基于数据驱动和联合设计的无线网络化控制系统的使能建模和设计

项目摘要

无线网络化控制系统提供了对车联网、信息物理系统等新型智能系统的关键基础性赋能能力，是作为控制系统“第三形态”的网络化控制系统的必然发展趋势和未来研究的重心，具有根本的重要性。尽管该类系统在国际上已成为学术研究的热点，在国内研究尚不充分，且现有研究具有“模型一般性强，针对性不足，方法理论性强，实用性不足”的缺点。针对该类系统研究的重要性和急迫性，本项目以理论和应用赋能为根本目标，拟进行以数据驱动无线特性在线建模为标志的模型创新、以联合设计使能框架为标志的方法创新、和以层次化模块化混合仿真实验为标志的平台创新，解决无线特异性在理论和应用赋能要求下的定量表征、非实时不可靠无线数据传输和应用赋能要求下的控制设计挑战、使能模型和设计下的闭环分析和优化等科学问题，最终形成由使能建模、使能设计和专用仿真平台所构建的一整套解决方案，有效赋能该领域的理论研究和典型应用。

研究背景

• 以“网络共享”信道为本质特点的网络化控制系统形成了控制系统的“第三形态”，处于理论和应用研究的前沿
• “无线化”是网络化控制系统的必然发展趋势和未来研究的重心
• 无线网络化控制系统的研究提供了对IoT、CPS、IoV等新型智能系统的关键基础性赋能能力，具有根本的重要性
• “无线”的独特网络共享限制冲击了有线网络化控制系统的研究范式

研究目标

• 以使能建模有效赋能理论研究。通过发展无线通信网络特性的使能建模方法和建设相关混合仿真平台，有效赋能无线网络化控制系统理论研究，允许既有理论研究做适应于新型智能系统应用的改造，并支持本项目使能设计研究。
• 以使能设计有效赋能典型应用。通过发展无线网络化控制系统的使能设计方法和建设相关混合仿真平台，构建一套完整的使能设计框架及其验证方法，有效赋能无线网络化控制系统典型应用。

主要研究内容

• 面向理论赋能的无线通信网络特性分析和使能建模
  • 新型智能系统中无线通信网络的特性分析
  • 面向理论赋能的无线通信网络的使能建模
  • 基于混合仿真平台的使能建模仿真实验验证
• 面向应用赋能的无线网络化控制系统使能设计和闭环分析
  • 面向应用赋能的无线网络化控制系统的使能设计
  • 无线网络化控制系统使能设计的闭环分析和优化
  • 基于混合仿真平台的使能设计仿真实验验证
• 支持理论和应用赋能验证的混合仿真实验平台建设

基本研究框架

相关阅读

研究成果

Journal Articles

1. Deep Reinforcement Learning for Maintenance Optimization of Multi-Component Production Systems Considering Quality and Production Plan Ming Chen, Yu Kang, Kun Li, Pengfei Li, and Yun-Bo Zhao Quality Engineering 2024 [doi] [pdf]
2. Robust Bipartite Output Regulation of Linear Uncertain Multi-Agent Systems Under Observer-Based Protocols Jiashuo Liu, Cui-Qin Ma, Yun-Bo Zhao , and Yu Kang IEEE Trans. Circuits Syst. II 2024 [Abs] [doi] [pdf]

   Robust bipartite output regulation of linear uncertain multi-agent systems is studied over a signed digraph. Since only parts of agents have access to the information of the exosystem, a distributed observer is introduced to estimate the exosystem state for each agent. Then, a distributed control protocol is proposed based on the internal model method and observer for the exosystem. By exploiting matrix analysis and algebraic graph theory, sufficient conditions for achieving robust bipartite output regulation are given. It is shown that the multi-agent system being structurally balanced and the augmented multiagent system having a spanning tree with the exosystem being the root are the communication topology conditions for ensuring robust bipartite output regulation. Finally, the correctness of the results is validated by an example.

3. PCB Layout-Based Spatio-Temporal Graph Convolution Network for Anomaly Prediction in Solder Paste Printing Binkun Liu, Yun-Bo Zhao , Yu Kang, Yang Cao, and Zhenyi Xu IEEE Trans. Compon. Packag. Manuf. Technol. 2024 [Abs] [doi] [pdf]

   Predicting solder paste printing anomaly on the printed circuit board (PCB) can improve first-pass yield and reduce rework costs. Considering the impact of PCB layout on the quality of solder paste printing, we propose a PCB layoutbased spatio-temporal graph convolution network, in which we construct a graph to model the spatial distribution of solder pads. Specifically, since the printing quality is related to the spatial distribution of the pads, we convert the PCB to a graph according to the Pearson correlation of the printing quality and then trim the edges of the graph with a correlation threshold to model the spatial distribution of solder pads. To model the timevarying physicochemical properties of the solder paste, normalize the production time, calculate the attention of the production time, and reconstruct the printing quality based on the attention. And then, we devise a weighted loss to improve the performance of predicted printing defective products due to the scarcity of defective products. Ultimately, the predicted printing quality is compared with the inspection threshold to estimate degree of anomaly. The proposed method is validated on six-day of real solder paste printing data, improving the average F1 score by 0.057 and the average accuracy by 0.022 for three typical anomalous printing behaviours over two temporal prediction scales.

