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Robust Model Predictive control for Signal Temporal Logic Synthesis

IFAC-PapersOnLine 2015年第27期48卷 323-328页

作者： Farahani, Samira S. Raman, Vasumathi Murray, Richard M. Department of Computing and Mathematical Sciences California Institute of Technology PasadenaCA United States Department of Control and Dynamical Systems California Institute of Technology PasadenaCA United States

Most automated systems operate in uncertain or adversarial conditions, and have to be capable of reliably reacting to changes in the environment. The focus of this paper is on automatically synthesizing reactive controllers for cyber-physical systems subject to signal temporal logic (STL) specifications. We build on recent work that encodes STL specifications as mixed integer linear constraints on the variables of a discrete-time model of the system and environment dynamics. To obtain a reactive controller, we present solutions to the worst-case model predictive control (MPC) problem using a suite of mixed integer linear programming techniques. We demonstrate the comparative effectiveness of several existing worst-case MPC techniques, when applied to the problem of control subject to temporal logic specifications; our empirical results emphasize the need to develop specialized solutions for this domain. © 2015, IFAC (International Federation of Automatic control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Temporal logic Automation Computer circuits controllers Embedded systems Hybrid systems Integer programming Logic Synthesis Model predictive control Predictive control systems Robust control Specifications Uncertain systems Comparative effectiveness Discrete time model Environment dynamics Mixed integer linear Mixed integer linear programming techniques Robust model predictive control Robust optimization Temporal logic specifications

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Poster abstract - Context-aware adaptation mechanism for smart resources: A RGBD sensor case study 13

Poster abstract - Context-aware adaptation mechanism for sma...

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13th ACM Conference on Embedded Networked Sensor Systems, SenSys 2015

作者： Munera, Eduardo Poza-Luján, Jose-Luis Posadas-Yagüe, Juan-Luis Muñoz, Manuel Blanes Noguera, Juan Fco Institute of Control Systems and Industrial Computing Universitat Politècnica de València Valencia Spain

ISBN: (纸本)9781450336314

In Distributed control Systems (DCS) the distribution of sensor data needs to be optimized in order to reduce the client process redundancy, i.e.: same sensor data processing in different clients. This paper presents an implementation of Embedded Networked Sensors as Smart Resources that allows to access to high-level information abstracting the user from low level mechanisms. The distributed services provided by Smart Resources implement selfaware adaptation mechanisms in order to suit the performance to the context. Information integrity must be also ensured during this adaptation. The Smart Resource implementation is based on a RGBD sensor. Through a set of experiments is evaluated the performance of the reconfiguration and adaptation mechanisms and detailed the influence of the data integrity according to the provided service.

关键词： Quality of service

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A two-stage vector quantization approach via self-organizing map 6

A two-stage vector quantization approach via self-organizing...

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6th International Conference on Signal Processing, ICSP 2002

作者： Xu, Lixin Liu, W.Q. Svethat, V. School of Computing Curtin University of Technology Australia Department of Automatic Control Beijing Institute of Technology China

ISBN: (纸本)0780374886

In this paper, a two-stage algorithm for vector quantization will be proposed based on selforganizing map (SOM) neural network. Firstly, a conventional self-organizing map will be modified to deal with dead codebooks in the learning process and then will be used to obtain the codebook distribution structure for a given set of input data. Secondly, subblocks will be classified based on the previous structure distribution with a prior criteria. Then the conventional LBG algorithm will be applied to these subblocks for data classification with initial values obtained via SOM. Finally, extensive simulations illustrate that the proposed two-stage algorithm is very effective. © 2002 IEEE.

关键词： Self organizing maps

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Soil-Available Potassium Content Measurement Based on Nernst Informed Neural Network With Electrical Signal

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2025年

作者： Sun, Mingchun Zhao, Rongqiang Liu, Hongfang Jin, Jing Liu, Jie Harbin Institute of Technology Faculty of Computing Harbin150001 China National Key Laboratory of Smart Farm Technologies and Systems Harbin150001 China Heilongjiang Academy of Agriculture Science Jiamusi154000 China Department of Control Science and Engineering Harbin Institute of Technology Harbin150001 China

Soil-available potassium content is essential for agricultural crop management. The electrochemical measurement method exhibits advantages of high speed, low cost, and simple operation. However, it encounters challenges, such as poor signal reproducibility, limited sample accessibility, and restrictions on measurement accuracy. To address these issues, the Nernst informed neural network (NINN)-based electrochemical measurement of soil-available potassium content is proposed. The framework for the electrochemical soil-available potassium content measurement is established. The proposed method is developed to exploit the nonlinear relationship between the electrical signal and the soil-available potassium content end-to-end with a single potassium ions-selective electrode. The NINN in the proposed method is developed to improve the measurement accuracy on the dataset with a limited number of samples by integrating Nernst mechanism into the network. The potassium-content dynamic estimation in the proposed method is developed to overcome the uncertainties of the dilution factor and influence of interfering ions. The practical measurement exhibits the mean absolute percentage error in a low range and the time within 10 min. Experimental results demonstrate that the proposed method improves the accuracy compared to purely data-driven models and reduces the electrochemical measurement costs. Furthermore, the proposed method also exhibits the superiority in terms of measurement speed;operational complexity compared to the commercial products relied on spectroscopy. The proposed method can contribute to the advancement of the measurement of soil nutrients. © 2023 IEEE.

