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5th International Scientific and Technical Conference on Mechanical Science and Technology Update, MSTU 2021

作者： Eremin, E.L. Nikiforova, L.V. Shelenok, E.A. Information and Control Systems Department Amur State University Blagoveshchensk Russia Automation and System Engineering Department Pacific National University Khabarovsk Russia

The article studies algorithms synthesis of a multiply connected system for controlling non-affine plants, the state variables of which are not available for direct measurement. It is shown that the decentralized control law constructed on the basis of the hyperstability criterion eliminates the influence of non-linearities and compensates external and parametric perturbations in the tracking multiply connected system with the required accuracy. © Published under licence by IOP Publishing Ltd.

关键词： MIMO systems

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Event-triggered learning of Euler-Lagrange systems: A Koopman operator framework

Event-triggered learning of Euler-Lagrange systems: A Koopma...

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IEEE Conference on Decision and control

作者： Kaikai Zheng Dawei Shi Shilei Li Yang Shi MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing China Department of Mechanical Engineering Faculty of Engineering University of Victoria Victoria BC Canada

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Euler-Lagrange (EL) systems represent a crucial and large class of dynamical systems, and a precise model of the true system would be beneficial in planning and tracking problems. This work aims to learn an unknown EL system using noisy measurement data to achieve improved data utilization efficiency. Specifically, for the considered EL system, a linear representation of the system is constructed using the Koopman operator, which is further characterized by sample data using Willems’ fundamental lemma. Moreover, an event-triggered learning mechanism is proposed to improve data utilization efficiency, and it is designed based on the analysis of the learning error bounds. The effectiveness of the proposed event-triggered learning approach is validated through a manipulator example.

关键词： Learning systems Event detection Manipulators Safety Planning Noise measurement Dynamical systems

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Combined Nonlinear control Algorithm for Structural Undefined Non-Affine Input Delayed Plant

Combined Nonlinear Control Algorithm for Structural Undefine...

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2021 International Russian automation Conference, RusAutoCon 2021

作者： Eremin, E.L. Nikiforova, L.V. Shelenok, E.A. Amur State University Information and Control Systems Department Blagoveshchensk Russia Pacific National University Automation and System Engineering Department Khabarovsk Russia

ISBN: (纸本)9780738131566

The article is devoted to solving the problem of the combined control law synthesis for one class of non-affine plants with a delay in the input variable. The considered plant operates under conditions of a priori parametric and structural uncertainties in the presence of permanent external noise. Only the scalar plant output is available for direct measurement. The structure of the control system includes a reference predictor and dynamic filter-corrector. The synthesis of the combined regulator is based on the use of the hyperstability criterion, and the required operation quality of the obtained system is ensured at the stage of simulation. © 2021 IEEE.

关键词： Uncertainty Regulators automation Input variables Heuristic algorithms Filtering algorithms control systems

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Boosting Explore-Exploit Behavior for Navigating Vehicle by Maintaining Informative Topological Frontier

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Liu, Qiming Cui, Xinru Liu, Zhe Wang, Hesheng Department of Automation Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

Target search in unknown environments places high demands not only on an autonomous vehicle's ability to perceive and interpret target cues, but also on its conscious of collecting these cues by active exploration. While existing navigation methods have successfully built target-driven policies by maintaining memory of explored areas, there has been a lack of focus on facilitating target-aware exploration-the informative frontier information at unexplored yet visible areas is often overlooked. In this paper, we introduce a novel topology-based memory structure, Frontier-enhanced Topological Memory (FTM), and a Hierarchical Topology Encoding and Extraction (HTEE) module, fostering the autonomous vehicle's awareness of both environmental exploration and target approach. Specifically, FTM innovatively incorporates informative ghost nodes on traditional topological map to represent unexplored yet visible regions. We leverage an online-trained implicit scene representation to estimate the positions and generate features of these ghost nodes. The HTEE then employs implicit graph convolutions and attention mechanisms to extract cognitive information from FTM, taking into account the hierarchical memory structure, target cues, and current state. Our design bolsters cognitive navigation decisions. The experiments in the high-fidelity environments, including performance tests, visualizations, and interpretability experiments, validate the effectiveness of our approach in enhancing the vehicle's exploratory behavior. The improved exploration awareness for target cue collection, in turn, enhances the success rate and path efficiency of target search. Furthermore, we demonstrate the adaptability of our algorithm in real-world physical environments. IEEE

关键词： Data mining

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive control

A Real-time Local Planner Design for Smart Wheelchairs Based...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Guanfeng Yu Han Zhang Zehao Wang Jingchuan Wang Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities.