4. Multivariate Time Series Modeling and Forecasting with Parallelized Convolution and Decomposed Sparse-Transformer Shusen Ma, Yun-Bo Zhao , Yu Kang, and Peng Bai IEEE Trans. Artif. Intell. 2024 [Abs] [doi] [pdf]

   Many real-world scenarios require accurate predictions of time series, especially in the case of long sequence timeseries forecasting (LSTF), such as predicting traffic flow and electricity consumption. However, existing time series prediction models encounter certain limitations. Firstly, they struggle with mapping the multidimensional information present in each time step to high dimensions, resulting in information coupling and increased prediction difficulty. Secondly, these models fail to effectively decompose the intertwined temporal patterns within the time series, which hinders their ability to learn more predictable features. To overcome these challenges, we propose a novel endto-end LSTF model with parallelized convolution and decomposed sparse-Transformer (PCDformer). PCDformer achieves the decoupling of input sequences by parallelizing the convolutional layers, enabling the simultaneous processing of different variables within the input sequence. To decompose distinct temporal patterns, PCDformer incorporates a temporal decomposition module within the encoder-decoder structure, effectively separating the input sequence into predictable seasonal and trend components. Additionally, to capture the correlation between variables and mitigate the impact of irrelevant information, PCDformer utilizes a sparse self-attention mechanism. Extensive experimentation conducted on five diverse datasets demonstrates the superior performance of PCDformer in LSTF tasks compared to existing approaches, particularly outperforming encoder-decoder-based models.

5. Rolling Self-Triggered Distributed MPC for Dynamically Coupled Nonlinear Systems Tao Wang, Yu Kang, Pengfei Li, Yun-Bo Zhao , and Hao Tang Automatica 2024 [Abs] [doi] [pdf]

   The mutual influences caused by dynamic couplings in large-scale systems increase the difficulty in the design and analysis of distributed model predictive control (DMPC), and require information exchange among subsystems which calls for a scheduling strategy to save communication resources in communication-limited environments. To circumvent the two problems, we design a rolling selftriggered DMPC strategy for large-scale dynamically coupled systems with state and control input constraints. First, the optimal control problem where the cost is subject to the coupled dynamic and the constraints are subject to the uncoupled counterpart is proposed, forming the dual-model DMPC that is simple in design and analysis but yields good control performance. Second, the information exchange only occurs at some specified triggering instants determined by a rolling self-triggered mechanism, saving communication resources more significantly. The effectiveness of the designed strategy is verified by numerical simulations.

6. Unified Fuzzy Control of High-Order Nonlinear Systems With Multitype State Constraints Yangang Yao, Yu Kang, Yunbo Zhao, Pengfei Li, and Jieqing Tan IEEE Trans. Cybern. 2024 [Abs] [doi] [pdf]

   This article presents a unified adaptive fuzzy control approach for high-order nonlinear systems (HONSs) with multitype state constraints. Existing methods always require that the upper and lower constraint boundaries are strictly positive and negative functions (or constants) respectively, which is often inconsistent with the actual constraints. In this article, “multitype state constraints” means that the upper and lower constraint boundaries include multiple types, such as both being strictly positive (or negative), sometime be positive or negative and so on (cases \" -\textpm). By designing a unified mapping function (UMF), the multi-type state constraints are processed under removal the feasibility conditions (FCs). Furthermore, a technical design makes the proposed method also suitable for unconstrained HONSs. By means of fuzzy logic system (FLS) and fixed-time stability theory (FTST), the proposed algorithm can ensure that the tracking error converges to a zero-centered neighborhood within a fixed time. In addition, the adaptive event-triggered control (AETC) technique which can adjust trigger threshold automatically according to tracking error is introduced to save network resources. Simulation results demonstrate the scheme developed.

7. Flexible Prescribed Performance Output Feedback Control for Nonlinear Systems With Input Saturation Yangang Yao, Yu Kang, Yunbo Zhao, Pengfei Li, and Jieqing Tan IEEE Trans. Fuzzy Syst. 2024 [doi] [pdf]
8. A Novel Prescribed-Time Control Approach of State-Constrained High-Order Nonlinear Systems Yangang Yao, Yu Kang, Yunbo Zhao, Pengfei Li, and Jieqing Tan IEEE Trans. Syst. Man Cybern, Syst. 2024 [Abs] [doi] [pdf]

   A novel practical prescribed-time control (PPTC) approach for high-order nonlinear systems (HONSs) subject to state constraints is studied in this article. Different from the existing methods which always require the constraint boundaries to be continuous functions, the state constraints considered in this article are discontinuous (i.e., the state constraints occur only in some time periods and not in others), which can be found in many practical systems. By designing a novel stretch modelbased nonlinear mapping function (NMF), the state constraints are dealt with directly, and the limitations that the virtual control function depends upon the feasibility condition (FC) and the tracking error depends upon the constraint boundaries in the conventional schemes are removed. Meanwhile, the proposed method is a unified one, which is also effective for HONSs with conventional continuous state constraints/ deferred state constraints/ funnel constraints or constraints-free without altering the control structure. Furthermore, by designing a newly timevarying scaling transformation function (STF), a more relaxed criterion for practical prescribed-time stable (PPTS) is given, based on which a newly PPTC algorithm is designed. The result shows that the proposed algorithm can preset the upper bound of the settling time, which does not depend upon the initial state of the system and control parameters, the limitations of singularity problem and excessive initial control input in existing methods are removed. Simulation examples verify the algorithm developed.

9. Event-Based Enhancing Prescribed Performance Control for Stochastic Non-Triangular Structure Nonlinear Systems: A Mtbfs-Based Approach Yuandong Zhu, Yangang Yao, Yu Kang, Yunbo Zhao, Jieqing Tan, Lichuan Gu, and Xuexiu Liang Nonlinear Dyn 2024 [doi] [pdf]
10. 基于动态信道切换的无线网络化控制系统的资源调度策略 郝小梅, and 赵云波 高技术通讯 2023 [Abs] [pdf]

    本文针对通信网络中存在竞争和非竞争信道的无线网络化控制系统，提出了一种基于估计 器的信道选择策略，在保证控制系统稳定性的同时尽可能地节约了宝贵的非竞争信道资源。在无 线网络化控制系统中，控制信号通过竞争信道传输时可能发生数据包丢失，导致执行器无法收到 实时的控制信号。而传感器端未知控制信号的实际传输情况，因而也无法得知每个时刻执行器所 使用的控制信号。针对这种情况，本文首先设计了估计器来估计执行器端上一时刻实际使用的控 制信号，再通过信道选择策略来约束执行器端使用控制信号的误差。然后，在所提信道选择策略 下设计控制器来保证控制系统稳定。最后，通过数值仿真验证了所提算法的有效性。

