessing Digital Images for Enhanced Detection and Clas...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Oleg Evstafev Sergei Shavetov Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russia

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The article addresses the application of Deep Learning (DL) methods and Computer Vision (CV) for the recognition and classification of surface defects in sheet metal. A specialized image preprocessing method has been developed, based on calculating statistical characteristics and subtracting them from averaged values. This method enhances defect detection, especially on low-contrast images, without requiring significant computational resources. The preprocessing algorithm includes considerations for image merging, the use of sliding windows with filters of various sizes, and image segmentation for input into the neural network. A defect detection model based on the Faster R-CNN Convolutional Neural Network (CNN) ensures high sensitivity in Automated Optical Inspection systems (AOIS), detecting defects as small as 0.5×0.5 mm in real-time.

关键词： Optical filters Sensitivity Metals Lighting Optical imaging Real-time systems Classification algorithms Optical sensors Convolutional neural networks Defect detection

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A New Modular Adaptive Backstepping control of Nonlinear systems with Unknown control Coefficients*

A New Modular Adaptive Backstepping Control of Nonlinear Sys...

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IEEE Conference on Decision and control

作者： Dmitry Gerasimov Artem Pashenko Oleg Suzdalev Vladimir O. Nikiforov Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russia

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The paper addresses the problem of design of a modular adaptive backstepping controller for a class of nonlinear strict-feedback systems with unknown virtual and actual control gains. By involving the high-order time derivatives (HOTD) of the adjustable parameters into the virtual and actual control laws, the backstepping procedure is reduced to a relatively simple static error model. This model is used for design of the recently proposed adaptation algorithm with memory regressor extension which ensures two key properties. First, it is used for calculation of the HOTD of the adjustable controller parameters. Second, the algorithm provides a systematic technique for accelerating the controller parameters and, as a result, improves the transient performance of the closed-loop system.

关键词： Adaptation models Backstepping Adaptive systems Systematics Closed loop systems Transient analysis Nonlinear systems

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Automation of Ultrasonic Testing Technology for Soldered Joints of Heat Exchanger Elements

Automation of Ultrasonic Testing Technology for Soldered Joi...

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Intelligent Technologies and Electronic Devices in Vehicle and Road Transport Complex (TIRVED)

作者： Valeriy V. Malyy Igor Y. Kinzhagulov Vladimir E. Prokhorovich Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia

ISBN: (数字)9798331518707

ISBN: (纸本)9798331518714

This article discusses the automation of ultrasonic echo-pulse method technology for testing soldered joints of heat exchanger elements. The article describes a test object with a complex geometric shape and defects in soldered joints that occur during manufacturing, such as "non-soldering" and "partial non-soldering". The article describes the problems of existing solutions for quality control of soldered joints, which consist in the complexity of positioning the piezoelectric transducer, which leads to insufficient efficiency and reliability of the testing results, which justifies the relevance of the work. Finite element modeling was carried out to establish the dependencies of geometric displacements during positioning of the piezoelectric transducer, based on the results of which an algorithm was developed that allows increasing the efficiency and reliability of the testing results. An experimental testing of the created automated ultrasonic testing system was carried out, which confirmed that the proposed method for automating the technology of ultrasonic testing of soldered joints of heat exchanger elements is more efficient and reliable compared to existing solutions.

关键词： Heating systems Automation Shape Roads Piezoelectric transducers Quality control Acoustics Finite element analysis Reliability Testing

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Direct Adaptive control of LTV Discrete-time systems with Uncertain Periodic Coefficients*

Direct Adaptive Control of LTV Discrete-time Systems with Un...

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IEEE Conference on Decision and control

作者： Dmitry N. Gerasimov Dang Hien Ngo Vladimir O. Nikiforov Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russia

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The paper considers the problem of the state-feedback adaptive control of a class of discrete linear time-varying plant with multisinusoidal parameters. The plant is representable in the strict-feedback form, in which the parameters are on the main diagonal of the state matrix. The amplitudes, frequencies, and the phases of the multisinusoids are not known a priori, however the maximum numbers of sinusoids (harmonics) in each parameter are available. The problem is solved by design of periodic parameters observers recovering the parameters dynamics, the plant parameterization, and developing a discrete-time adaptive backstepping controller. In order to tune the controller parameters and improve the closed-loop transient performance, an adaptation algorithm with memory regressor extension is applied. The main results of the paper are demonstrated by simulation.

关键词： Discrete-time systems Backstepping Heuristic algorithms Observers Harmonic analysis Adaptive control Transient analysis

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A New Approach for Technological Processes Design Using Machine Learning Algorithms

A New Approach for Technological Processes Design Using Mach...

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International Russian Automation Conference (RusAutoCon)

作者： Aleksandr Laptev Sergey Tretyakov Yuri Andreev Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

In recent years, there has been an active introduction of digital and automated technologies in Russian mechanical engineering and instrumentation industries. Such systems are CAD, CAPP, MES systems, which allow to automate many processes in production. This study is devoted to CAPP (computer-aided process design systems), paying special attention to the methods used for the design of technological processes. The study showed that the search systems of existing CAPP are all based on manual entry of attributes and subsequent time-consuming analysis of search results, technological processes are dialogue mode. And one of the main factors determining the efficiency and competitiveness of the enterprise is a timely developed and established technological process. In order to increase the efficiency of the technological preparation stage of production, it is proposed a new method for designing technological processes in CAPP through the use of machine learning. Thus, the study made possible the development of a new automated process search system for analogue detail. Also the carried out study provides the algorithm, describing a new process engineering method with machine learning tools.

关键词： Process design Industries Machine learning algorithms Automation Instruments Production Machine learning Manuals Mechanical engineering

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