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Analysis of Anti-surge control Method for Axial Flow Compressor

外文科技期刊数据库(文摘版)工程技术 2021年第6期 417-418页

作者： CHEN Hongxin CHEN Sishi Shenyang Blower Group Automatic Control System Engineering Co. Ltd. Shenyang 110000 China

With the continuous development of society, axial compressor has been more and more widely used in modern industry. The surge motion of axial compressor has gradually attracted people's attention. It is necessary to actively explore the anti surge control method of axial compressor. In this paper, the surge control method of fully static regulating axial compressor is analyzed, and the surge control of axial compressor is realized by using programmable controller, which solves the shortcomings of existing control methods, improves the operation condition and improves the efficiency of axial compressor.

关键词： axial flow compressor anti-surge control method implementation

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Expert system for the Water system Diagnostics 23

Expert System for the Water System Diagnostics

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23rd International Conference on control systems and Computer Science Technologies, CSCS 2021

作者： Nitu, Costica Krapivin, Vladimir F. Mkrtchyan, Ferdenant A. Dobrescu, Anda Sabena University Politehnica of Bucharest Department of Automatic Control and System Engineering Bucharest Romania Kotelnikov's Institute of Radioengineering and Electronics Russian Academy of Sciences Fryazino Branch Fryazino Russia University Politehnica of Bucharest Bucharest Romania

New information - modeling instrumental approach is proposed to realize the diagnostics of hydrological and hydrochemical systems and processes. Decision making procedure is based on the big data processing algorithms... 详细信息

ISBN: (纸本)9781665439398

关键词： Decision making

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Process Optimization of Black Soldier Fly Egg Production via Model Based control

arXiv

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arXiv 2022年

作者： Kobelski, Alexander Hempel, Arne-Jens Padmanabha, Murali Wille, Luiz-Carlos Streif, Stefan Faculty of Electrical Engineering and Information Technology Automatic Control and System Dynamics Technische Universitaet Chemnitz Chemnitz09111 Germany The Department of Digital Engineering Staatliche Studienakademie Glauchau Glauchau08371 Germany

Black soldier fly (BSF) larvae (Hermetia illucens) are a valuable protein source for manufacturing animal feed. To maximize their production, both the quantity and quality of their reproductive cycle, i.e. egg production during oviposition, must be increased. In artificial environments, flies often sit idle in cages without mating, depleting their energy reserves and resulting in lower egg production per female. By controlling environmental conditions such as temperature and light inside breeding cages, the flies may be stimulated in a way that improves egg output. However, this stimulation increases the energy demand of the process and may stress the flies, resulting in reduced egg production. Therefore, control must be applied in a careful way, which requires knowledge of the egg production cycle. In this work, a mathematical model describing the various fly life stages and their transition to the egg production process is developed. Relevant factors are identified and their effect on the fly life and egg production is mathematically described. Parameters are identified using data from literature and goodness of fit is evaluated. Using the model, an optimal control problem is formulated with the goal of minimizing the energy costs and increasing the egg production quantity. In Simulation, our approach showed 13% higher output in shorter time at reduced energy costs compared to a (standard) constant setpoint approach. Optimal control could reach same amount of egg in 60 % of time compared to standard scenario. © 2022, CC BY-NC-ND.

关键词： Optimal control systems

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On the Gaussian Filtering for Nonlinear Dynamic systems Using Variational Inference

On the Gaussian Filtering for Nonlinear Dynamic Systems Usin...

