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检索条件"任意字段=International Conference on Complex Systems: Control and Modeling Problems"

共 12259 条记录，以下是1431-1440 订阅

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Fast Probabilistic Policy Reuse via Reward Function Fitting

Fast Probabilistic Policy Reuse via Reward Function Fitting

引用

IEEE international conference on Fuzzy systems (FUZZ-IEEE) / IEEE World Congress on Computational Intelligence (IEEE WCCI) / international Joint conference on Neural Networks (IJCNN) / IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Liu, Jinmei Wang, Zhi Chen, Chunlin Nanjing Univ Dept Control & Syst Engn Nanjing Peoples R China

ISBN: (数字)9781728186719

ISBN: (纸本)9781728186719

Transfer learning has shown great potential to accelerate reinforcement learning (RL) by utilizing prior knowledge of relevant task that has been learned in the past. Policy Reuse Q-learning (PRQL) is a general policy transfer framework, which speeds up the learning process of the target task by probabilistically reusing source policies from the policy library. In this paper, we propose an improved PRQL method to achieve more fast probabilistic policy reuse in deep reinforcement learning (DRL). First, we extend the basic PRQL algorithm to DRL, proposing a probability policy reuse algorithm that builds on DRL to solve more complex problems. Second, PRQL algorithms usually use a metric based on the average gain to measure the similarity between tasks. However, it contains very limited information and must be delayed until the end of an episode to update, which is inefficient. Instead, we propose a new metric based on fitting the reward function, which can make the agent converge to the most suitable reuse policy more quickly and accurately. We demonstrate the detection accuracy, received cumulative reward, and speed of convergence of our method in three complex Markov tasks. Experimental results show that our method can consistently achieve efficient policy transfer in these tasks.

关键词： Q-learning Fitting Neural networks Transfer learning Markov processes Gain measurement Probabilistic logic

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Research on Real-Time Tuning of PID Parameters Based on Fuzzy control

Research on Real-Time Tuning of PID Parameters Based on Fuzz...

引用

Image Processing and Computer Applications (ICIPCA), IEEE international conference on

作者： Weixu Sun Tianjin University of Commerce Tianjin China

ISBN: (数字)9798350360240

ISBN: (纸本)9798350384161

A strategy for correcting PID parameters in real time for fuzzy control is proposed for the problem of the difficulty of correcting traditional PID control parameters. Exploring the effect of three PID control parameters on the control's quality was the initial step. Next, this paper imports the fuzzy control strategy and creates the fuzzy controller. PID parameters are adjusted in real time by fuzzy inference, fuzzy inference, knowledge base, non-fuzzy. Finally, an experimental comparison between traditional and fuzzy PID was made using Matlab simulation experiments. Test results showed that the fuzzy PID algorithm significantly reduces overclock response time compared to traditional PID algorithms, with a 20% response time reduction and a 10% overclock reduction. Fuzzy PID is a more ideal and efficient control method thanks to its excellent performance and adaptability to the control problems of complex systems.

关键词： Fuzzy logic Fuzzy control PI control Velocity control Real-time systems Inference algorithms Timing PD control Time factors Clocks

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Event-Triggered Decentralized Stabilization for State-Constrained Nonlinear Interconnected systems Using Adaptive Dynamic Programming

Event-Triggered Decentralized Stabilization for State-Constr...

引用

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

作者： Wenqian Du Guoling Yuan Mingduo Lin Bo Zhao Kuoyong Yu Qiao Lin School of Systems Science Beijing Normal University Beijing China Beijing National Innovation Institute of Lightweight Ltd. Beijing China University of Nottingham Ningbo China Ningbo China

ISBN: (数字)9798331504755

ISBN: (纸本)9798331504762

In this paper, an event-triggered decentralized stabilization method based on adaptive dynamic programming (ADP) is proposed for nonlinear interconnected systems with constant-valued state constraints. By introducing a barrier function for coordinate transformation, the original system with state constraints is transformed into an unconstrained form. Then, with the developed cost functions for auxiliary subsystems, the decentralized stabilization problem of interconnected systems is transformed into a series of optimal control problems. Here-after, to obtain the event-triggered optimal control policies, the local policy iteration algorithm is investigated to solve the event-triggered Hamilton-Jacobi-Bellman equations (HJBEs) for auxiliary subsystems. The local critic neural networks (NNs) are employed to approximate the cost functions. Furthermore, the closed-loop nonlinear interconnected system and the weight estimation errors of local critic NNs are guaranteed to be uniformly ultimately bounded by a set of developed decentralized stabilizing policies. Finally, a numerical example is employed to validate the effectiveness of the proposed method.