11. Compound Event-Triggered Distributed MPC for Coupled Nonlinear Systems Yu Kang, Tao Wang, Pengfei Li, Zhenyi Xu, and Yun-Bo Zhao IEEE Trans. Cybern. 2023 [Abs] [doi] [pdf]

    This paper investigates the event-triggered distributed model predictive control (DMPC) for perturbed coupled nonlinear systems subject to state and control input constraints. A novel compound event-triggered DMPC strategy, including a compound triggering condition and a new constraint tightening approach, is developed. In this event-triggered strategy, two stability-related conditions are checked in a parallel manner, which relaxes the requirement of the decrease of the Lyapunov function. As a result, the number of triggering instants can be reduced significantly. Furthermore, the proposed constraint tightening approach solves the problem of the state constraint satisfaction, which is quite challenging due to the external disturbances and the mutual influences caused by dynamical coupling. Simulations are conducted at last to validate the effectiveness of the proposed algorithm.

12. Disturbance Prediction-Based Adaptive Event-Triggered Model Predictive Control for Perturbed Nonlinear Systems Pengfei Li, Yu Kang, Tao Wang, and Yun-Bo Zhao IEEE Trans. Automat. Contr. 2023 [Abs] [doi] [pdf]

    A disturbance prediction based adaptive event-triggered model predictive control scheme is proposed for nonlinear systems in the presence of slowly varying disturbance. The optimal control problem in the model predictive control scheme is formulated by taking advantage of a proposed central path-based disturbance prediction approach, and the event-triggered mechanism is designed to be adaptive to the triggering interval. As a result, the proposed scheme improves the state prediction precision and hence reduces greatly the triggering frequency. Furthermore, for input-affine nonlinear systems, the disturbance separation and compensation techniques are developed to further enlarge the triggering interval. Theoretical analysis of the algorithm feasibility and closed-loop stability, as well as numerical evaluations of the effectiveness of the proposed schemes, are also given.

13. Leader-Following Cluster Consensus of Multiagent Systems With Measurement Noise and Weighted Cooperative–Competitive Networks Cui-Qin Ma, Tian-Ya Liu, Yu Kang, and Yun-Bo Zhao IEEE Trans. Syst. Man Cybern, Syst. 2023 [Abs] [doi] [pdf]

    Leader-following cluster consensus is investigated for multi-agent systems with weighted cooperative-competitive networks and measurement noise. A stochastic approximation protocol is proposed for interactively balanced and sub-balanced networks, and pinning control is introduced to deal with the divergence phenomenon in interactively unbalanced networks. With these protocols, sufficient conditions for reaching strong mean square leader-following cluster consensus are established for all the three types of networks, which are also extended to the cases without measurement noise. Numerical examples illustrate the effectiveness of the proposed protocols and theoretical analysis.

14. 具有领导者的高阶线性多运动体系统的群智汇集趋同 马翠芹, 杜梅, and 赵云波 中国科学 技术科学 2023 [Abs] [doi] [pdf]

    本文研究了具有领导者的高阶线性多运动体系统的群智汇集趋同问题. 利用运动体与其邻居的信息, 分别 为跟随者设计了状态反馈型和输出反馈型控制协议, 并利用矩阵Riccati代数方程、矩阵分析等工具, 给出了系统 实现领导-跟随者群智汇集趋同的充分条件. 研究表明, 当领导者和跟随者所组成的多运动体系统的通信拓扑交 互平衡并且存在一棵生成树时, 只要合理地选取满足条件的控制增益, 系统在所给出的控制协议作用下可以实现 领导-跟随者群智汇集趋同. 特别地, 当为跟随者设计输出反馈型控制协议时, 借助误差系统可以将领导-跟随者群 智汇集趋同问题转化为静态输出反馈问题. 当系统的输入输出矩阵满足一定的秩条件时, 系统在所设计的输出反 馈型控制协议作用下可以实现领导-跟随者群智汇集趋同.

15. 基于优先级预测器的无线网络化控制系统的动态传输策略 闫文晓, and 赵云波 高技术通讯 2023 [Abs] [doi] [pdf]

    文针对无线通信网络中存在丢包的多包传输无线网络化控制系统，提出了一种基于预测 器的动态传输策略，在几乎不增加信道资源占用的情况下显著提升系统稳定性。在多包传输的无 线网络化控制系统中，由于通信资源的限制，传感器到控制器间的数据传输中出现丢包问题，影 响控制系统性能。针对这个问题，本文首先设计了优先级预测器来预测下一时刻每个传感器数据 对系统稳定性的影响，帮助系统决策每个传感器的发送优先级，再通过传输调节器对不同优先级 传感器补偿相应的随机退避时间上限，进而让优先级高的传感器在随机退避的方式下优先传输， 然后在此策略下设计控制器使系统稳定。最后通过数值仿真验证了本文策略的有效性。

16. 面向人机序贯决策实现共享控制下的仲裁优化 张倩倩, 赵云波, 吕文君, and 陈谋 中国科学：信息科学 2023 [Abs] [doi] [pdf]

    共享控制存在于众多由人类智能和机器智能共同参与的序贯决策场景. 由于人的决策范围和 智能机器的决策范围尚未予以明确划分, 需要加以实时仲裁从而达到人机共存并且共享决策权限. 为 此本文提出了一种仲裁优化方法, 该方法的独特之处在于引入自主性边界概念, 优化了共享控制中人 机决策动作的仲裁机制. 本文为自主性边界的计算和更新维护提供了思路, 能够基于贝叶斯规则的意 图推理分析人机共享系统可能要实现的目标, 从而确定仲裁参数. 此外, 本文还分析了自主性边界的 不确定性以促进边界信息对共享控制中决策质量的优化效果. 实验结果表明, 所提出的方法在累积奖 励、成功率、撞击率方面表现出色, 这些说明了本文提出的共享控制中的仲裁优化方法在求解人机序 贯决策问题时的有效性和价值.

