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1st International Conference on Robotics, Engineering, Science, and technology, RESTCON 2024

作者： Boonthai, Torsak Nunthavarawong, Peerawatt Kowitwarangkul, Pruet Fuchiwaki, Masaki Bangkok Thailand Bangkok Thailand Kyushu Institute of Technology Department of Intelligent and Control Systems Fukuoka Japan

ISBN: (纸本)9798350348842

Mechanical alloying plays a crucial role in controlling and enhancing the characteristics of powder materials which in turn influence the quality and performance of thermal spray coatings. In this study, the optimal milling parameters for mechanical alloying were determined, specifically a rotational speed of 60 rpm, a milling period of 6 hours, and wet milling conditions. These settings led to the best preparation of feedstock powder, resulting in a minimal particle size of 17.5 μm and a narrow particle size dispersion. The observed extensive cataracting and impact zones at this rotational speed of 60 rpm corresponded to 65 of the % critical speed, indicating enhanced milling efficiency. Additionally, DEM modeling demonstrated good agreement with experimental findings, indicating enhanced milling efficiency. Additionally, DEM modeling demonstrated good agreement with experimental findings, highlighting that this rotational speed induced a cataracting regime characterized by a broad zone of impacted particles, yielding the highest impact velocity of 1.79 m/s and a ball indenter force interaction of 1.19 N. © 2024 IEEE.

关键词： Mechanical alloying

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Adaptive event-triggered state estimation for large-scale systems subject to deception attacks

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Science China(Information Sciences) 2022年第2期65卷 139-154页

作者： Hanchen XIAO Derui DING Hongli DONG Guoliang WEI College of Science University of Shanghai for Science and Technology Department of Control Science and Engineering University of Shanghai for Science and Technology School of Software and Electrical Engineering Swinburne University of Technology Institute of Complex Systems and Advanced Control Northeast Petroleum University

This paper addresses state estimation issues of large-scale systems with measurements subject to deception attacks, where the communication topology among sub-estimators is the same as the physical coupling structure of the subsystems. In consideration of the limited channel bandwidth, a novel adaptive event-triggered scheme is proposed for governing the data transmission among sub-estimators. With the help of Lyapunov analysis approaches, sufficient conditions are derived to ensure the input-to-state stability of the dynamics of estimation errors. Meanwhile, the bound of the estimation errors is obtained in the mean-square sense. The desired estimator parameters are presented in an analytical form dependent on the solution of a set of matrix inequalities. The developed scheme is related to the local information of the subsystems and thus satisfies the requirement of scalability. Finally, a simulation example of power systems is given to reveal the usefulness and effectiveness of the developed design scheme.

关键词： large-scale discrete-time systems adaptive event-triggering communication Adaptive event-triggering communication deception attacks input-to-state stability power systems

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Pushing the limit to near real-time indoor LiDAR-based semantic segmentation 8

Pushing the limit to near real-time indoor LiDAR-based seman...

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8th International ISPRS Workshop LowCost 3D - Sensors, Algorithms, Applications

作者： Bournez, Pierrick Salzinger, Jules Cella, Marco Vultaggio, Francesco d'Apolito, Francesco Fanta-Jende, Phillipp AIT Austrian Institute of Technology Center for Vision Automation and Control Unit Assistive and Autonomous Systems Austria

Semantic segmentation of indoor 3D point clouds is a critical technology for understanding three dimensional indoor environments, with significant applications in indoor navigation, positioning, and intelligent robotics. While real-time semantic segmentation is already a reality for images, existing classification pipelines for LiDAR point clouds assume a pre-existing map which relies on data collected from accurate but heavy sensors. However, this approach is impractical for high-level task planning and autonomous exploration, which benefits from a rapid 3D structure understanding of the environment. Furthermore, while RGB cameras remain a popular choice in good visibility conditions, such sensors are inefficient in environments where visibility is hindered. Consequently, LiDAR point clouds emerge as a rather reliable source of environmental information in such circumstances. In this paper, we adapt an existing semantic segmentation model, Superpoint Transformer, to LiDAR-based situation where RGB inputs are not available and near real-time processing is attempted. To this end, we simulated our robot's trajectory and leveraged Hidden Point Removal using the open-source dataset S3DIS to train the model. We investigated various strategies such as modifying the interval prediction and thoroughly study its influence on the prediction intervals. Our model demonstrates an improvement from 40 to 67.6 mean Intersection over Union (mIoU) compared to the baseline on simple (floor, ceiling, walls) and complex (doors, windows) classes. Copyright: © 2024 Pierrick Bournez et al.

