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Hierarchical extended parameter estimation algorithms for finite impulse response moving average models

IFAC-PapersOnLine 2024年第14期58卷 416-421页

作者： Feng Ding Xiao Zhang Ling Xu Xingchen Liu School of Internet of Things Engineering Jiangnan University Wuxi 214122 PR China School of Microelectronics and Control Engineering Changzhou University Changzhou 213164 China College of Computer and Control Engineering Qiqihar University Qiqihar 161006 China

This paper explores some hierarchical extended parameter estimation algorithms for finite impulse response moving average (FIR-MA) model from observation data, including the hierarchical extended stochastic gradient algorithm, the hierarchical multi-innovation extended stochastic gradient algorithm, the hierarchical extended gradient algorithm, the hierarchical multi-innovation extended gradient algorithm, the hierarchical extended least squares algorithm and the hierarchical multi-innovation extended least squares algorithm. The proposed hierarchical algorithms for the FIR-MA systems can be extended to other stochastic systems with colored noises.

关键词： Recursive identification Hierarchical identification Multi-innovation identification

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Recognition of Residual Current A+6 Waveform Based on Random Forest Algorithm 6

Recognition of Residual Current A+6 Waveform Based on Random...

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6th International Conference on Frontier Technologies of Information and computer, ICFTIC 2024

作者： Zhao, Pei Wang, Xiaohui Liu, Fanyu Ou, Ziye Jia, Yunshuo State Grid Hebei Electric Power Marketing Service Center Hebei Shijiazhuang China North China Electric Power University School of Control and Computer Engineering Hebei Baoding China

ISBN: (纸本)9798331541750

In the field of power system safety protection, residual current detection technology plays a vital role, which is essential to ensure the safe and stable operation of the system. Accurate identification of the waveform of the residual current is necessary for the residual current protection device to perform the disconnect operation correctly. At present, the recognition of specific waveforms such as F, A0, A90, A135, and SDC in the A+6 waveform is not very sufficient, especially in terms of compatibility and recognition efficiency at 50Hz and 60Hz frequencies. In this study, we propose a new residual current A+6 waveform recognition technology based on a random forest algorithm, which improves recognition accuracy by selecting 13 time-domain statistical features. The experimental results show that the accuracy of the proposed method for the recognition of alternating current, F, A0, A90, A135, and SDC waveforms and their amplitudes at 50Hz and 60Hz on the experimental bench reaches 98.6% and 99.3%, respectively. In addition, the generated decision trees can be easily integrated into embedded systems, showing high practical value. © 2024 IEEE.

关键词： Random forests

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SSIG: Single-Sample Information Gain Model for Integrating Multi-Omics Data to Identify Cancer Subtypes

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Chinese Journal of Electronics 2021年第2期30卷 303-312页

作者： ZHANG Yuanyuan WANG Ziqi WANG Shudong KOU Chuanhua School of Information and Control Engineering Qingdao University of Technology College of Computer Science and Technology China University of Petroleum (East China)

Different living environments of cancer samples lead to different molecular mechanisms of cancer development, which in turn leads to different cancer subtypes. How to identify cancer subtypes is a key issue for the realization of precision medicine. With the development of high-throughput technologies, multi-omics data which can better understand different causes of cancer have emerged. However, the current methods of analyzing cancer subtypes using multi-omics data is mostly derived from population cancer sample data and ignores the differences between different cancer ***, the joint analysis of multi-omics based on a single sample may reveal more information about the differences between individual cancers. A strategy for identifying cancer subtypes is proposed based on Single-sample information gain(SSIG) which construct sample feature matrix by considering the heterogeneity of sample. Applying this strategy to current popular subtype identification methods, cancer subtypes can be identified more accurately and the mechanism of cancer can be found from the perspective of a single sample. By comparing different methods in different clustering measure, and using survival analysis, it is shown that SSIG is more suitable for cancer subtype identification than the original multi-omics data, and it is easier to mine the cancer subtype classification mechanism hidden behind the data.

关键词： identify cancer subtypes SSIG medical computing cancer subtype classification mechanism Single-sample information gain model different cancer subtypes original multiomics data genetics cancer subtype identification current popular subtype identification methods population cancer sample data different cancer samples data analysis cancer development genomics cancer sample feature matrix different molecular mechanisms different living environments bioinformatics individual cancers different clustering measure

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Possibilities of Adopting Electric Vehicles in the Agritourism Development Context 18

Possibilities of Adopting Electric Vehicles in the Agritouri...