关键词： Estimation error Adaptive systems Event detection Simulation Optimal control Interconnected systems Artificial neural networks Cost function Approximation algorithms Dynamic programming

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LADRC Vector control for PMSM under High Speed and Low Carrier Ratio

LADRC Vector Control for PMSM under High Speed and Low Carri...

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international conference on Power and Energy Technology (ICPET)

作者： Hanshu Zhao Qiang Yang College of Electrical Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350375855

ISBN: (纸本)9798350375862

Unmanned Aerial Vehicles (UAVs) can use power series axis Permanent Magnet Synchronous Motors (PMSMs) to power onboard equipment, allowing the motors to operate under high-speed and low-carrier-ratio conditions. At this point, there will be problems such as fast response and complex system sensitivity, resulting in poor performance of many control methods applied at low speeds. Currently, the conventional PI control method is commonly used. To find alternative methods to traditional PI control, it is proposed to apply Linear Active Disturbance Rejection control (LADRC) to high-speed and low-carrier-ratio PMSM. In this paper, an equivalent LADRC controller to the PI controller is obtained and introduced into the UAV power system through parameter derivation and calculation. The proposed solution is assessed through simulation experiments and the result demonstrates that the proposed method can achieve the same or even better performance as the PI controller, which provides a new control method for high-speed and low-carrier-ratio PMSM.

关键词： Robust control PI control Sensitivity Autonomous aerial vehicles Permanent magnet motors Power systems complex systems Machine vector control

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AI-Based modeling and control of Robotic systems: A Brief Tutorial 3

AI-Based Modeling and Control of Robotic Systems: A Brief Tu...

引用

3rd international conference on Robotics and Computer Vision, ICRCV 2021

作者： Raina, Deepak Saha, Subir Kumar Indian Institute of Technology Mechanical Engineering Department Delhi India

ISBN: (纸本)9781665436281

Accurate modeling and control of robotic systems are often critical to perform complex manipulation tasks. Artificial Intelligence (AI) based approaches have gained widespread popularity to deal with task complexity and uncertainty. This paper gives a detailed overview and tutorial of AI-based approaches for modeling and control of robotic systems. We provide an easy-to-understand explanation of the key AI-based techniques and demonstrate learning an inverse dynamics model and target reaching controller for a 2-link robotic manipulator using state-of-the-art AI-based methods. The experimental results present a thorough analysis of AI-based techniques and validate their advantages over conventional methods. The code used for the examples has also been made open-source for the research community on this link: https://***/ai-modeling-control. Thus, this paper aims to become a starting point for researchers interested in developing and implementing AI-based methods for robot modeling and control. © 2021 IEEE.

关键词： Reinforcement learning

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Isolated zones and granulation of complex network systems 12

Isolated zones and granulation of complex network systems

引用

12th IEEE international conference on Electronics and Information Technologies, ELIT 2021

作者： Polishchuk, Olexandr Laboratory of Modeling and Optimization of Complex Systems Pidstryhach Institute for Applied Problems of Mechanics and Mathematics National Academy of Sciences of Ukraine Lviv Ukraine

ISBN: (纸本)9781665442961

The problem of blocking certain areas of network systems and their boundary case, which is the granulation of network to a set of isolated zones, is investigated in the article. The losses that await the system due to blocking of its separate components are determined, and method for finding alternative ways of flow motion bypassing the isolated zone of network are proposed. The granulation process of the network system is reflected as a temporal network and the losses that await the system during the deployment of such processes are calculated. © 2021 IEEE.

关键词： complex networks

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An Enhanced Artificial Bee Colony Algorithm Based on Elimination History and Elite Correction

An Enhanced Artificial Bee Colony Algorithm Based on Elimina...

引用

Data-driven Optimization of complex systems (DOCS), international conference on

作者： Yingduo Lei Haibo Yu Qinna Zhu Jianchao Zeng School of Electrical and Control Engineering North University of China Taiyuan China School of Computer Science and Technology North University of China Taiyuan China

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

Artificial bee colony (ABC) algorithm is often challenged by slow convergence, poor accuracy, and premature convergence in handling complex medium-scale optimization problems, due to its biased search equation and the high assimilation rate of bees within the colony. To trade off the ABC for global exploration and local exploitation of complex problem landscapes, this paper proposes an enhanced ABC based on elimination history and elite correction (HeCABC). Given the bias effects of the superior solutions and the historical inferior solutions eliminated on the search behavior of ABC, HeCABC separately formulates an exploration equation oriented by the historically eliminated inferior solutions and an exploitation equation upon multi-elite information fusion for employed bees and onlook bees, to regulate their exploration and exploitation intensity of the solution space. Meanwhile, HeCABC couples an elite correction strategy for fine-tuning the quality of the elites based on the update signal of these elites within the colony. HeCABC is experimented on various complex CEC 2014 test functions of 30 dimensions. The experimental results showcase its superior performance over five state-of-the-art ABC variants and two advanced swarm optimizers.

