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International Conference on Industrial Artificial Intelligence (IAI)
2024 6th International Conference on Industrial Artificial Intelligence (IAI)
21-24 Aug. 2024
Showing 1-25 of 114
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
63275 - IAI, 2024 (PRT)
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Table of Contents
Spatial-Temporal Graph Fusion Transformer for Long-term Water Quality Prediction
Ziqi Wang;Xiangxi Wu;Xingyang Chang;Renren Wu;Jing Bi;Junfei Qiao
Publication Year: 2024,Page(s):1 - 6
Over the past decades of rapid development, the global water pollution problem has become prominent. Accurate water quality prediction can detect the trend and anomaly of water quality changes in advance, thereby taking timely measures to avoid the occurrence of water quality problems. Traditional statistical methods for water quality prediction make it difficult to capture the complex relationshi...Show More
The feedback control system, which is closed loop through the real time network, is called the networked control system. Because of the existence of the control loop network, the analysis and design of the networked control system become complex. The traditional control theory should be re-evaluated before it can be applied to the networked control system. A large number of literatures and researc...Show More
Task Allocation and Path Planning for Multiple Destinations Oriented Towards Task Updates
Yong Yang;Dingxin He;Huantao Mao;Hong Chen;Hongtao Wu;Zhi-Wei Liu
Publication Year: 2024,Page(s):1 - 6
This study addresses the complexities of orchestrating multi-target transportation tasks within multi-agent systems, constrained by load capacity. The primary objective is to engineer an advanced path planning framework that assures collision avoidance and optimal load distribution. Diverging from conventional single-path strategies, this research incorporates load factors and requires continuous ...Show More
DRL-Based Resource Scheduling for Control System in Heterogeneous Environment
Publication Year: 2024,Page(s):1 - 6
We investigate the scheduling problem of control tasks in heterogeneous environments. We measure the computational resource required for linear quadratic regulators (LQR) and model the scheduling problem as the bin packing problem. We formulate the bin packing problem as a Markov Decision Process. In the Markov Decision Process, we generate two action subspaces within the action space and propose ...Show More
This paper is concerned with the tracking con-trol problem with prescribed performance for multiple-input and multiple-output (MIMO) nonlinear systems. The prescribed performance means that the system outputs track the given trajectories with the arbitrarily predefined speed of response and accuracy. Most prescribed performance control (PPC) solutions for MIMO systems fail to achieve global tracki...Show More
Penetration-Free Collision Detection and Response Algorithm Based on Extended Position-Based Dynamics
Minghui Wang;Fan Ding;Chengye Liao;Yangyang Pan;Tao Yang;Jianping He
Publication Year: 2024,Page(s):1 - 6
In the virtual simulation platform, frequent physical interactions between the robot and the environment poses extremely high demands on the handling of collisions and contacts in the simulation. Current mainstream virtual simulation platforms, in pursuit of real-time performance, have sacrificed some accuracy in simulation algorithms, leading to control strategies obtained in training that are di...Show More
A Motion Intent Recognition Method Based on Dynamic Feature Fusion and Multi-Stream TCN
Publication Year: 2024,Page(s):1 - 6
Clinical motor relearning theory emphasizes the active participation of patients, so the recognition of patient's motor imagery plays a key role in robot-assisted rehabilitation exercise training. We constructed an upper limb rehabilitation sEMG (Surface Electromyography) dataset by capturing 18 upper limb rehabilitation movements using a wireless sEMG acquisition system and proposed a deep learni...Show More
The Experimental Research On Off-axis Digital Holography Recording And Reconstruction Based On MATLAB Simulation
Publication Year: 2024,Page(s):1 - 6
This article first analyzes the two-step imaging process in optical holography, namely wavefront recording and wavefront reconstruction. According to the relationship of the four diffraction components in the spatial spectrum of the off-axis digital holography diffraction process, the minimum angle is derived between the object light and the reference light of the off-axis digital holography. Acco...Show More
Energy-Saving Control of Air Conditioning Water System Based on Improved NSGA-II Algorithm
Yangrui Gong;Xiangshun Li;Xu Zhang;Yi Liu;Boya Qin;Huibin Li;Qijing Kong
Publication Year: 2024,Page(s):1 - 6
The energy consumed by the HVAC system to maintain thermal comfort inside the building accounts for more than 50% of its energy consumption. The water system is the core of the HVAC system, and unreasonable control of the water system will lead to a significant amount of energy consumption. Therefore, research on energy-saving control of the water system is very important. Currently there are many...Show More
Multitarget Robust Deep Stochastic Configuration Network Parameter Modeling Method
Publication Year: 2024,Page(s):1 - 5
To improve the model accuracy of deep stochastic configuration network (DSCN) in multitarget robust parameter modeling tasks, this paper presents a multitarget robust DSCN modeling method. This method expands the hidden layer output matrix by optimizing the network model structure and exploiting the correlation between multiple targets to improve the modeling quality. The model output weights are ...Show More
A New Robust Learning Algorithm for Ordinary Differential Equation Network
Publication Year: 2024,Page(s):1 - 6
