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A Direct/Indirect Approach to Optimal control problems 4th

A Direct/Indirect Approach to Optimal Control Problems

引用

4th international conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

作者： Bertolazzi, Enrico Biral, Francesco University of Trento Via Sommarive 9 Trento Italy

ISBN: (纸本)9783031812439

Direct methods are well known to have a large convergence rate in the solution of optimal control problems and thanks to the availability of efficient Non-Linear Programming (NLP) algorithms that are widely adopted. Additionally, it has been proved that thanks to the Covector Mapping Principle (CMP) there is essentially no distinction between direct and indirect methods when Pseudo Spectral collocation is used. In this work, inspired by CMP, a map is proposed to connect the discretized equations of the indirect method with those resulting from the direct transcription with the same trapezoidal scheme. The indirect method will benefit this new formulation since it can adopt the same regularization techniques typically implemented in direct approaches while still maintaining the explicit solution of the control as a function of the states and co-states in a bi-level optimization solution strategy. Finally, the proposed mapping is also derived for the implicit dynamics. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Optimal control systems

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CLUE: Safe Model-Based RL HVAC control Using Epistemic Uncertainty Estimation 23

CLUE: Safe Model-Based RL HVAC ControL Using Epistemic Uncer...

引用

10th ACM international conference on systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys)

作者： An, Zhiyu Ding, Xianzhong Rathee, Arya Du, Wan Univ Calif Merced Merced CA USA Univ Calif Santa Cruz Santa Cruz CA 95064 USA

ISBN: (纸本)9798400702303

Model-Based Reinforcement Learning (MBRL) has been widely studied for Heating, Ventilation, and Air Conditioning (HVAC) control in buildings. One of the fundamental problems is the large amount of data required to train a neural network for building dynamics modeling. In this paper, we developed CLUE, a safe MBRL HVAC control approach that can achieve low human comfort violation with a dynamics model trained on a small dataset. We used Gaussian Process (GP) as the building dynamics model, which provides the uncertainty of each output. The uncertainty result is then integrated into a safe HVAC control algorithm. Although GP has been studied for HVAC control, this work provides a data-efficient GP modeling method. We designed a novel meta kernel learning technique that incorporates domain knowledge from historical data of multiple buildings to set the GP kernel hyperparameters. Our method can significantly reduce the amount of data required for GP hyperparameter setting. Furthermore, we incorporate the GP-based uncertainty into a Model Predictive Path Integral (MPPI) process to find a safe, energy-efficient action for each control cycle. We generate a large number of action trajectories by the GP building dynamics model, and find the optimal trajectory by a novel MPPI objective function that considers the uncertainty of every action in all trajectories. We then execute the first action of the optimal trajectory. Extensive experiments in a simulated five-zone building show that CLUE only needs seven days of training data to provide comparable energy saving as the state-of-the-art MBRL method, but with 12.07% less comfort violations. Our code and dataset are available at https://***/ryeii/CLUE.

关键词： Epistemic uncertainty estimation Model-based reinforcement learning HVAC control Model predictive control

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Models for controlling the Structure of the Technological Core of the Reproduction System 5

Models for Controlling the Structure of the Technological Co...

引用

5th international conference on control systems, Mathematical modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Gusev, Vladislav B. V.A. Trapeznikov Institute of Control Sciences of RAS Laboratory of Smart Control Systems Moscow Russia

ISBN: (纸本)9798350309126

The presented models made it possible to combine two approaches to the structural management of the technological complex of the economy: consolidated approach - with the help of an optimization model of multi-product reproduction and local approach - with the help of a balance model of final consumption. The optimization model made it possible to build a multi-stage process for calculating the structural trajectory that brings the economic system closer to the optimal state. In the calculations, tables of resources and use of goods and services of the Russian Federation were used. It is shown that with the use of a consolidated management regime, the productivity of the Russian economy can increase significantly already at the first stages of the implementation of the plan. At the same time, the entire set of industries is automatically split into three non-overlapping groups: industries that require changes in output volumes (recipients), those that require price changes (donors), and those that do not require any changes. Financing of restructuring can be balanced by the excise tax mechanism within the framework of permissible inflation. The balance model solves the problem of material support of state programs or other needs. It allows you to assess the necessary changes in output, gross product, and maximum possible volumes of final consumption of various sectors of the economy, as well as estimates of current and equilibrium productivity. Each of these approaches requires its own mechanisms for implementation and organization of management, but when applied together, they can give a synergistic effect. © 2023 IEEE.

关键词： Cell proliferation

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Exposure-NeuS: Multi-View Head Reconstruction Using Exposure-Distorted Data

Exposure-NeuS: Multi-View Head Reconstruction Using Exposure...