关键词： Accuracy Merging Artificial bee colony algorithm Search problems Robustness History Particle swarm optimization complex systems Optimization Convergence

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Safety-Oriented Train control systems Monitoring in Smart Railway Transportation: A Review 4

Safety-Oriented Train Control Systems Monitoring in Smart Ra...

引用

4th international conference on Pattern Analysis and Intelligent systems, PAIS 2022

作者： Zamouche, Djamila Aissani, Sofiane Omar, Mawloud Saad, Narimane Sciences Exactes Univ. Lab. d'Informatique Mé Dicale Faculté Bejaia06000 Algeria Université Bretagne Sud Irisa Laboratory Vannes56000 France

ISBN: (数字)9781665461610

ISBN: (纸本)9781665461610

Safety in railway transportation is becoming urgent due to a large number of accidents and its severe socio-economic impact on a global scale. Currently, various smart train control systems are being developed and these are enhancing the intelligence of individual train operation control. However, this in turn raises the complexity level and the control task would be even more complex. Furthermore, due to increased train's speed, abnormal interactions between train and control system could occur, which gives a sharp increase to serious accidents. Therefore, the systems' operation must be monitored continu-ously during the train's movement to check the correctness of its own behavior while generating control commands. In this study, we conduct a survey based on relevant and recent safety monitoring approaches proposed in the literature to get an insight into the state-of-the-art of the key problems of operation safety of train control systems. © 2022 IEEE.

关键词： Railroads

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Practical Explicit-time Stabilization of Multi-agent control systems with Proportional Feedback Design

Practical Explicit-time Stabilization of Multi-agent Control...

引用

IEEE international conference on Unmanned systems (ICUS)

作者： Wen Yan Tao Zhao Edmond Q. Wu College of Electrical Engineering Sichuan University Chengdu China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

The more complex nonlinear feedback in the design of controller for multi-agent systems (MASs), the more chattering is likely to occur in the control input. However, it is difficult for the existing methods to achieve fixed-time control only through linear proportional feedback. For solving this problem, a novel explicit-time proportional control method is proposed for MASs. It can achieve the practical conditionally fixed-time stability of system. Firstly, a practical conditionally fixed-time stable system is proposed by a special proportional function. Then, a nominal controller is designed based on this stability system, which is called as practical explicit-time stabilization. In the end, the proposed method is applied to MASs, which makes this control system error converge to a predefined neighborhood of zero within an explicit time. Compared with the existing predefined-time back-stepping control methods, the smoothness of control input is improved by solving the problems of singularity and high gain. Theoretical analysis and simulation verify the main results.

关键词： Visualization Accuracy Proportional control Autonomous systems Human-machine systems Stability analysis Transient analysis Robots Multi-agent systems

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Research on Structure Design and control Method of Underwater Exploration Robot 7

Research on Structure Design and Control Method of Underwate...

引用

7th international conference on Intelligent, Interactive systems and Applications, IISA2022

作者： Cao, Lijing Kong, Tengguang Zhou, Mei Shandong Xiehe University Shandong Province Jinan250109 China Shandong Jianzhu University Shandong Province Jinan250101 China

For the sake of complete the detection of complex underwater environment in the engineering construction, this paper designs the structure of the underwater exploration robot according to the actual requirements of the project, and proposes a control method of the underwater exploration robot using neural network to improve the PID control ***, the overall structure and control system layout of underwater exploration robot are designed and planned according to the design ***, aiming at the problems of complex parameter setting and poor real-time performance of system parameters in traditional control methods, the automatic learning characteristics of feedforward neural network and PID controller are combined to realize the online alter of PID control unit ***, according to the above method, a PID controller with automatic learning characteristics is designed to control the underwater exploration robot, which can achieve the optimal parameter combination of the underwater exploration robot's motion control, and improve its poor adaptability in underwater motion. © 2022 The Authors. Published by Elsevier B.V.

关键词： Three term control systems

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