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International Conference on Information Fusion

作者： Yi Liu Xi Li Le Yang Lyudmila Mihaylova Ji Li Department of Electrical and Computer Engineering University of Canterbury Christchurch NZ State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems National University of Defense Technology Changsha China Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Locaris Electronic Technology Co. Ltd Zhengzhou China

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

This paper introduces a new variational Gaussian filtering approach for estimating the state of a nonlinear dynamic system. We first assume that the predictive distribution of the state is Gaussian and derive an iterative method for updating the state posterior in the natural parameter space through KullbackLeibler divergence minimization. The obtained update rule is the same as that of the conjugate-computation variational inference technique in Bayesian learning. The derivation here is simpler and more insightful. We then impose a Wishart prior on the inverse of the state prediction covariance to take into account the impact of approximating the state predictive distribution using a Gaussian density on the state posterior estimation. The prediction covariance is identified jointly with the state using variational inference and the established state posterior update rule to achieve the desired Gaussian filtering. Simulation study examines the performance of the proposed filtering framework in target tracking based on bearing and range measurements.

关键词： Target tracking Smoothing methods Filtering Estimation Filtering algorithms Prediction algorithms Minimization Nonlinear dynamical systems Bayes methods Iterative methods

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Notch filter on differential difference operational amplifier 3

Notch filter on differential difference operational amplifie...

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3rf International Scientific Conference on Metrological Support of InnovativeTechnologies, ICMSIT 2022

作者： Yu Denisenko, D. Prokopenko, N.N. Ivanov, Yu I. Butyrlagin, N.V. Information System and Radio Engineering Department Don State Technical University Gagarin Sq. 1 Rostov-on-Don344000 Russia Department of Automatic Control Systems Southern Federal University Bolshaya Sadovaya St. 33 Rostov-on-Don344000 Russia Department of Information System and Radio Engineering Don State Technical University Gagarin Sq. 1 Rostov-on-Don344000 Russia Institute for Design Problems in Microelectronics of Russian Academy of Sciences IPPM RAS Zelenograd124681 Russia

A new notch filter (NF) circuit based on a single differential difference operational amplifier (DDA) has been developed and studied, which is characterized by reduced current consumption in the static mode. Equations are obtained for the transfer functions and parameters of the NF, which includes a low-pass filter and a Sallen-Key high-pass filter, the signals of which are summed by the DDA. Computer modeling of the NF in CAD Micro-Cap was performed. © Published under licence by IOP Publishing Ltd.

关键词： Operational amplifiers

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Active Sallen-Key RC-High-Frequency filter based on non-inverting voltage followers 3

Active Sallen-Key RC-High-Frequency filter based on non-inve...

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3rf International Scientific Conference on Metrological Support of InnovativeTechnologies, ICMSIT 2022

作者： Yu Denisenko, D. Prokopenko, N.N. Ivanov, Yu I. Butyrlagin, N.V. Information System and Radio Engineering Department Don State Technical University Gagarin Sq. 1 Rostov-on-Don344000 Russia Department of Automatic Control Systems Southern Federal University Bolshaya Sadovaya St. 33 Rostov-on-Don344000 Russia Head of Information System and Radio Engineering Department Don State Technical University Gagarin Sq. 1 Rostov-on-Don344000 Russia Institute for Design Problems in Microelectronics of Russian Academy of Sciences IPPM RAS Zelenograd124681 Russia

A new high-pass filter (HPF) circuit of the second-order Sallen-Key family has been developed and studied, in which independent adjustment of the main parameters is realized -the pole frequency, the quality factor of the pole and the transmission coefficient. The basic equations for the transfer functions and HPF parameters are presented. The results of computer simulation a proposed circuits HPF in CAD Micro-Cap 12 are shown. © Published under licence by IOP Publishing Ltd.