关键词： Crops

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Geometric encoding, filtering, and visualization of genomic sequences 6

Geometric encoding, filtering, and visualization of genomic ...

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6th International Conference on Information Visualization Theory and Applications, IVAPP 2015

作者： Da Gama Leitão, Helena Cristina Saracchini, Rafael Felipe Veiga Stolfi, Jorge Institute of Computing Federal Fluminense University Niterói Brazil Department of Simulation and Control Technical Institute of Castilla y León Burgos Spain Institute of Computing State University of Campinas Campinas Brazil

ISBN: (纸本)9789897580888

This article describes a three-channel encoding of nucleotide sequences, and proper formulas for filtering and downsampling such encoded sequences for multi-scale signal analysis. With proper interpolation, the encoded sequences can be visualized as curves in three-dimensional space. The filtering uses Gaussian-like smoothing kernels, chosen so that all levels of the multi-scale pyramid (except the original curve) are practically free from aliasing artifacts and have the same degree of smoothing. With these precautions, the overall shape of the space curve is robust under small changes in the DNA sequence, such as single-point mutations, insertions, deletions, and shifts.

关键词： Visualization

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Time-in-action RL

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IET Cyber-Systems and Robotics 2019年第1期1卷 28-37页

作者： Jiangcheng Zhu Zhepei Wang Douglas Mcilwraith Chao Wu Chao Xu Yike Guo Institute of Cyber-Systems and Control Department of Control Science and EngineeringZhejiang UniversityHangzhouPeople's Republic of China Data Science Institute Department of ComputingImperial College LondonLondonUK School of Public Affairs Zhejiang UniversityHangzhouPeople's Republic of China

The authors propose a novel reinforcement learning(RL)framework,where agent behaviour is governed by traditional control *** integrated approach,called time-in-action RL,enables RL to be applicable to many real-world systems,where underlying dynamics are known in their control theoretical *** key insight to facilitate this integration is to model the explicit time function,mapping the state-action pair to the time accomplishing the action by its underlying *** their framework,they describe an action by its value(action value),and the time that it takes to perform(action time).An action-value results from the policy of RL regarding a *** time is estimated by an explicit time model learnt from the measured activities of the underlying *** value network is then trained with embedded time model to predict action *** approach is tested using a variant of Atari Pong and proved to be convergent.

关键词： action policy agent

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Expert control of Vacuum Pan Crystallization

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IEEE control Systems 1994年第5期14卷 28-34页

作者： Michal, Jan Kmínek, Milos Kmínek, Pavel Department of Computing and Control Engineering Prague Institute of Chemical Technology Technicka 5 166 28 Praha 6 Czech Republic

Vacuum pan crystallization is a process that is very difficult to control by classical means. This paper presents a method of using a rule-based expert system for the control of such a process. The structure of the expert controller for adjusting the characteristic conductivity is shown to consist of a diagnostic expert system and a discrete dynamic model that is used for conversion of semantic results into numeric output values. The expert controller was implemented in the sugar factory in Lovosice in 1993.< >

关键词： Crystallization Feeds Sugar industry Automatic control Diagnostic expert systems control systems Production facilities Crystals Solids Temperature measurement

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ChatGPT Chats on Computational Experiments:From Interactive Intelligence to Imaginative Intelligence for Design of Artificial Societies and Optimization of Foundational Models

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IEEE/CAA Journal of Automatica Sinica 2023年第6期10卷 1357-1360页

作者： Xiao Xue Xiangning Yu Fei-Yue Wang College of Intelligence and Computing Tianjin UniversityTianjin 300350China State Key Laboratory for Management and Control of Complex Systems the Institute of Automdtion of Chinese Academg of SciencesBeijing 100190China

POWERED by the rapid development of Internet,the penetration of the Internet of Things,the emergence of big data,and the rise of social media,more and more complex systems are exhibiting the characteristics of social,physical,and information *** systems are known as cyber-physicalsocial systems(CPSS)[1],[2].These CPSS face unprecedented challenges in design,analysis,management,control and integration due to their involvement with human and social factors[3],[4].To cope with this challenge,there are two main approaches to CPSS research.

关键词： Intelligence Foundation involvement

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The first Soviet seminar on control in a fuzzy environment

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Fuzzy Sets and Systems 1979年第4期2卷 349-351页

作者： Orlovsky, S.A. Shapiro, D.I. Computing Center USSR Academy of Sciences Moscow Russian Federation Institute of Automated Control Systems Moscow Russian Federation

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

arXiv

引用

arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

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