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Optimal reduced-order interval observer design for uncertain continuous-time linear systems

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2023年第2期33卷 1043-1064页

作者： Liu, Longwen Xie, Wei Zhang, Langwen South China Univ Technol Coll Automat Sci & Technol Guangzhou Peoples R China Minist Educ Key Lab Autonomous Syst & Networked Control Guangzhou Peoples R China South China Univ Technol Unmanned Aerial Vehicle Syst Engn Technol Res Ctr Guangzhou Peoples R China Minist Educ Key Lab Syst Control & Informat Proc Shanghai Peoples R China

This article investigates the reduced-order interval observer (R-IO) design technique for continuous-time linear systems with unknown external disturbances and measurement noises. First, we propose a coupled R-IO structure with more design degrees of freedom, and it can be directly applied not only to solve the difficulty of the error system cooperativity construction but to relax the constraint on the sensor measurement noises. Second, the R-IO existence condition is derived as a set of matrix equations (MEs), and a complete solution, explicitly showing the available design parameters, to such an R-IO is further obtained by solving the MEs. Third, using the solution, an integrated optimization indicator of the R-IO performance is built as the valid selection mechanism of these parameters. Finally, the efficiency of the obtained results is illustrated through a numerical example and a practical example.

关键词： interval estimation optimization function parametric design reduced-order observer

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Experimental study of heat transfer characteristics for a refrigerator by using reverse heat loss method

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2011年第5期38卷 572-576页

作者： Sim, Jae Seong Ha, Ji Soo Keimyung Univ Dept Energy & Environm Sci Coll Environm Taegu 704701 South Korea LG Elect Refrigerator Div Chang Won Kyongnam South Korea

The present study has been carried out to predict the heat transfer characteristics of a residential refrigerator through insulation wall by using reverse heat loss method. The temperature time history characteristics were measured to achieve the steady state condition. In this experiment the steady state condition was reached at about 20 h of heating. The temperature and heat inputs were then averaged with one hour data and considered as the steady state temperature and heat input. From the measured values of temperature and heat input, one can conclude that, the temperature differences between the inside and outside of a refrigerator has a nearly linear relationship with heat input. The overall heat transfer coefficients have been derived by introducing the optimal heat loss function to analyze the heat loss characteristics. The accuracy of heat loss prediction has been checked with various experimental data and the normalized errors of the obtained result are found to be within 2.5%. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Refrigerator Reverse heat loss Overall heat transfer coefficient Insulation performance optimization function

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A robust and secured adaptive image watermarking using social group optimization

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VISUAL COMPUTER 2023年第10期39卷 4839-4854页

作者： Garg, Preeti Kishore, R. Rama Guru Gobind Singh Indraprastha Univ Univ Sch Informat Commun & Technol New Delhi India Delhi NCR KIET Grp Inst Ghaziabad India

Watermarking is the process of inserting concealed data into carrier data to authenticate the owner of the material. To achieve optimal performance, we present an intelligent system for watermarking that combines a meta-heuristic method with an embedding technique. The suggested work proposes a blind watermarking technique that embeds the watermark bits in the best location of discrete cosine transform blocks while taking advantage of the discrete wavelet transform's features. To safeguard the embedded watermark, a two-step security mechanism is used: first, the column values are shuffled using a proposed shuffling algorithm, and then the scrambled watermark is encrypted using the Arnold encryption scheme. The primary goal of any watermarking technology is to protect embedded data from various attacks while maintaining the carrier data's quality. By tailoring the embedding site for watermark encapsulation, the recommended technique achieves an acceptable balance of these two characteristics known as imperceptibility and resilience. A meta-heuristic algorithm based on human social behavior is employed to optimize the placement. The social group optimization (SGO) algorithm is a new member of the family of meta-heuristic algorithms. No attempt has been made to include the social group optimization technique into applications for watermark embedding, to our knowledge. The SGO method can assist in striking a balance between various watermarking qualities. To demonstrate the utility of the suggested method, it is compared to a variety of existing watermarking techniques. The approach presented here is a robust solution that may be applied to a wide variety of multimedia applications, including telemedicine, media distribution, and security systems.

关键词： Digital watermarking Meta-heuristic optimization optimization function Social group optimization Adaptive locations

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The optimization Route to Robotics-and Alternatives

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KUNSTLICHE INTELLIGENZ 2015年第4期29卷 379-388页

作者： Toussaint, Marc Ritter, Helge Brock, Oliver U Stuttgart Machine Learning & Robot Lab Stuttgart Germany U Bielefeld Neuroinformat Grp Bielefeld Germany TU Berlin Robot & Biol Lab Berlin Germany

Formulating problems rigorously in terms of optimization principles has become a dominating approach in the fields of machine learning and computer vision. However, the systems described in these fields are in some respects different to integrated, modular, and embodied systems, such as the ones we aim to build in robotics. While representing systems via optimality principles is a powerful approach, relying on it as the sole approach to robotics raises substantial challenges. In this article, we take this as a starting point to discuss which ways of representing problems should be best-suited for robotics. We argue that an adequate choice of system representation-e.g. via optimization principles-must allow us to reflect the structure of the problem domain. We discuss system design principles, such as modularity, redundancy, stability, and dynamic processes, and the degree to which they are compatible with the optimization stance or instead point to alternative paradigms in robotics research. This discussion, we hope, will bring attention to this important and often ignored system-level issue in the context of robotics research.