关键词： Semantic Segmentation

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Frequency Domain Auto-tuning of Structured LPV controllers for High-Precision Motion control 63

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Broens, Yorick Butler, Hans Toth, Roland Asml Veldhoven Netherlands Eindhoven University of Technology Department of Electrical Engineering Eindhoven Netherlands Hunren Institute for Computer Science and Control Systems and Control Laboratory Hungary

ISBN: (纸本)9798350316339

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype. © 2024 IEEE.

关键词： Continuous time systems

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Deadtime Compensation-Based Approximate Decoupling control Approach for Multivariable Processes

Deadtime Compensation-Based Approximate Decoupling Control A...

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2024 IEEE Region 10 Conference, TENCON 2024

作者： Aldhandi, Suresh Detroja, Ketan P. Indian Institute of Technology The Systems and Control Group Department of Electrical Engineering Telangana Hyderabad502285 India

ISBN: (纸本)9798350350821

The interaction effects among individual loops and multiple time delays are the prime reasons for degrading the closed-loop performance of multivariable systems. For highly interacting systems, decouplers are used to counteract interaction effects. However, decouplers may not be realizable and even if they are realizable, for high dimensional systems, decoupler elements may be complex. To improve the decoupler realizability, a dead-time compensation (DTC) approach is proposed in this work. The DTC framework can minimise the impact of dead-time on system dynamics. The proposed decoupler is designed based on the dynamic relative gain array (DRGA) to compensate for interaction effects. The DRGA reveals more insights about the coupling effect between a pair of input-output loops. The DRGA elements are used as decoupler elements for the multivariable process. The minimization of both interaction effects and dead-time dynamics can be achieved with the proposed DTC-based decoupling control approach. The simple IM C PI tuning rules are utilized to implement controllers for each loop. The simulation study affirming the proposed method provides better desired closed-loop performance, error indices for nominal and plant model mismatches, and robust stability against plant uncertainty over the popular existing decoupler based approaches. © 2024 IEEE.

关键词： Multivariable control systems

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Rocket Self-learning control based on Lightweight Neural Network Architecture Search

Rocket Self-learning Control based on Lightweight Neural Net...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Wang, Zhaolei Lu, Kunfeng Yu, Chunmei Yao, Na Wang, Ludi Zhao, Jikang Beijing Aerospace Automatic Control Institute Science and Technology on Aerospace Intelligent Control Laboratory Beijing China Beijing Aerospace Automatic Control Institute China Academy of Launch Vehicle Technology Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

Aiming at the problem that the traditional control law design process is complex and relies heavily on accurate mathematical models, this paper uses the Deep Deterministic Policy Gradient (DDPG) reinforcement learning to realize the self-learning of continuous motion control law. However, since the performance of the DDPG algorithm depends heavily on the hyper-parameters, there is no clear design basis for the Actor-Critic framework neural network architecture. Considering that the reinforcement learning requires a large amount of computation, the repetitive manual trial and error of hyper-parameters greatly reduces the design efficiency of the algorithm and increases labor costs. On the basis of converting the network architecture design problem into a graph topology generation problem, an automatic search and optimization framework for deep reinforcement learning neural network structure is given in this paper, where the graph topology generation algorithm based on LSTM recurrent neural network, the weight sharing-based lightweight training and evaluation mechanism of deep reinforcement network parameter, and the policy gradient-based learning algorithm of graph topology generator parameter are innovatively combined. Thus, the neural network hyper-parameters in the DDPG algorithm are automatically optimized, and the control law is obtained by self-learning training. Finally, taking rocket vertical recovery control as an ex-ample, the effectiveness of the proposed method is verified. © 2022 IEEE.

关键词： Learning systems

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Train control System Independent of Communication Transmission Paths

Train Control System Independent of Communication Transmissi...