The data modeling of complex systems typically exhibits characteristics such as strong nonlinearity, variable redundancy, and abnormal data, all of which tend to decrease the model performance. To solve these problems, a robust learning algorithm for an ordinary differential equation (ODE) network is proposed. Firstly, the ODE network is trained as the basic model. Secondly, a novel loss function ...Show More
Sensor Fault Estimation Based on Dynamic Event-triggered Mechanism and Interval Observer
Publication Year: 2024,Page(s):1 - 6
In this paper, the problem of fault estimation(FE) for a class of systems with dynamic event-triggered mecha-nism(ETM) in network environment is studied. In order to increase the interval between events and reduce the amount of data transmission, this paper introduces internal dynamic vari-ables into the event-triggered mechanism and modifies the event- triggered threshold. Then, for the augmented...Show More
Mixup Enhanced Linear Robust Explainable Model for Identifying Key Factors of Surface Defects in Strip Steel Manufacturing
Jinchuan Qian;Xuerui Zhang;Songyan Pi;Zhihuan Song;Xinmin Zhang
Publication Year: 2024,Page(s):1 - 6
The surface defect is a common defect in strip steel products, which can seriously affect the various properties of the strip steel. This paper aims to propose a key influencing factor identification indicators based on the idea of explainable artificial intelligent to assist engineers in locating key variables related to surface defects. In the practical application, the obtained data show the ch...Show More
Fuzzy Neural Networks-Based Intelligent Tracking Control for Flexible-Joint Industry Robotic Manipulator
Publication Year: 2024,Page(s):1 - 6
Due to the unstructured environment and the complex target tasks, the traditional mechanism and control theory are not able to meet the requirements of the real-time high-accuracy control of the environment-adaptive robot systems. This paper focuses on flexible-joint industry robotic manipulator, which can effectively resist external forces and reduce the vibration. Fuzzy neural networks-based int...Show More
Research Progress and Key Technology Analysis in Cooperative Control of Dual Robots
Publication Year: 2024,Page(s):1 - 6
To meet the intricate demands of modern industries, multi-robot cooperative control systems offer broad applications, robust fault tolerance, and high efficiency. This research proposes trajectory compensation and digital twin technology as remedies for challenging collaborative planning, low real-time and accuracy, limited model accuracy, and inadequate planning of complicated tasks in dual-robot...Show More
In order to solve the problems of long manual titration time, cumbersome operation, reliance on human eye judgment, and errors in titration endpoint in chemical quantitative testing. This paper designs a automatic chemical solution titration equipment and proposes a titration recognition method based on HSV color space. A typical chemical titration color model is established, and the RGB color spa...Show More
Priors-Informed Machine Learning for Dynamic System Modelling: Mecanum Wheel as an Example
Publication Year: 2024,Page(s):1 - 6
An accurate dynamic model holds critical significance for model based applications such as state estimation, system control, monitoring and optimization. While first principles based dynamic modelling allows for clear interpretability, it faces difficulties for complex systems under uncertainties. Purely data-driven machine learning based black box modelling is easy to implement but has low interp...Show More
Genetic Algorithm for Scheduling of Steelmaking and Continuous Casting Processes Considering Earliness/Tardiness Penalty*
Publication Year: 2024,Page(s):1 - 5
The production scheduling for steelmaking and continuous casting operations involves the allocation of each heat to specific equipment at various stages within the steelmaking process. Refinement and continuous casting are performed in accordance with the casting plans formulated by the planner and simultaneously determine the production sequence and start/finish time of heats on each equipment. T...Show More
Variable Neighborhood Search for Scheduling of Cold Rolling Annealing Process of Silicon Steel*
Publication Year: 2024,Page(s):1 - 5
Aiming at the production scheduling problem of cold rolling annealing process of silicon steel, a multi-objective optimization model of production scheduling is established, which considered various process constraints such as steel grade switch, width jump, annealing temperature jump, etc. The multi-objective functions are transformed into a single objective function by weighted sum method. Based...Show More
Incremental Learning based Broad Canonical Correlation Analysis Network for Industrial Process Monitoring
Publication Year: 2024,Page(s):1 - 6
This paper proposes an incremental learning based broad canonical correlation analysis network (ILBCCAN) to address the time-consuming problem of deep learning models in training process. It uses canonical correlation window, mapping window, and enhancement window to extract the correlation and nonlinear structure between variables, thus improves the feature extraction capability. Moreover, it con...Show More
Multi-Objective Optimization of Wastewater Treatment Process Based on Improved Fast Non-Dominated Sorting Algorithm with Hybrid Crossover Operator
Publication Year: 2024,Page(s):1 - 6
With the increasingly serious water pollution problems, wastewater treatment process has become a hot spot in today's research. The key issue of wastewater treatment process is to achieve the optimization of the system's energy consumption and cost reduction under the premise of meeting the effluent water quality standards, so as to achieve the purpose of “maintaining quality and reducing consumpt...Show More
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
63275 - IAI, 2024 (PRT)
- Print on DemandPurchase at Partner
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