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18th Iberian Conference on Information Systems and Technologies, CISTI 2023

作者： Samuil, Ionela Stancioiu, Loredana Ionica, Andreea Cristina Leba, Monica University of Petrosani Department of Management and Industrial Engineering Petrosani Romania University of Petrosani Engineering and Management Doctoral School Petrosani Romania University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9789893347928

In a society that is looking for ways of sustainable development, the use of electric vehicles (EVs) can be an applicable solution in different fields of activity, including the tourism industry. The current research analyzes the possibility of using Buggy EVs in a predominantly agritourism region. In this sense, with the help of STELLA Architect, dynamic modeling software, a simulation is run to determine the potential behavior of tourists who use different types of off-road vehicles and their willingness to become Buggy EV users. Based on the data obtained, an algorithm is developed to size the fleet of Buggy EVs necessary for carrying out the activity, taking into account the most important characteristics of the existing Buggy EV, namely range, charging time and price. The results obtained from the study can be used as a starting point for improving the tourist experience, by integrating the technology we are so connected to. © 2023 ITMA.

关键词： computer software

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Collaborative Optimization of Multi-regional Integrated Energy System Based on Improved Beluga Whale Optimization Algorithm

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Distributed Generation and Alternative Energy Journal 2024年第4期39卷 717-750页

作者： Liu, Ming School of Control and Computer Engineering North China Electric Power University Beijing102206 China

With the installed capacity of the renewable energy power generation is growing at a high speed, a large number of the renewable energy is connected to the grid, the energy problem has been solved to a large extent, but the ensuing problems can not be ignored, the first is the consumption of the renewable energy, which is followed by the stability problem of the power system, and a multi-regional integrated energy system (MRIES) is constructed to solve the problem. In view of the wind power uncertainty, the absorption treatment is carried out by the equipment layer and the optimization layer respectively. A hybrid energy storage system (HESS) is introduced in the equipment layer to suppress the influence of the wind power uncertainty on the system stability. A combination of the convolutional filtering algorithm, the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise algorithm and the fuzzy control algorithm is introduced in the optimization layer to develop the charging and discharging strategy of the HESS. With the strategy, the impact of the electric power fluctuations on the power system during the optimization process can be reduced largely. Then, on the basis of fully considering the energy coupling in different equipments, a collaborative optimization model of the MRIES is constructed. And the integrated demand response model considering the time-of-use electric price is introduced in the load side. Finally, the improved Beluga optimization(IBWO) algorithm is developed to optimize the model. The optimization results show that the IBWO algorithm plays a good optimization effect both in the participation of energy supply equipments and the economy, plays a collaborative optimization role in the MRIES and ensures the stability of the whole power system. © 2024 River Publishers.

关键词： Hybrid power

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Extremum Seeking and Adaptive Dynamic Programming for Distributed Feedback Optimization 63

Extremum Seeking and Adaptive Dynamic Programming for Distri...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Liu, Tong Krstic, Miroslav Jiang, Zhong-Ping New York University Control and Networks Lab Department of Electrical and Computer Engineering Tandon School of Engineering BrooklynNY11201 United States University of California Department of Mechanical and Aerospace Engineering San DiegoCA92093-0411 United States

ISBN: (纸本)9798350316339

This paper studies the distributed feedback optimization problem for linear multi-agent systems without precise knowledge of local costs and agent dynamics. The proposed solution is based on a hierarchical approach that uses upper-level coordinators to adjust reference signals toward the global optimum and lower-level controllers to regulate agents' outputs toward the reference signals. In the absence of precise information on local gradients and agent dynamics, an extremum-seeking mechanism is used to enforce a gradient descent optimization strategy, and an adaptive dynamic programming approach is taken to synthesize an internal-model-based optimal tracking controller. The whole procedure relies only on measurements of local costs and input-state data along agents' trajectories. Moreover, under appropriate conditions, the closed-loop signals are bounded and the output of the agents exponentially converges to a small neighborhood of the desired extremum. A numerical example is conducted to validate the efficacy of the proposed method. © 2024 IEEE.

关键词： Dynamic programming

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Development of a Soft Hand and Wrist Rehabilitation Robot Utilizing Lattice Structure Actuators

Development of a Soft Hand and Wrist Rehabilitation Robot Ut...

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2024 International Convention on Rehabilitation engineering and Assistive Technology and World Rehabilitation Robot Convention, i-CREATE and WRRC 2024

作者： Lai, Jianwei Song, Aiguo Zhang, Wenbin Lu, Ye Wang, Jiajin Li, Ye School of Instrument Science and Engineering Southeast University State Key Laboratory of Digital Medical Engineering Jiangsu Key Laboratory of Remote Measurement and Control Nanjing210096 China College of Computer Science and Software Engineering Hohai University Nanjing210024 China

ISBN: (纸本)9798350355123

Soft robots offer promising solutions for rehabilitation due to their inherent attributes such as suppleness, lightweight construction, and safety features. However, prevalent soft actuators face limitations in output force and bending angle, impeding their effective application in rehabilitation. This paper proposes a novel design approach employing a two-layer lattice structure actuator, comprising flexion, guiding, and extension layers. This innovative design facilitates supple and efficient bi-directional rehabilitation training for fingers and wrists. Experimental results demonstrate the efficacy of the proposed dual-layer lattice structure actuator. At an air pressure of 150 kPa, it achieves an end force of 14.88 N, marking a remarkable 906% increase compared to its single-layer counterpart. Additionally, the dual-layer structure exhibits a minimum bending radius of 2.77 cm under 60 kPa, representing a 38.5% reduction relative to the single-layer actuator. Leveraging these actuators, a hand and wrist rehabilitation robot was developed and subjected to a clinical trial involving two healthy subjects. The trial outcomes reveal significant improvements in finger grasping ability and wrist range of motion with the assistance of the rehabilitation robot. These results underscore the practical usability and effectiveness of the soft hand and wrist rehabilitation robot, thereby holding promise for enhancing patient rehabilitation outcomes. © 2024 IEEE.