关键词： Cost function Machine Learning Optimality Principle optimization function Robotic System

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A hybrid model to overcome landslide inventory incompleteness issue for landslide susceptibility prediction

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GEOCARTO INTERNATIONAL 2024年第1期39卷

作者： Tan, Jiayao Yang, Chi Wang, Yuzhou Xiong, Hanxiang Ma, Chuanming China Univ Geosci Sch Environm Studies Wuhan Peoples R China Shanghai Jiao Tong Univ Sch Environm Sci & Engn Shanghai Peoples R China Eastern Inst Technol Eastern Inst Adv Study Ningbo Peoples R China

Landslide inventory incompleteness (LII) may significantly affect the model performance in landslide susceptibility mapping (LSM). However, traditional methods, including heuristic, statistical and deterministic models, cannot address LII issue. In this work, we introduce a novel hybrid LEO-MAHP model, blending landslide frequency, empirical adjustments, optimization functions, and multi-participated analytic hierarchy process to address it by taking Badong County as the study area. This hybrid model mitigates the drawbacks of data-heavy statistical approaches and subjective heuristic models by incorporating LII into weight determination. The findings show that the LEO-MAHP model demonstrates superior performance (AUROC = 0.809 and 0.805) over conventional statistical (AUROC = 0.714 and 0.770) and heuristic models (AUROC = 0.738 and 0.741) across different LII levels. We further discuss alternative LII solutions, proposing an updated landslide management strategy that accounts for climate change and human activities. Our findings underscore the necessity of evaluating LII before applying statistical or machine learning methods in LSM.

关键词： Hybrid model landslide susceptibility optimization function prevention and control incomplete landslide inventory

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Automatic tuning of segmentation parameters for tree crown delineation with VHR imagery

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GEOCARTO INTERNATIONAL 2021年第19期36卷 2241-2259页

作者： Sothe, Camile de Almeida, Claudia Maria Schimalski, Marcos Benedito Liesenberg, Veraldo Diaz, Pedro Achanccaray Natl Inst Space Res INPE Remote Sensing Div Sao Jose Dos Campos SP Brazil Santa Catarina State Univ UDESC Dept Forest Engn Lages SC Brazil Pontifical Catholic Univ Rio de Janeiro PUC Dept Elect Engn Rio De Janeiro RJ Brazil

In the case of tree species delineation with very high spatial resolution (VHR) images, is desirable that each segment corresponds to one individual tree crown (ITC). However, in order to have a segmentation algorithm that generates segments matching to ITCs, its parameters ought to be properly tuned. Aiming to avoid time-consuming trial-and-error procedures associated with this task, some initiatives for the automatic search of segmentation parameters have been developed, such as metaheuristic methods. The objective of this work was to test the automatic tuning of segmentation parameters of three segmentation algorithms for the delineation of ITCs belonging to a native endangered species in a subtropical forest area, comparing this method with the traditional trial-and-error approach. Two datasets (WorldView-2 and an orthoimage) and three segmentation algorithms (multiresolution, mean-shift and graph-based) were tested. For the automatic approach, a hybrid metaheuristic method was applied to accomplish the automatic search of parameters for the segmentation algorithms, while for the trial-and-error, a visual assessment was conducted for each set of parameters tested. Four supervised metrics were used to assess the quality of the segmentation results for the optimization approach and for the final set of parameters chosen in the trial-and-error approach. Results showed that none of the algorithms, datasets or approaches differ too much. The evaluation metrics values were lower, indicating that the reference ITCs polygons matched with the segmentation results. Despite the similar results, the automatic tuning of segmentation parameters proved to be a feasible alternative to reduce the subjectivity and the human effort in the choice of segmentation parameters as compared to the trial-and error approach.

关键词： Individual tree crown image segmentation object-based image analysis optimization function metaheuristic methods

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Real-time active power dispatch of virtual power plant based on distributed model predictive control

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ELECTRONICS LETTERS 2022年第23期58卷 872-875页

作者： Feng, Shuai Funding, Dongsheng Yang Zhou, Bowen Luo, Yanhong Li, Guangdi Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

With the increasing penetration of renewable energy, virtual power plants (VPP) reduce the impact on the power grid by integrating massive distributed resources for unified management. However, the optimal scheduling of a large number of distributed resources in VPP has become a new problem in recent years. Therefore, aiming at the real-time optimal scheduling problem in the optimal scheduling of virtual power plant, this letter regards the virtual power plant as a multi-agent system and proposes a novel real-time active power dispatch scheme of virtual power plant based on distributed model predictive control (DMPC), so that each agent can not only calculate its own optimization function relatively independently, but also fully refer to the neighbour information. Simulation results show the feasibility and effectiveness of the proposed method.