引用

2024 international Annual conference on complex systems and Intelligent Science, CSIS-IAC 2024

作者： Cheng, Zhanliang Peng, Bo An, Ning School of Data Science University of Science and Technology of China Hefei China School of Mathematical Science University of Science and Technology of China Hefei China Research Institute of Mine Artificial Intelligence China Coal Research Institute Beijing100013 China State Key Laboratory of Intelligent Coal Mining and Strata Control Beijing100013 China

ISBN: (纸本)9798331504755

We propose Exposure-NeuS, a high fidelity human head reconstruction method from multi-view images, even from exposure-distorted images. Previous methods either did not reconstruct with sufficient accuracy, such as failing to reconstruct hair, or resulted in artifacts or holes in the reconstructed results due to exposure in the input data. To solve these challenging problems, we improve the original fine sampling of the model by using piecewise power function sampling to obtain sampling points closer to the real surface. And we develop a prior latent code to implicitly model factors such as environment and exposure. Experiments show that we eliminate or reduce the erroneous facial depressions and hair holes that occur in the baseline method during reconstruction. Released code is provided as follows:https://***/zhanliangOO/*** © 2024 IEEE.

关键词： Network security

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Simulation of Hydraulic control Model of Underwater Manipulator Based on Improved Genetic Algorithm

Simulation of Hydraulic Control Model of Underwater Manipula...

引用

2023 international conference on Computer Simulation and modeling, Information Security, CSMIS 2023

作者： Zhou, Mingjia Chen, Bo Sun, Yan Li, Yongbin Harbin Huade University Heilongjiang Harbin150025 China

ISBN: (纸本)9798350343724

Underwater manipulator is mainly driven by electric and oil hydraulic pressure, and it is widely used in underwater operation. The control parameters of conventional PID controller are fixed, and the control effect on nonlinear and time-varying systems is poor, so the dynamic response and steady-state accuracy of the system cannot be taken into account. In order to make full use of the dynamic performance of the manipulator, the fuzzy PID controller structure is introduced into the hydraulic control system of the underwater manipulator, and the fuzzy PID control parameters are adjusted by using the improved GA (genetic algorithm). Multi-point parallel operation mechanism is used to find the global optimal solution, and the convergence speed is fast. The mutation operator used for local search is optimized. The simulation results show that the improved GA tuning fuzzy PID control parameters has obvious advantages and faster search speed. The response speed of PID controller based on improved GA is 65.85% higher than that of conventional PID controller. The experimental results verify the feasibility of the hydraulic control model of underwater manipulator based on improved GA, and this method has certain reference significance for complex trajectory planning. © 2023 IEEE.

关键词： Genetic algorithms

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Comparisons of Decentralized Model Predictive control without Weighting Factors for Electrical Drive systems 10

Comparisons of Decentralized Model Predictive Control withou...

引用

10th IEEE international Power Electronics and Motion control conference, IPEMC 2024 ECCE Asia

作者： Xie, Haotian Wei, Yao Ke, Dongliang Yu, Xinhong Huang, Dongxiao Wang, Fengxiang Rodriguez, Jose Kennel, Ralph Heldwein, Marcelo Lobo Chinese Academy of Sciences Quanzhou Institute of Equipment Manufacturing Haixi Institutes China Universidad San Sebastian Faculty of Engineering Chile Technichal University of Munich Chair of High-Power Converter Systems Germany

ISBN: (纸本)9798350351330

Model-based predictive control (MPC) has been widely spread in both academic and industry applications, due to its inherent merits of easy conduction, excellent dynamic response as well as adapive involvement of constraints. The optimal vector is selected via optimizing the error terms in the designed optimization function of MPC. However, the design of weighting factor is still a challenging task as various control objectives are coordinated in the cost function. In this paper, comprehensive comparisons of decentralized model-based predictive control without any weighting parameters for electrical drive systems are proposed. The comparisons not only evaluate the control performance but also the algorithm complexity. First, the novel construction of cost function in the presented decentralized MPC is described. According to the abovementioned concept, a complex MPC optimization problem is separated into a combination of simpler local problems, which can be solved by each sub-task. The initial optimization for each control objective are conducted, and then generate the optimal vector. The comparative results are implemented on a pair of 2.2 kW induction machine lab- constructed experimental platform. The proposed decentralized MPC methods are aiming to obtain the improvement of control performance for a large-scale control system with multiple parameters. © 2024 IEEE.

关键词： Model predictive control

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2024 IEEE 19th international conference on the Perspective Technologies and Methods in MEMS Design, MEMSTECH 2024 - Proceedings

2024 IEEE 19th International Conference on the Perspective T...

引用

19th IEEE international conference on the Perspective Technologies and Methods in MEMS Design, MEMSTECH 2024

ISBN: (纸本)9798350378627

The proceedings contain 31 papers. The topics discussed include: Bilow – knee-prothesis study;electrodynamic modeling the motion devices of MEMS;application of bayes theory model to determine the optimal variant of technological process for production of MEMS components;the monitoring of automated platforms for testing Internet of Things devices;simulation of parameters and modes of wave propagation in electromechanical systems using methods of inverse problems theory;advanced computer-aided optimization of quartz resonator-based sensors;improvement of the control system of the robotic mobile platform;segmentation of medical images using deep learning and texture enhancement based on fractional derivative operators;modelling of the dynamic process in the microbeam of the MEMS resonators;exploring the potential of cellulose acetate membranes for precise gas permeation in microfluidic devices;and investigation of magnetic properties of cryogenically cooled electrolyte pure iron powder.