17. Event-Based Model Predictive Control for Nonlinear Systems with Dynamic Disturbance Pengfei Li, Tao Wang, Yu Kang, Kun Li, and Yun-Bo Zhao Automatica 2022 [Abs] [doi] [pdf]

    In this paper, we investigate the event-based model predictive control (MPC) for constrained nonlinear systems with dynamic disturbance. An event-triggered disturbance prediction MPC (DPMPC) scheme and a self-triggered counterpart, which explicitly consider the disturbance dynamics, are proposed. For the event-triggered DPMPC scheme, the triggering condition relying on the state prediction error and the predicted disturbance sequence, updates at each time step based on the system states. For the self-triggered DPMPC scheme, the next triggering instant is determined by using the optimal state sequence and predicted disturbance sequence. In both event-based schemes, the optimal control problems are solved only at triggering instants, thus reducing the consumption of computational resources. The effectiveness of the two schemes is demonstrated by a simulation example.

18. Cluster Consensus for Coupled Harmonic Oscillators Under a Weighted Cooperative-Competitive Network Cui-Qin Ma, Tian-Ya Liu, and Yun-Bo Zhao International Journal of Control 2022 [Abs] [doi] [pdf]

    Cluster consensus is investigated for multiple coupled harmonic oscillators under a weighted cooperativecompetitive network. Consensus protocols for three categories of communication networks are constructed by employing a weighted gain, and sufficient conditions for guaranteeing cluster consensus are obtained. It is found that under the proposed protocols, the states of all oscillators can be guaranteed to reach periodic orbits that are the same in frequency no matter which cluster the oscillators belong to. In particular, cluster partitions here are not given a prior, but are determined by the communication topology among oscillators. Numerical examples are given to validate the effectiveness of theoretical results.

19. DoS攻击下基于自适应事件触发的无人水面艇航向控制和故障检测 赵云波, 王岭人, and 叶泽华 高技术通讯 2022 [Abs] [pdf]

    针对网络能力受限和非周期DoS攻干扰的网络化USV系统，提出一种基于自适应事件触发的故障检测滤波器和控制器的设计方法。首先，构建一个考虑非周期DoS攻击、外部干扰和执行器故障同时存在的USV控制系统。然后，针对网络化USV系统，提出一种自适应事件触发机制，动态更新触发阈值，减少网络资源浪费。其次，通过构造一个分段Lyapunov函数，给出闭环系统全局指数稳定且具有指定H_∞干扰衰减指数的充分条件，并设计基于观测的故障检测滤波器和控制器。最后，通过仿真验证方法的有效性。结果表明，该方法不仅能对USV系统航向进行有效控制，而且能在节省网络资源的同时检测执行器故障的发生和位置。

Conference Articles

1. A Reliable Ensemble Model Based on Hierarchical Component Features for Repair Label Prediction of Soldering Defects Longxin Chen, Yunbo Zhao, Binkun Liu, Shaojie Dong, Huijuan Zhu, and Peng Bai In 2024 14th Asian Control Conf. ASCC 2024 [Abs] [pdf]

   Using solder paste inspection (SPI) and automated optical inspection (AOI) data, accurate prediction for repair labels of soldering defective printed circuit board (PCB) components can help reduce labor costs. Existing research tries to pick out both the false defect components (actually good) and impossible-to-repair components among defective PCB components, using SPI and AOI data. However, it is inappropriate to pick out the false defect components from screened components using defective information in AOI data. Therefore, the problem setting of existing research is inappropriate, resulting in the algorithm’s performance not meeting actual requirements. To address this problem, we only care about the reliable prediction of impossible-to-repair components. We propose a hierarchical component feature extraction method that can comprehensively characterize the degree of component defects from multiple levels, including pin level and component level. Then we apply the ensemble model based on XGBoost and TabNet and adjust the probability threshold of components judged as impossible-to-repair category, achieving the reliable prediction of impossible-to-repair components. Finally, we validated our method on real datasets and achieved better experimental results compared to baseline methods, which can meet actual requirements,

2. Uncertainty-Based Dynamic Weighted Experience Replay for Human-in-the-Loop Deep Reinforcement Learning Xia Tian, Yu Kang, Yun-Bo Zhao , Ya-Qing Zhou, and Peng-Fei Li In 2024 [Abs] [pdf]

   Human-in-the-loop reinforcement learning (HIRL) enhances sampling efficiency in deep reinforcement learning by incorporating human expertise and experience into the training process. However, HIRL methods still heavily depend on expert guidance, which is a key factor limiting their further development and largescale application. In this paper, an uncertainty-based dynamic weighted experience replay approach (UDWER) is proposed to solve the above problem. Our approach enables the algorithm to detect decision uncertainty, triggering human intervention only when uncertainty exceeds a threshold. This reduces the need for continuous human supervision. Additionally, we design a dynamic experience replay mechanism that prioritizes machine self-exploration and humanguided samples with different weights based on decision uncertainty. We also provide a theoretical derivation and related discussion. Experiments in the Lunar Lander environment demonstrate improved sampling efficiency and reduced reliance on human guidance.

