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Data Driven control and Learning Systems (DDCLS)

作者： MinYin Shen Fei Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

In this paper, by integrating singular perturbation method and off-policy reinforcement learning, a new approach to solving the H∞ tracking control problem is presented for linear time-invariant two time scales systems. A composite control scheme is designed through decomposing the two time scales system into fast and slow subsystems. For the slow subsystem, a model-free H∞ tracking controller is designed based on off-policy reinforcement learning to accomplish system tracking of the desired trajectory while effectively suppressing disturbances, without knowledge of the dynamics. Meanwhile, for the fast subsystem, a model-based offline controller is adopted. To better tracking performance, an exponential discount factor is introduced to weight the cost of input and tracking errors. By analysis and simulation, the effectiveness and superior tracking performance of proposed method has been verified.

关键词： Linear systems Learning systems Costs Perturbation methods Design methodology Reinforcement learning control systems

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Fixed-time Funnel Sliding Mode control for Dual-motor Driving System

Fixed-time Funnel Sliding Mode Control for Dual-motor Drivin...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Jia-Meng Wu Cheng-Lin Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

A fixed-time funnel sliding mode control strategy is developed for a dual-motor driving system, which ensures the system converges within a fixed time. Firstly, the coupling error is introduced by combining the reference tracking process with the motor synchronization process. By using a selected funnel function, the system can achieve satisfactory transient performance. Secondly, the concept of multi-surface sliding modes is designed to deal with the tracking issue so that the system can converge in a fixed-time regardless of the motor’s initial state. Finally, the effectiveness of this strategy is demonstrated through a simulation example.

关键词： Couplings Motors Synchronization Transient analysis Sliding mode control Convergence

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Model-Free $H_{2}/H_{\infty}$ Predictive control for Discrete-Time System via Q-Learning

Model-Free $H_{2}/H_{\infty}$ Predictive Control for Discret...

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Data Driven control and Learning Systems (DDCLS)

作者： Yihong Lin Peng He Haiying Wan Zhuangyu Liu Xiaoli Luan Fei Liu Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

This paper presents a model-free $H_{2}/H_{\infty}$ Q-learning predictive control strategy for linear discrete-time systems. To design predictive controller with the system measured states, a policy iteration solution algorithm is employed to approximate the control inputs. Specifically, the developed algorithm is formulated in the form of linear matrix inequalities, designed to stabilize the system with mixed $H_{2}/H_{\infty}$ control performance. Additionally, to improve robust performance under system disturbance variations, we introduce the receding horizon optimization into the Q-learning based predictive control. Finally, simulation results demonstrate the effectiveness of the proposed approach.

关键词： Discrete-time systems Q-learning Simulation Heuristic algorithms Predictive models Prediction algorithms Approximation algorithms

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Robust Stochastic Configuration Network Based Prediction Model of Total Nitrogen Content in Crude Oil 5

Robust Stochastic Configuration Network Based Prediction Mod...

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5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Lu, Jun Feng, Min Ding, Jinliang Zhang, Xiaoling Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian116024 China

ISBN: (纸本)9798350325294

The refineries usually process the blending crude oil at present. Blending crude oil leads to the increased uncertainties of physical properties of crude oil. This paper presents a robust stochastic configuration network (SCN) based prediction model for total nitrogen content in crude oil. First, the robust SCN based on Bayesian framework is proposed. In the Bayesian framework, the noise and outliers are assumed to be the mixture of two Gaussian distributions to improve the robustness of SCN. Then, to solve the problem that there are no analytical solutions of parameters due to the assumption of mixture of Gaussian distributions, parameters of the proposed robust SCN are estimated by the expectation maximization (EM) algorithm. Experiments using the real-world data collected from a refinery are carried out. The results indicate that the proposed approach has better accuracy and robustness. © 2023 IEEE.

关键词： Crude oil

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Integral Adaptive Sliding Mode control for Vehicle Platoon with Disturbance Observer

Integral Adaptive Sliding Mode Control for Vehicle Platoon w...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Xin Yang Cheng-Lin Liu Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This article proposes an integral adaptive sliding mode control (IASMC) strategy that combines adaptive reaching laws and disturbance observers (DO) for vehicle platoon system subject to unknown disturbance. The objective is to ensure the string stability and make the spacing error between any front and rear vehicles in the platoon be zero, which means that the vehicles are driven at the expected spacing. To achieve it, the bidirectional (BD) topology and the constant time headway (CTH) policy are employed. Then, an adaptive smoothed sliding mode reaching law is constructed to eliminate the chattering issue. The unknown disturbances can be estimated by the designed DO. Meanwhile, the Lyapunov method is applied to the analysis and proof of the stability of the designed IASMC strategy, and the Laplace transform is used in the proof of the string stability. Finally, based on simulation, it can be seen that the availability and superiority of the designed strategy can be verified.

关键词： Adaptive systems Laplace equations Stability analysis Disturbance observers Topology Sliding mode control Lyapunov methods

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Data augmentation method for light guide plate based on improved CycleGAN

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Optoelectronics Letters 2024年

作者： GONG Yefei YAN Chao XIAO Ming LU Mingli GAO Hua School of Electrical and Automation Engineering，Changshu Institute of Technology Jiangsu Engineering Research Center of Industrial Robot Complex Process Intelligent Control School of Electrical Engineering， Yancheng Institute of Technology Wuxi Novo Automation Technology Corp

An improved CycleGAN network method for defect data augmentation based on feature fusion and self attention residual module is proposed to address the insufficiency of defect sample data for light guide plate(LGP) in production， as well as the problem of minor defects. Two optimizations are made to the generator of CycleGAN: 1) Fusion of low resolution features obtained from partial up-sampling and down-sampling with high-resolution features. 2) Combine self attention mechanism with residual network structure to replace the original residual module. Qualitative and quantitative experiments were conducted to compare different data augmentation methods， and the results showed that the defect images of the LGP generated by the improved network were more realistic， and the accuracy of the YOLOv5 detection network for the LGP was improved by 5.6%， proving the effectiveness and accuracy of the proposed method.