关键词： Patient rehabilitation

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Load Frequency control Strategy of Interconnected Power System Based on Tube DMPC

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Distributed Generation and Alternative Energy Journal 2024年第3期39卷 635-658页

作者： Xinshan, Wang School of control and computer engineering North China Electric Power University Beijing102206 China

Solar thermal power generation shares technical characteristics with traditional thermal power generation. This enables rapid adjustment of turbine generator output to meet the demands of the power grid load for frequency modulation. However, fluctuations in light intensity lead to variations in interconnected power system parameters, posing challenges for load frequency control (LFC). In this study, we propose a Robust Distributed Model Predictive control (RDMPC) method. This method achieves system trajectory tracking by solving the nominal system optimization problem. It also flexibly adjusts the weights of different Tube models to determine the optimal control law using the standard Tube online combination with various gain values. Additionally, we incorporate the states of adjacent areas into the feedback control law to achieve effective coordination between these areas. Using MATLAB/Simulink, we simulated the power system in two areas. Compared to standard Tube DMPC, our proposed algorithm effectively mitigates the impact of light intensity, enhances adjustment speed, reduces frequency fluctuation, and demonstrates superior control effectiveness. © 2024 River Publishers.

关键词： Electric power system interconnection

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Task planning of Robotic Grasping for Deep-Container Environment Based on Dynamic Space Constraints RRTC Algorithm 20

Task planning of Robotic Grasping for Deep-Container Environ...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Xu, Yan Liu, Yaqiu Liu, Xun Zhang, Lin Li, Peibo Northeast Forestry University College of Computer and Control Engineering Harbin China Shanghai Jiao Tong University School of Mechanical Engineering Shanghai China Donghua University College of Mechanical Engineering Shanghai China

ISBN: (纸本)9798350320831

Multi-axis collaborative manipulators encounter challenges such as slow planning speed, low efficiency, and poor path quality while conducting grasping operations. This paper proposes the Dynamic Space Constraints RRTC motion planning algorithm that considers the grasping pose in the deep-container picking problem and introduces a novel method to optimize the collision-free grasping pose in compliance with environmental constraints. The paper also proposes a prior graph path generation algorithm based on the end-effector's sphere space constraint that compresses the body's search space to improve efficiency. Avoiding complicated non-convex constraint modeling required for obstacle avoidance can be achieved by modeling nonconvex sets with an obstacle-free state as the union of a finite number of convex regions. Based on the prior path, the algorithm generates a dynamic constraint manifold and uses a bidirectional search tree that employs a sliding constraint manifold for traction. The algorithm includes an adaptive step length mechanism dynamically based on the obstacle distance for higher efficiency and accuracy. Experimental results demonstrate that the Dynamic Space Constraints RRTC algorithm plans an optimized path that satisfies the constraint condition compared to traditional algorithms in terms of computation time and efficiency. © 2023 IEEE.

关键词： Motion planning

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PHOTOVOLTAIC POWER PREDICTION BASED ON IMPROVED PYRAFORMER

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2024年第1期86卷 385-398页

作者： Li, Guodong Cai, Wenhao School of Control and Computer Engineering North China Electric Power University Beijing102206 China

The stochastic and high volatility of PV power generation poses a great challenge to the operational management of the electrical grid, while precise anticipation of PV power yield can reduce the impact of its uncertainty. Hence, a photovoltaic prediction model called PDGformer, based on an improved Pyraformer model, is proposed. The encoder of the PDGformer model employs a unique dual-branch structure, wherein the local branch captures the local information of the photovoltaic power sequence, enabling the simultaneous capture of temporal and dimensional dependencies of the photovoltaic data. Conversely, the global branch captures the global information of the photovoltaic power sequence. The model's decoder incorporates an Attention mechanism to effectively integrate both local and global information and generate the final prediction results. Additionally, an MSE reweighting framework is introduced to alleviate the interference caused by abrupt changes in predictions. This framework reduces the loss caused by mutations while increasing the loss for normal states. Employing actual photovoltaic data from a specific location for illustrative analysis, the experiments demonstrate the superior performance of the proposed model compared to others, such as Pyraformer, in effectively predicting photovoltaic output power. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Forecasting

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