3. Trust-Modulated Authority Allocation in Human-Guided Goal Recognition Tasks Rui-Yu Xia, Yun-Bo Zhao , Jun-Sen Lu, Yang Wang, Peng-Fei Li, and Yu Kang In 2024 [Abs] [pdf]

   In shared control teleoperation, the machine infers the humans’ goal to provide effective assistance, which we call human-guided goal recognition. However, current methods mainly use algorithm confidence to assign control authority during the process, which makes it difficult to correct machine inference errors under high confidence. To address this problem, we propose a trust model that considers machine capability fluctuations and human-machine interaction experience. We also add trust as a dynamic assessment of machine capabilities to authority allocation to improve the success rate of the tasks. Finally, we verify the effectiveness of the proposed method through experiments.

4. Prediction of Yield in Functional Testing of Motherboards in Laptop Manufacturing Yunbo Zhao, Shaojie Dong, Yu Kang, Kangcheng Wang, Longxin Chen, and Peng Bai In 2024 14th Asian Control Conf. ASCC 2024 [Abs] [pdf]

   Functional testing stands as a pivotal quality control step in the production process of laptop motherboards, aiming to validate the proper functioning of various components. However, due to the multitude of functional modules involved on the motherboard, testing all of them requires a significant amount of time and resources. As a result, production line engineers often rely on empirical selection of modules with low yield rates for testing. However, such empirical yield estimation is often inaccurate. To address this challenge, this study proposes a hybrid model based on XGBoost and Long Short-Term Memory (LSTM) networks to predict the yield of each functional module. By harnessing the feature learning capability of XGBoost and the sequential modeling power of LSTM, this model efficiently explores the intricate correlations among motherboard functional modules, thereby accurately forecasting their yields. We extensively train and validate the model using historical production data and successfully deploy it on real laptop motherboard production lines. Experimental results demonstrate that our hybrid model accurately predicts the yield of each functional module, providing crucial guidance for the functional testing process. Through in-depth analysis of the predicted yield results, engineers can systematically choose testing projects to save time and resources. This research offers a novel approach and pathway for enhancing motherboard production efficiency and quality.

5. Board-Level Functional Test Selection Based on Fault Tree Analysis Yaoyao Li, Kangcheng Wang, Yu Kang, Yunbo Zhao, and Peng Bai In 2023 6th Int. Symp. Auton. Syst. ISAS 2023 [Abs] [doi] [pdf]

   With the increasing complexity of the circuit board, the cost of board-level functional test ensuring the board quality becomes dramatically high. Data-driven-based test selection methods have been widely studied for test-cost reduction. However, existing test selection methods tend to overfit due to overlooking the root causes of faulty boards. To address this issue, a test selection method based on reliability analysis is proposed. A fault tree oriented to the board-level functional test is established for analyzing the reliability of the board and test items. The reliability analysis result is then effectively utilized to formulate a test selection method. Three indices are introduced to evaluate the test efficiency and the test quality. Experimental results demonstrate the effectiveness of the proposed method.

6. A Feature Engineering-based Method for PCB Solder Paste Position Offset Prediction Binkun Liu, Yunbo Zhao, Yu Kang, Yang Cao, Peng Bai, and Zhenyi Xu In 2023 6th Int. Symp. Auton. Syst. ISAS 2023 [Abs] [doi] [pdf]

   Solder paste printing position offset is a common type of defective printed circuit board (PCB) printing, and accurate position offset prediction helps to avoid the production of defects, thus improving efficiency. The existing methods mainly use the powerful nonlinear fitting ability of deep learning to learn the variation pattern of solder paste printing quality to achieve a good prediction. However, factories also focus on the interpretability of the model, and existing methods are difficult to give the basis for decisions, so there are still limitations in the practical application. To solve this problem, we propose a Support vector machine (SVM) approach, in which we manually design 14 statistical features based on the original data, then the resampling reduces the effect of data imbalance and achieves PCB pad-level offset prediction. Finally we verified on about one week of real solder paste printing production data and achieved good experimental results.

7. Defect Detection of Laptop Appearance Based on Improved Multi-Scale Normalizing Flows Jie Zhang, Zerui Li, and Yunbo Zhao In 2023 38th Youth Acad. Annu. Conf. Chin. Assoc. Autom. YAC 2023 [Abs] [doi] [pdf]

   In the laptop production process, timely detection of appearance defects is essential to ensure product quality. At present, there are many shortcomings in the manual visual inspection-based method on the laptops production line. In addition, due to the wide variety of laptop appearance defects and extreme differences in defect scales, existing defect detection algorithms perform poorly in the field of laptop appearance inspection. In response to the above problems, this paper proposes a defect detection algorithm based on improved multi-scale normalizing flows. First, the multi-level features extracted from the backbone network are fused by using the pyramid feature fusion module to obtain multi-scale features with rich semantic and spatial information. Then, the effective density estimation of the multi-scale features is achieved by fusing the normalizing flows of attention mechanisms. Finally, the defects are detected and localized based on the output likelihood values. The experimental results demonstrate the effectiveness of the proposed method in detecting and locating appearance defects.

8. A Robustness Benchmark for Prognostics and Health Management Binkun Liu, Yun-Bo Zhao , Yang Cao, Yu Kang, and Zhenyi Xu In 2022 41st Chin. Control Conf. CCC 2022 [Abs] [doi] [pdf]

   With the rise of intelligent manufacturing, prognostics and health management(PHM) has developed rapidly as an important part of intelligent manufacturing.Existing deep learning-based PHM methods are data-dependent. However, sensor data often contains noise and is redundant and high-dimensional, making it difficult for the PHM methods to learn a stable set of model parameters, so the methods are likely to be wrong when disturbed. However, the factory hopes that the PHM methods are robust enough to adapt to various disturbances, so it is necessary to perform robustness evaluation on the existing methods in advance for easy deployment. Although the existing robust theoretical analysis methods for neural networks can obtain tight robust boundaries, they consume a lot of computing resources and are difficult to scale to large neural networks. To slove this problem, We design a benchmark for robustness analysis of large deep learning PHM models, in which we test the model robustness using a variety of perturbations to simulate the actual production environment of the factory. Specifically, Gaussian noise is used to test the robustness of the model to background noise; random mask is used to test the robustness of the model to data loss. We hope that our robustness benchmark can serve as a reference for designing PHM models to improve the robustness of factory PHM models.