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2024 IEEE International Conference on Electrical systems for Aircraft, Railway, Ship Propulsion and Road Vehicles and International Transportation Electrification Conference, ESARS-ITEC 2024

作者： Iwamoto, Koki Kitano, Takayasu Gion, Akihiro Railway Technical Research Institute Train Control Systems Signalling&Operation Systems Technology Division Kokubunji Tokyo Japan

ISBN: (纸本)9798350373905

With recent labor shortages in the railway industry, there is a growing need for the streamlining of equipment maintenance in Japan. Currently, many train control systems rely on proprietary networks that use rail current in track circuits for transmission, resulting in costly operation and maintenance of onboard equipment and ground equipment. In order to realize a low-cost train control system, this paper proposed the separation of the security control function and the information transmission function by using public communication lines, which are the most versatile information transmission lines, by offering the prospect of reducing the number of self-owned equipment, including cables, radios, and antennas, in addition, proposed the design policy of a train control system that can adjust the stability of communication transmission paths as the situation demands. © 2024 IEEE.

关键词： IP Network Proprietary Lines Public Communication Lines Railway Communication Train control System

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Optimization of FFT Algorithm Based on Target Location

Optimization of FFT Algorithm Based on Target Location

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2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2022

作者： Wang, Biao Jia, Yanbin Jing, Zhiyu Wang, Xiaoxuan Jia, Sijian Wang, Na North Automatic Control Technology Institute Taiyuan030006 China

ISBN: (纸本)9781665409025

Aiming at the shortcomings of the existing methods of acquiring fixed-range and fixed-velocity information for reconnaissance on the battlefield, a method that can improve precise positioning and speed-fixing is proposed, aiming to optimize the existing positioning and speed-fixing algorithm, using computational sparse fast Fourier transform (SFT) has long existed due to its high efficiency and wide practicability. The algorithm calculates the Discrete Fourier Transform (DFT) through its unique method. This article mainly uses the SFT algorithm of the aliasing filter. Transform the information in the time domain into the information processing method in the frequency domain, effectively integrate and classify the huge data, greatly reduce the amount of calculation, and then visualize and analyze the data through MATLAB simulation, which really effectively improves the positioning The accuracy of fixed speed provides a more reliable source of information and data support for command and decision-making. © 2022 IEEE.

关键词： Discrete Fourier transforms

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Online Identification of Frequency Response of Attitude control System based on Eigensystem Realization Algorithm 22

Online Identification of Frequency Response of Attitude Cont...

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2nd International Conference on control and Intelligent Robotics, ICCIR 2022

作者： Peng, Yue Liu, Jiarun Science and Technology on Aerospace Intelligent Control Laboratory Beijing Aerospace Automatic Control Institute Beijing China China Academy of Launch Vehicle Technology Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9781450397179

In view of the problems that the existing attitude control system identification algorithms often rely on actively applying the excitation signal in the loop, which may lead to actuator damage, control quality degradation and long identification time, this paper studies an identification algorithm without actively applying the excitation signal - Eigensystem Realization Algorithm (ERA).The algorithm can be carried out under closed-loop conditions without affecting the stability and safety of flight *** on a simple state-space model, this paper analyzes the difference of the identification effect of the algorithm under different parameter settings, and applies the algorithm to the frequency response identification of the attitude control system of a vertical take-off and landing (VTOL) verification *** simulation results show that the identification results of the new algorithm have a certain reference value for the verification and evaluation of control system design results, and provide a new idea for the field of online identification of aircraft dynamic characteristics. © 2022 ACM.

关键词： Frequency response

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Adaptive Finite-Time control of Uncertain Mixed-Order Fully Actuated Nonlinear systems with Parameter Estimations

Adaptive Finite-Time Control of Uncertain Mixed-Order Fully ...

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2023 China Automation Congress, CAC 2023

作者： Gao, Yajun Duan, Guang-Ren Harbin Institute of Technology Center for Control Systems and Guidance Technology Harbin China Southern University of Science and Technology Center for Control Science and Technology Shenzhen China

ISBN: (纸本)9798350303759

The finite-time control (FTC) problem, in this paper, is investigated for uncertain mixed-order fully actuated nonlinear (UMOFAN) systems with parameter estimations. A new finite-time controller is proposed that can make the origin of the closed-loop system finite-time stable and make parameter estimations close to their real values at the same time. In the control design process, the requirement for the state derivative information is eliminated via filters. Furthermore, the parameter in the adaptive law is updated by utilizing past and concurrent data on the basis of concurrent learning, thereby alleviating the persistent exciting (PE) condition. The effectiveness and the practicability of proposed control method are illustrated on the basis of the application of the permanent magnet synchronous motor (PMSM). © 2023 IEEE.

关键词： Parameter estimation

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