关键词： scheduling multiagent system power grid power generation dispatch optimization function multi-agent systems optimisation power plants virtual power plant neighbour information distributed control real-time active power dispatch scheme real-time optimal scheduling problem power engineering computing power grids predictive control renewable energy distributed model predictive control

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Adaptive drilling application uses AI to enhance on-bottom drilling performance

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JPT, Journal of Petroleum Technology 2020年第8期72卷 45-47页

作者： Jeffery, Christopher Creegan, Andrew NOV

Ever since the first commercial well was spudded, operators have looked for ways to drill wells faster without sacrificing safety or incurring huge costs. While saving time and money through efficient drilling is not a new concept, the more recent adoption of drilling optimization and automation services has certainly become one of the biggest drivers to achieving those *** the current downturn has shown limited signs of recovery, it has continued to evolve in ways never imagined, and the effects are taking their toll in every facet of the oil and gas industry. While rigs and drilling equipment can be set aside to ride out the storm, what about the drilling teams who are working on the rigs and in remote operation centers? As these teams are being removed from the field, the expectation is that many of them won’t return for a myriad of reasons. So, what happens when that experience is lost?The exodus of seasoned crews, otherwise known as the “great crew change,” has been discussed for several years, but recent conditions could expedite the process. Considering the recent shutdown of rigs and the loss of personnel, the question remains whether we will see a noticeable gap in knowledge and experience once crews return to the drilling rigs in full *** lack of individual skills can be offset over time with hands-on experience, but a drilling crew needs to operate at the highest level possible, preferably with few to no gaps in experience. To assist the drilling process, NOV’s M/D Totco division recently launched its KAIZEN intelligent drilling optimization application, which performs as an adaptive autodriller. The system features continuous learning capabilities, enabling it to provide proactive drilling dysfunction mitigation while maximizing rate of penetration (ROP) and optimizing mechanical specific energy. It also reduces human dependence in the drilling process, lowering the risk of slow or incorrect responses to drilling dysfunction. In turn, the syst

关键词： drilling equipment digital wellsite portfolio control mode artificial intelligence drilling process optimization function machine learning drilling operation adaptive drilling application control system Artificial intelligence Drilling Equipment Drilling Operations Drilling optimization Information Management and Systems

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The calibration of the partial factors for the design of a typical hypar membrane structure 60

The calibration of the partial factors for the design of a t...

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60th Anniversary Symposium of the International-Association-for-Shell-and-Spatial-Structures (IASS SYMPOSIUM) / 9th International Conference on Textile Composites and Inflatable Structures (STRUCTURAL MEMBRANES)

作者： De Smedt, Elien Mollaert, Marijke Caspeele, Robby Pyl, Lincy Vrije Univ Brussel Pl Laan 2 B-1040 Etterbeek Belgium Univ Ghent Ghent Belgium

ISBN: (纸本)9788412110104

Membrane structures are widely used for various functions, although there does not exist a unified design approach as there exists for conventional buildings (partial factor framework, Eurocode). Specific for most membrane structures is that they have doubly curved shapes, they are pre-tensioned and exhibit a non-linear structural behaviour. The current article investigates an existing calibration method to obtain the partial factors to be used for the design of a typical hypar membrane structure. The reliability analysis is performed using a First Order Second Moment method in combination with Latin Hypercube Sampling. The study is performed for the load cases snow load and wind uplift load.

关键词： hypar membrane structure reliability index optimization function Latin Hypercube Sampling

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An Improvement of Genetic Algorithm for optimization Problem 2

An Improvement of Genetic Algorithm for Optimization Problem

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International Conference on Digital Arts, Media and Technology (ICDAMT) - Digital Economy for Sustainable Growth

作者： Pravesjit, Sakkayaphop Kantawong, Krittika Univ Phayao Fac Informat & Commun Technol Phayao Thailand

ISBN: (纸本)9781509052103

This paper proposed an improvement of genetic algorithm for optimization problem. In this study, the Gaussian function is applied in crossover and mutation operators instead of traditional crossover and mutation. The algorithm is tested on five benchmark problems and compared with the self-adaptive DE algorithm, traditional differential evolution (DE) algorithm, the JDE self-adaptive algorithm and the hybrid bat algorithm with natural-inspired. The computation results illustrate that the proposed algorithm can produce optimal solutions for all functions. Comparing to the other four algorithms, the proposed algorithm provides the best results. The finding proves that the algorithm should be improved in this direction.

关键词： optimization function genetic algorithm genetic operator crossover operator mutation operator

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