9. Equipment Health Assessment Based on AHP-CRITIC Dynamic Weight Yunsheng Zhao, Pengfei Li, Tao Wang, Yu Kang, and Yun-Bo Zhao In 2022 41st Chin. Control Conf. CCC 2022 [Abs] [doi] [pdf]

   Prognostics Health and Management (PHM) has become a hot research problem with the improvement of different equipment. Besides, it is significant to assess the health status of equipment in PHM because an accurate health assessment can guide maintenance plans for engineers. To accurately reflect equipment health status by an index, an assessment method based on AHP-CRITIC dynamic weight is proposed in this paper. Analytic Hierarchy Process (AHP) is a subjective method used to evaluate the importance of different indicators. The criteria importance through inter-criteria correlation (CRITIC) method is used to calculate the contrast intensity of the same indicator and the conflict between indicators and obtain the objective weights. A set of more scientific weights is gained by combining the weights obtained from AHP and CRITIC, respectively. Moreover, to reflect each indicator’s real impact on overall health status, a dynamic weight adjustment mechanism is used. The case study of suction nozzles of a specific type of chip mounter shows that this method can reflect the health status accurately.

10. Anomaly Detection for Surface of Laptop Computer Based on Patchcore Gan Algorithm Huijuan Zhu, Yu Kang, Yun-Bo Zhao , Xiaohui Yan, and Junqiang Zhang In 2022 41st Chin. Control Conf. CCC 2022 [Abs] [doi] [pdf]

    Timely detection of notebook appearance defects is an important means to prevent products from being delivered to customers before leaving the factory.In industrial production, more emphasis is placed on fast and accurate detection methods, but the existing difficulties: 1. Defect samples are rare and difficult to obtain; 2. In high-resolution images, there are slight differences between abnormal samples and normal samples; 3. Slowly detection and insufficient accuracy.The existing methods mainly use a large amount of abnormal samples, so it is difficult to extend to the field of notebook appearance anomaly detection.To solve this problem, we designed a method that firstly uses unsupervised PatchCore which the algorithm was trained on normal samples and Defect GAN is used in test phase. To create a large number of verisimilitude abnormal samples and test these samples with PatchCore. On TKP-Surface datasets, the AUROC score of image-level anomaly detection achieves 96.1%, which meets the requirements of industrial applications.

Theses

1. 面向分布式模型预测控制的事件驱动策略设计与分析 王涛 中国科学技术大学, 合肥 2023 [Abs] [pdf]

   分布式模型预测控制具有控制性能出色、多约束和多目标处理能力强、灵活 性和容错性高等优点，在智能电网、城市交通网络、工业控制等诸多领域得到了 广泛应用。在该类控制系统中，负责局部优化的节点的计算资源往往有限且节点 之间信息的传输容易受到网络资源的限制。这使得只在特定的时刻执行控制动 作的事件驱动策略成为分布式模型预测控制中的研究热点。 尽管已经取得一定的研究进展，但兼顾系统稳定性和算法可行性的低触发 策略仍有待研究，其核心原因是用于确保稳定性的 Lyapunov 函数递减原则和基 于不精确的状态预测误差保证可行性所必然带来的频繁触发问题。面向这一挑 战，本文从改变稳定性保证原则和提高预测误差精度的角度展开分布式模型预 测控制的事件驱动策略研究，具体工作包括： 1. 面向 Lyapunov 分析方法保守的触发策略设计，提出了自适应事件触发分 布式模型预测控制策略。定义了具有衰减预测时域的最优控制问题并基于 此设计了触发条件，降低了计算复杂度和触发频率，从而降低了计算和通 信负载。 2. 面向邻居信息非精确可知的触发策略设计，提出了复合事件触发分布式模 型预测控制策略，解决了在单一稳定性触发条件下频繁触发问题。设计了 与邻居系统估计信息无关的稳定性触发条件，其联合基于 Lyapunov 函数 的稳定性条件以并行触发的方式，降低了事件触发频率。 3. 面向预测模型不精确的触发策略设计，提出了基于扰动预测的自适应事件 触发分布式模型预测控制策略，提高了模型预测精度。设计了基于中心路 径的扰动预测方案和自适应触发阈值方案，降低了状态预测误差，提高了 触发阈值，显著降低了触发频率。4. 面向系统动态互联的触发策略设计，提出了滚动自触发分布式模型预测控 制策略，简化了优化问题设计，减小了状态预测误差估计的保守性。设计 了双模型最优控制问题，简化算法可行性分析的同时优化了控制性能。设 计了滚动自触发机制，增大了自触发的触发间隔，降低了计算和通信负载。 综上所述，本文对分布式模型预测控制的事件驱动策略设计和分析进行了 系统性的研究，创新地提出了对应的解决方案，推动了分布式模型预测控制的进 一步发展。

2. 基于动态信道选择的无线网络化控制系统设计和分析 郝小梅 浙江工业大学, 浙江杭州 2022 [Abs] [pdf]