关键词： Pedestrians Accuracy systematics Wheelchairs Estimation Predictive models Real-time systems

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K-BMPC: Derivative-based Koopman Bilinear Model Predictive control For Tractor-trailer Trajectory Tracking With Unknown Parameters

K-BMPC: Derivative-based Koopman Bilinear Model Predictive C...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Zehao Wang Han Zhang Jingchuan Wang Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Nonlinear dynamics bring difficulties to controller design for control-affine systems such as tractor-trailer vehicles, especially when the parameters in the dynamics are unknown. To address this constraint, we propose a derivative-based lifting function construction method, show that the corresponding infinite dimensional Koopman bilinear model over the lifting function is equivalent to the original control-affine system. Further, we analyze the propagation and bounds of state prediction errors caused by the truncation in derivative order. The identified finite dimensional Koopman bilinear model would serve as predictive model in the next step. Koopman Bilinear Model Predictive control (K-BMPC) is proposed to solve the trajectory tracking problem. We linearize the bilinear model around the estimation of the lifted state and control input. Then the bilinear Model Predictive control problem is approximated by a quadratic programming problem. Further, the estimation is updated at each iteration until the convergence is reached. Moreover, we implement our algorithm on a tractor-trailer system, taking into account the longitudinal and side slip effects. The open-loop simulation shows the proposed Koopman bilinear model captures the dynamics with unknown parameters and has good prediction performance. Closed-loop tracking results show the proposed K-BMPC exhibits elevated tracking precision with the commendable computational efficiency. The experimental results demonstrate the feasibility of K-BMPC.

关键词： Trajectory tracking Computational modeling Estimation Predictive models control systems Data models Nonlinear dynamical systems

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Data selection strategy in data-driven model predictive control of uncertain systems

Data selection strategy in data-driven model predictive cont...

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第34届中国过程控制会议

作者： Lingyi Yang dewei Li Department of Automation Shanghai Jiao Tong UniversityKey Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai Engineering Research Center of Intelligent Control and Management

In this paper,a novel data-driven methodology for MPC with data selection strategies is *** novel selection strategy involves two ***,we check the similarity between the current data and the past data items already existing in the data *** enables the controller to pick a set of informative data items which contain sufficient information on each direction of the signal ***,for the data items within the data oracle,we integrate multiple similar data vectors into a single vector to cut down amount of *** simulation examples displays the upgraded performance and smaller amount of calculation of selection strategies.

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Dynamics of coupled implicit and explicit opinions

arXiv

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arXiv 2023年

作者： Zhang, Qi Wang, Lin Wang, Xiaofan Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Automation School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

This paper proposes a dual opinions co-evolution model based on the dual attitudes theory in social psychology, where every individual has dual opinions of an object: implicit and explicit opinions. The implicit opinions are individuals’ inner evaluations affected by the experience, while the explicit opinions are external expressions of the evaluations and are influenced by public opinion. We theoretically analyze the dynamics of coupled dual opinions in an adversarial discussion scenario, in which two opposing groups participate in the discussion. We rigorously give a method to grade the degree of individual bias. When individuals have a slight bias, dual opinions reach a consensus, showing the phenomenon of acceptance. When individuals are moderately or even extremely biased, they will exhibit the phenomenon of outward compliance, that is, their publicly explicit opinions conform to public opinion, while implicit opinions will reach a persistent disagreement and even polarization. Our investigation indicates that dual opinions may not be monotone initially but eventually converge monotonically. Besides, we analyze the influence of parameters on the co-evolutionary process and results. Numerical simulations of the dual opinions formation process produce inward and outward conformity phenomena, namely acceptance and compliance. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamics

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Techno-economic effects of electricity market conditions in the optimal operation of hybrid power plants

Techno-economic effects of electricity market conditions in ...

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7th International Hybrid Power Plants & systems Workshop (HYB 2023)

作者： J. Martinez-Rico I. Ruiza de Argandoña E. Zulueta M. Armendia U. Fernandez-Gamiz Automation and Control Unit Tekniker Basque Research and Technology Alliance Eibar Spain System Engineering and Automation Control Department University of the Basque Country (UPV/EHU) Vitoria-Gasteiz Spain Energy Engineering Department University of the Basque Country (UPV/EHU) Vitoria-Gasteiz Spain

Hybrid power plants (HyPPs) combining different renewable energy sources with battery energy storage systems (BESSs) present multiple advantages and might become a key part of the energy transition, but the still high price of BESSs and varying market conditions could slow down the investment on them. In this paper, the optimal operation of a HyPP consisting of wind, solar photovoltaic and a BESS operating in the Iberian Electricity Market is analysed under the market scenarios between 2018 and 2022. The study reveals the significant effects of the market conditions regarding the revenues obtained by installing BESSs, but claims the need for new market mechanisms to ensure their feasibility. Moreover, a closer market study indicates that price difference rates between markets have not varied significantly, resulting in similar optimal operation strategies in the studied years.

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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IEEE International Conference on Robotics and Biomimetics

作者： Muyang Hou Zhenya Lei Haidong Hu Zhong Wang Yong Wang Le Xie Hesheng Wang Department of Automation Shanghai Jiao Tong University Shanghai China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Beijing Institute of Control Engineering Beijing China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant; on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A* which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion.

关键词： Hands Trajectory tracking Trajectory planning Service robots Stability analysis Safety Mobile robots Resource management Splines (mathematics) Trajectory optimization

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