关键词： High pass filters

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A stabilizing reinforcement learning approach for sampled systems with partially unknown models

arXiv

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arXiv 2022年

作者： Beckenbach, Lukas Osinenko, Pavel Streif, Stefan The Laboratory for Automatic Control and System Dynamics Technische Universität Chemnitz Chemnitz09107 Germany The Digital Engineering Center Skolkovo Institute of Science and Technology Moscow121205 Russia

Reinforcement learning is commonly associated with training of reward-maximizing (or cost-minimizing) agents, in other words, controllers. It can be applied in model-free or model-based fashion, using a priori or online collected system data to train involved parametric architectures. In general, online reinforcement learning does not guarantee closed loop stability unless special measures are taken, for instance, through learning constraints or tailored training rules. Particularly promising are hybrids of reinforcement learning with "classical" control approaches. In this work, we suggest a method to guarantee practical stability of the system-controller closed loop in a purely online learning setting, i. e., without offline training. Moreover, we assume only partial knowledge of the system model. To achieve the claimed results, we employ techniques of classical adaptive control. The implementation of the overall control scheme is provided explicitly in a digital, sampled setting. That is, the controller receives the state of the system and computes the control action at discrete, specifically, equidistant moments in time. The method is tested in adaptive traction control and cruise control where it proved to significantly reduce the *** Codes 93D15 © 2022, CC BY-NC-ND.

关键词： Reinforcement learning

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Multi-robot Motion Planning under MITL Specifications based on Time Petri Nets

Multi-robot Motion Planning under MITL Specifications based ...

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European control Conference (ECC)

作者： Sofia Hustiu Dimos V. Dimarogonas Cristian Mahulea Marius Kloetzer Dept. of Automatic Control and Applied Informatics Technical University ”Gheorghe Asachi” of Iasi Romania Division of Decision and Control System KTH Royal Institute of Technology Stockholm Sweden Aragón Institute of Engineering Research (I3A) University of Zaragoza Maria de Luna 1 Zaragoza Spain

This paper proposes a high-level path planning strategy under Time Petri net (TPN) formalism for a multiagent system, which is subject to Metric Interval Temporal Logic (MITL) specifications. The work aims to design a scalable model with respect to the number of agents, as the MITL formula requires multiple agents to ensure similar tasks. The obtained model is denoted Composed Time Petri net and it couples two TPN representations assigned to the motion of the agents, respectively to the MITL specification. The planning approach is based on model-checking methods and the results are evaluated on a case study applied in robotics industry.

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High-Speed Trajectory Tracking control for Quadrotors via Deep Reinforcement Learning

High-Speed Trajectory Tracking Control for Quadrotors via De...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Hean Hua Hang Zhong Hui Zhang Yongchun Fang Yaonan Wang College of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control Technology Changsha China School of Robotics Hunan University Changsha China Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This paper presents a learning-based high-speed trajectory tracking control strategy for quadrotors, which achieves efficient learning and strong reliability by the collaboration of deep reinforcement learning (RL) and self-tuning mechanism. Different from existing methods, the proposed strategy is designed to explore optimal control performance by taking advantage of model-based self-tuning mechanism and deep reinforcement learning. Specifically, the self-tuning guided deep RL scheme is put forward for quadrotors, with superior learning efficiency and strong adaptability. Firstly, a novel self-tuning mechanism is constructed and some auxiliary variables are introduced to enhance the tracking performance. Then, based on the model-driven self-tuning design, the deep RL is proposed to achieve model-guided learning, where the tuning actions are adopted in the evaluation process during training, aiming at removing the bad explorations by the carefully designed parallel evaluation. Finally, the convergence is analyzed based on the proposed learning framework, which indicates the efficient cooperation of exploration and self-tuning mechanism. To verify the effectiveness of the proposed controller, the guided training and hardware experiments are implemented to show efficient cooperation and satisfactory high-speed trajectory tracking control of the proposed method.

关键词： Training Adaptation models Trajectory tracking Heuristic algorithms Optimal control Deep reinforcement learning Hardware

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing

On the Approximation of the Quotient of Two Gaussian Densiti...

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International Conference on Information Fusion

作者： Yi Liu Xi Li Le Yang Lyudmila Mihaylova Yanbo Xue Department of Electrical and Computer Engineering University of Canterbury Christchurch NZ State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems National University of Defense Technology Changsha China Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Career Science Lab Beijing China

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target.

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