   近年来，无线网络化控制系统由于其低成本、高灵活、易维护等诸多优点 已成为学术研究的热点，相关成果被广泛应用于工业控制、智能家居、智能医 疗等领域。由于无线网络化控制系统中资源有限的通信网络在不同用户中进行 共享，若能在保证控制系统性能可靠的前提下节省无线网络化控制系统所用的 通信网络资源，将能有效优化共享通信网络的资源分配和共享用户的性能提 升，相关问题已经成为当前研究的热点问题之一。 本文研究无线网络化控制系统中的通信资源节省问题，提出了一种基于动 态信道选择的网络资源调度策略。该策略可实时预测控制系统的传输需求，进 而对数据传输信道进行动态选择，最终在保证控制系统性能的同时节省了大量 的网络信道资源。本文的主要工作如下： (1) 针对与其他用户共享通信网络的无扰无线网络化控制系统，设计了基于 估计器的动态信道选择策略，在保证无扰无线网络化控制系统性能的同时节省 了大量网络信道资源。该策略的实现由控制信号估计器、信道选择器和控制器 三部分完成，其中控制信号估计器通过已知数据估计出未知的执行器实际使用 数据，帮助进行信道选择。而信道选择器利用估计器得到的控制器实际使用数 据和当前最新状态进行信道选择。最后给出了闭环系统渐近稳定的充分条件并 通过数值仿真验证了策略的有效性。 (2) 针对与其他用户共享通信网络的有扰无线网络化控制系统，设计了改进 的基于估计器的动态信道选择策略，在保证有扰无线网络化控制系统性能的同 时节省了大量网络信道资源。该策略的实现同样由控制信号估计器、信道选择 器和控制器三部分完成，其中估计器的实现引入了有界递归的思想，保证了有 界扰动下估计控制信号误差有界。同样，给出了保证系统最终一致有界的充分 条件并通过数值仿真验证了策略的有效性。

3. 室内移动机器人路径规划算法改进研究 吴芳 浙江工业大学, 浙江杭州 2022 [Abs] [pdf]

   室内移动机器人可在工业和家用等场景发挥物料搬运、服务陪伴等重要功能， 其技术发展受到了业界的广泛关注。与一般应用场景不同，室内环境通常意味着 人类用户非预期的出现及其无法事先精确获知的运动轨迹，如何在该情况下同时 保证算法的高效性和人类用户的安全成为现有路径规划算法所面临的重要挑战， 成为当前的研究热点之一。 本文针对室内环境研究并改进了移动机器人路径规划领域的两种重要基础 算法动态窗口法和人工势场法，提升了室内环境下移动机器人规划路径的效 率和安全性。主要研究工作如下： （1）提出了基于全局规划的改进型动态窗口法，解决了室内环境下机器人 同时应对动静态障碍能力较弱、障碍附近目标不可达、可能陷入局部最优区域等 技术问题。具体研究工作包括：\ding172 借助于 A*算法的全局路径规划能力，极大降 低了传统 DWA 算法陷入局部最优的可能性；\ding173 设计了障碍物运动性质判断机 制实现分类避障，提升了算法同时应对动静态障碍的可靠性，确保了室内环境中 人类用户的安全；\ding174 改进了障碍项评价子函数，解决了算法存在的障碍附近目 标不可达问题。 （2）提出了基于采样的改进人工势场法，解决了该方法存在的局部极小值 问题和目标不可达问题，进一步结合障碍位置预测提升了室内环境中路径规划的 安全性。具体研究工作包括：\ding172 提出了基于采样的改进人工势场法，通过采样 选择引力和斥力均相对较小的运动方向，解决了局部极小值问题；\ding173 通过对机 器人-障碍物和机器人-目标之间的相对距离判断来完善采样机制，解决了障碍附 近目标不可达问题；\ding174 结合障碍位置预测，实现了更加安全的机械臂路径规划。 （3）设计了基于 TIAGo 机器人的指定地点桌面物品清理实验，进一步验证 了本文所提算法在实际环境中的可行性和避障路径规划的表现。相较于对比算法， 本文所提算法能够使得规划路径长度更短、距离障碍物更远、总运动时长也更短。 具体研究工作包括：\ding172 构建了机器人任务环境地图；\ding173 利用所提出的改进型动 态窗口法实现了高效安全的 TIAGo 底盘路径规划方法；\ding174 利用所提出的改进型 人工势场法实现了高效安全的 TIAGo 机械臂路径规划方法。

4. 主动丢包的多包无线网络化控制系统的分析和设计 闫文晓 浙江工业大学, 浙江杭州 2022 [Abs] [pdf]

   随着无线通信、嵌入式计算和传感器网络等技术的快速发展，无线网络化 控制系统成为了近些年研究的热点。该类系统具有高灵活、易维护和低成本的 特点，在车联网、无人机编队等领域有广泛的应用价值。无线网络化控制系统 一个显著的特点是往往需要多个传感器采集并以无线方式传输相关数据，由于 通信网络中数据传输的不完美，这一特点引发了传统网络化控制系统不多见的 多包传输问题，需要新的方法加以解决。 本文研究多包无线网络化控制系统中的主动丢包问题，提出了一种基于预 测器的动态传输策略，该策略能够在几乎不增加无线网络信道资源占用的同时， 减少主动丢包给无线网络化控制系统带来的影响，提升系统的整体性能。具体 研究工作包括以下两个方面： (1) 针对无扰动情况下的多包无线网络化控制系统的主动丢包问题，设计了 基于优先级预测器的动态传输策略，减小了主动丢包的影响，提升了系统性能。 该策略包含优先级预测器、传输调节器和控制器三部分：优先级预测器每一时 刻预测下一时刻各传感器数据对系统稳定性的重要性，从而帮助传输调节器进 行决策；在此基础上，传输调节器设计合理的传感数据动态传输规则，降低高 优先级数据的退避时间，提高低优先级数据的退避时间；进一步设计了保证系 统稳定的控制器，并通过数值仿真验证了策略的有效性。 (2) 针对有外部扰动的多包无线网络化控制系统的主动丢包问题，改进了基 于优先级预测器的动态传输策略，使策略在有界扰动下能减少主动丢包的影响， 提高了策略的抗干扰能力。为了处理干扰，在前述 PBDT 基本设计之上，加入 了预测偏差估计器，根据历史图窗数据估计因外界扰动造成的预测器的预测偏 差，并可以检测系统的突变扰动对其进行补偿，保证策略的鲁棒性；进一步在 此改进的策略下给出了相应的 H∞控制器设计方法，并通过数值仿真验证了策略 的有效性。

patent

1. 一种基于TCP套接字的SCILAB与NS3协同仿真接口方法 赵云波, 卢帅领, 梁启鹏, and 闫文晓 2024 [Abs] [pdf]