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A Reinforcement Learning Method in Cooperative Multi-Agent System for Production control System 2

A Reinforcement Learning Method in Cooperative Multi-Agent S...

引用

2nd IEEE international conference on Data Science and Network Security, ICDSNS 2024

作者： Malathy, V. Al-Jawahry, Hassan M. Madhura, G.K. Suganya, G. Rashmi, P. Sr University Department of Ece Warangal India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq Nitte Meenakshi Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India Dr. Sns Rajalakshmi College of Arts and Science Department of Computer Science Coimbatore India Inventuriz Labs Private Ltd Bengaluru India

ISBN: (纸本)9798350373110

Nowadays, in various domains including distributed control, telecommunication, robotics and economics to address the problems, Multi-Agent systems (MAS) is used. To solve with preprogrammed agent behavior complexity of many tasks of these domains making it difficult. The multi- agent systems can limit problem of control in complex system production, to solve more efficiently. However, local optimization tendencies are often shown in iterative development algorithms. So, by using reinforcement learning and considering indicators of global key performance this paper presents a new method for cooperative multi-agent system. To cooperative order agents, for the purpose of this a central deep and double deep learning module its knowledge is being transferred. From the results, subsequent reinforcement learning using memory, the order's experience is stored and increases 50% of average mean cycle. In comparison of production control conventional methods, nonlinear production system and parameters of learning interdependencies between the characteristics are investigated and the performance is evaluated. © 2024 IEEE.

关键词： Deep reinforcement learning

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Research on Interference Estimation and Tracking control of Harmonic Reducer Based on Interference Observer

Research on Interference Estimation and Tracking Control of ...

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2024 international conference on Interactive Intelligent systems and Techniques, IIST 2024

作者： Wu, Jiayi Cheng, Xiang Hunan Railway Professional Technology College School of Artificial Intelligence Zhuzhou China

ISBN: (纸本)9798350374421

As an important part of industrial robot, the high-precision operation of harmonic reducer ensures the precise action of industrial robot, and its health directly determines the running accuracy and reliability of industrial robot. In order to solve the problems of complex and abrupt interference in industrial environment, this paper first constructs the dynamic model of harmonic reducer, and then carries out estimation research on mismatched nonlinear interference, and puts forward an improved interference observer to enhance the original observer structure robustly by sliding mode. Finally, based on interference estimation, a robust tracking control strategy based on sliding mode theory is designed to ensure that harmonic deceleration can accurately track control expectations under external interference. The simulation results show that the method proposed in this paper is able to estimate the nonlinear disturbance of harmonic reducer and realize tracking control accurately. © 2024 IEEE.

关键词： Harmonic analysis

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Visuotactile Sensor Enabled Pneumatic Device Towards Compliant Oropharyngeal Swab Sampling

Visuotactile Sensor Enabled Pneumatic Device Towards Complia...

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IEEE/RSJ international conference on Intelligent Robots and systems (IROS)

作者： Li, Shoujie He, Mingshan Ding, Wenbo Ye, Linqi Wang, Xueqian Tan, Junbo Yuan, Jinqiu Zhang, Xiao-Ping Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Seoul Natl Univ Dept Mech Engn Seoul South Korea Qianyuan Inst Sci Dept Intelligent Control Hangzhou 310024 Peoples R China Sun Yat Sen Univ Affiliated Hosp 7 Clin Res Ctr Shenzhen 518107 Guangdong Peoples R China Ryerson Univ Dept Elect Comp & Biomed Engn Toronto ON M5B 2K3 Canada

ISBN: (纸本)9781665491907

Manual oropharyngeal (OP) swab sampling is an intensive and risky task. In this article, a novel OP swab sampling device of low cost and high compliance is designed by combining the visuotactile sensor and the pneumatic actuator-based gripper. Here, a concave visuotactile sensor called CoTac is first proposed to address the problems of high cost and poor reliability of traditional multi-axis force sensors. Besides, by imitating the doctor's fingers, a soft pneumatic actuator with a rigid skeleton structure is designed, which is demonstrated to be reliable and safe via finite element modeling and experiments. Furthermore, we propose a sampling method that adopts a compliant control algorithm based on the adaptive virtual force to enhance the safety and compliance of the swab sampling process. The effectiveness of the device has been verified through sampling experiments as well as in vivo tests, indicating great application potential. The cost of the device is around 30 US dollars and the total weight of the functional part is less than 0.1 kg, allowing the device to be rapidly deployed on various robotic arms.

关键词： Pneumatic actuators

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