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Technological Machines Diagnostics of Grain processing Enterprises as the Object of automation

Technological Machines Diagnostics of Grain Processing Enter...

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Kalandarov, Palvan I. Ubaydullayeva, Shakhnoza R. Nikolov, Nikola N. Hayitov, Aziz Sharifov, Husen 'Tashkent Institute of Irrigation and Agricultural Mechanization Engineers' National Research University Department 'Automation and Control of Technology Process in Production' Tashkent Uzbekistan Technical University of Varna Faculty of Computer Science and Automation Department of Automation Varna Bulgaria Bukhara Institute of Natural Resource Management of the National Research University 'Tashkent Institute of Irrigation and Agricultural Mechanization Institute' Tashkent Uzbekistan

ISBN: (纸本)9798350312911

The article gives the basic concepts of reliability, performance, durability, considers the issues of changing the technical state of the machine during operation. The models under consideration have the ability to introduce various perturbations in order to simulate physical defects, and numerical simulation on a computer made it possible to obtain solutions in the form of temporary realizations of oscillations for different states of the simulation object. The cooperative use of the full-scale method and mathematical modeling made it possible to reduce the volume of full-scale experiments and apply statistical methods of analysis in the problem of classifying the technical condition by constructing mathematical models of the probability of failure and uptime during their operating time. The content of the main types of machine states is revealed, considerable attention is paid to the issues of identifying and influencing failures and the causes of failures in the machine, the reasons for the loss of performance during operation. © 2023 IEEE.

关键词： Deterioration

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Dependability and Security Aspects of Network-Centric control

Dependability and Security Aspects of Network-Centric Contro...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Björn Leander Bjarne Johansson Tomas Lindström Olof Holmgren Thomas Nolte Alessandro V. Papadopoulos ABB Process Automation Process Control Platform Västerås Sweden Mälardalen University Västerås Sweden

Industrial automation and control systems are responsible for running our most important infrastructures, providing electricity and clean water, producing medicine and food, along with many other services and products we take for granted. The safe and secure operation of these systems is therefore of great *** of the emerging trends in industrial automation systems is the transition from static hierarchical controller-centric systems to flexible network-centric systems. This transition has a great impact on the characteristics of industrial automation systems. In this article we describe the network-centric design strategy for industrial automation systems and describe the impact on dependability and security aspects that this strategy brings, looking at both challenges and possibilities.

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Consistency Before Availability: Network Reference Point based Failure Detection for controller Redundancy

Consistency Before Availability: Network Reference Point bas...

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International Conference on Emerging Technologies and Factory automation (ETFA)

作者： Bjarne Johansson Mats Rågberger Alessandro V. Papadopoulos Thomas Nolte ABB Process Automation Process Control Platform Västerås Sweden Mälardalen University Västerås Sweden

Distributed control systems constitute the automation solution backbone in domains where downtime is costly. Redundancy reduces the risk of faults leading to unplanned downtime. The Industry 4.0 appetite to utilize the device-to-cloud continuum increases the interest in network-based hardware-agnostic controller software. Functionality, such as controller redundancy, must adhere to the new ground rules of pure network dependency. In a standby controller redundancy, only one controller is the active primary. When the primary fails, the backup takes over. A typical network-based failure detection uses a cyclic message with a known interval, a.k.a. a heartbeat. Such a failure detection interprets heartbeat absences as a failure of the supervisee; consequently, a network partitioning could be indistinguishable from a node failure. Hence, in a network partitioning situation, a conventional heartbeat-based failure detection causes more than one active controller in the redundancy set, resulting in inconsistent outputs. We present a failure detection algorithm that uses network reference points to prevent network partitioning from leading to dual primary controllers. In other words, a failure detection that prioritizes consistency before availability.

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Identification of Abnormal Operating Conditions in Fused Magnesium Furnaces Using a Deep Multiview TSK Fuzzy System

Identification of Abnormal Operating Conditions in Fused Mag...

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2024 China automation Congress, CAC 2024

作者： Xi, Chao Wu, Gaochang Fan, Zizhu Xu, Feng Wang, Hui Tang, Xiaokun School of Electrical and Automation Engineering East China Jiaotong University Nanchang China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China College of Computer Science and Technology Shanghai University of Electric Power Shanghai China Key Laboratory of Advanced Control and Optimization of Jiangxi Province East China Jiaotong University Nanchang China

ISBN: (纸本)9798350368604

The smelting process of the fused magnesium furnace(FMF) is prone to semi-molten abnormal conditions, which may lead to low product quality and production efficiency, and is also prone to safety accidents. At present, the operating conditions of FMF mainly rely on manual observation of the furnace shell features for diagnosis, and it is hard to timely and effectively identify abnormalities in the smelting process. Given the difficulty in identifying abnormal operating conditions of FMF, this paper proposes a deep multiview fuzzy classification method(DMFC) that can automatically identify abnormal operating conditions. First, based on the three-phase current data, CNN and Transformer are used to extract features as multiple views. Secondly, the Takagi-Sugeno-Kang(TSK) fuzzy model is used as a single-view model, and the evidence theory is used for dynamic fusion of multiple views. This method can effectively fuse multiple deep features, and has strong scalability and a certain degree of interpretability. Through verification of the real historical data of multiple FMFs, our model has relatively high accuracy, false detection rate(FDR), and missed detection rate(MDR). © 2024 IEEE.

关键词： Smelting

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