   基于 TCP 套接字的 SCILAB 与 NS3 协同仿真接口方法，首先是 SCILAB 和 NS3 软件的安装和配置；编写 SCILAB 接口程序； NS3 内接口程序的编写； SCILAB 内接口编程；编写 SCILAB 联合仿真循环程序，设置步数变量，是循环运行仿真 的次数，设置主循环函数， XCOS 输出数据变量通过扩展程序，发送给 NS3 ，同 时接受 NS3 上次仿真的结果， 存放到文件中 并读取到 SCILAB 工作空间， 作为 XCOS 的输入数据值，启动 XCOS ， XCOS 启动后从 SCILAB 工作空间读取 NS3 发 送的值并开始仿真，将每次运行得到的延迟信息和数据包的值保留下来，结束 循环，分别画出节点的延迟分布图和系统响应图。最终实现在网络化控制系统 仿真中得到高精度的仿真结果。本发明仿真精度高，兼具开源和低成本的优点。

2. 一种基于XCOS和NS3的协同仿真时间同步方法 赵云波, 卢帅领, 郝小梅, and 梁启鹏 2024 [Abs] [pdf]

   一种基于XCOS和NS3的协同仿真时间同步方法，包括：安装NS3中协同仿真接口,在NS3中安装套接字服务端程序,定义缓冲区，缓存SCILAB同步数据; 安装SCILAB中协同仿真接口；初始化NS3仿真脚本；新建NS3仿真脚本，在脚本中定义NS3仿真模块，定义初始化函数：节点设置函数、网络拓扑建立函数、信道属性配置函数、网络设备创建函数、网络协议栈安装函数、仿真开始及结束函数，通过NS3协同仿真接口初始化函数传值完成NS3配置；NS3同步机制设计；SCILAB内XCOS控制系统模型搭建；搭建被控对象模型；搭建控制器模型；搭建执行器模型；协同仿真软件间时间同步机制实现；绘制协同仿真结果图；最终实现在网络化控制系统仿真中得到高精度的仿真结果。

3. 一种基于有扰无线网络化控制系统延时估计逼近控制方法 赵云波, 卢帅领, and 梁启鹏 2022 [Abs] [pdf]

   基于延时估计的控制策略方法，针对有扰无线网络化控制系统，在延时概 率转移矩阵未知的前提下，提出了 EBAC 控制方法。 EBAC 方法采用分段逼近的 策略，将延时概率转移矩阵的估计与控制增益相结合，使控制器增益随概率转 移概率估计的收敛而更新，有效的利用了延时信息。通过更改逼近控制器中的 控制增益更新时刻判断条件，使控制增益在有扰情况下可以持续更新，其次针 对满足分段Markov特性的延时特性，设计了数据包抖动检测模块用以检测延时 特性的突变。利用Markov跳变系统方法得到了保证系统均方最终一致有界的充 分条件，并得到了相应的控制器。最后通过一个实例仿真说明了所设计的控制 策略能在延时转移矩阵未知以及分段Markov特性下保证系统的稳定性。

4. 一种基于动态信道选择的资源调度方法 赵云波, and 郝小梅 2022 [Abs] [pdf]

   一种基于动态信道选择的资源调度方法，首先在传感器和控制器之间设计一个信道选择模块，信道选择模块根据系统模型和收到的传感数据来计算得到执行器端上一时刻使用的数据；然后信道选择模块在每个时刻可以比较传感数据和上一个时刻的执行器端使用的数据之间的误差是否小于给定阈值，如果小于给定阈值使用竞争信道传输，大于给定阈值使用非竞争信道传输数据，从而保证每个时刻的执行器端使用的数据与传感数据之间的误差小于给定阈值。最终实现在保证控制系统性能的同时尽量地减少非竞争信道的使用。

5. 一种基于多路径切换的无限制DoS攻击防护方法 赵云波, and 朱巧慧 2022 [Abs] [pdf]

   基于多路径切换的无限制DoS攻击防护方法，首先根据网络丢包率情况和系统模型确定系统可以容忍的最大丢包数，设计DoS攻击检测模块，从而得到多切换路径条件；然后执行器端记录当前传感器到控制器的连续丢包数并发送给传感器，若当前连续丢包数满足路径切换条件，则传感器和控制器切换路径传输数据，若当前连续丢包数没有满足路径切换条件，则继续检测。多路径切换防护方法通过不断检测和切换路径，可以解决无限制DoS攻击造成的连续丢包现象，从而使得系统一直保持稳定。

6. 一种基于有扰无线网络化控制系统延时估计的逼近控制策略方法 赵云波, 卢帅领, and 梁启鹏 [Abs]

   基于延时估计的控制策略方法，针对有扰无线网络化控制系统，在延时概率转移矩阵未知的前提下，提出了EBAC控制方法。EBAC方法采用分段逼近的策略，将延时概率转移矩阵的估计与控制增益相结合，使控制器增益随概率转移概率估计的收敛而更新，有效的利用了延时信息。通过更改逼近控制器中的控制增益更新时刻判断条件，使控制增益在有扰情况下可以持续更新，其次针对满足分段Markov特性的延时特性，设计了数据包抖动检测模块用以检测延时特性的突变。利用Markov跳变系统方法得到了保证系统均方最终一致有界的充分条件，并得到了相应的控制器。最后通过一个实例仿真说明了所设计的控制策略能在延时转移矩阵未知以及分段Markov特性下保证系统的稳定性。

项目人员

赵云波 卢帅领 张天浩 梁启鹏 梁秀华 王涛 许畅 谢祖浩 郝小梅 闫文晓