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检索条件"任意字段=IEEE Conference on Control Technology and Applications"

共 50355 条记录，以下是101-110 订阅

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Making control in High Performance Computing for Overload Avoidance Adaptive in Time and Job Size

Making Control in High Performance Computing for Overload Av...

引用

ieee conference on control technology and applications (CCTA)

作者： Pagano, Rosa Cerf, Sophie Robu, Bogdan Guilloteau, Quentin Bleuse, Raphael Rutten, Eric Univ Grenoble Alpes INRIA CNRS Grenoble INPLIG F-38000 Grenoble France Univ Lille Cent Lille CNRS INRIAUMR CRIStAL 9189 F-59000 Lille France Univ Grenoble Alpes GIPSA Lab Grenoble INP CNRS F-38000 Grenoble France

ISBN: (纸本)9798350370959;9798350370942

The feedback control of High-Performance Computing (HPC) has been explored as an application area of control Theory, because of the high variability involved in their resource management. A regulation mechanism can allow to soundly automate the injection of small flexible jobs in a cluster. A trade-off is needed, to fill up the cluster's computing capacity while avoiding overload of e.g., the file server. In this work, we describe new results in this context, where the overload avoidance controller is made adaptive to the jobs' size, that is a time-varying unknown parameter. To do so, the original PI controller is enhanced with an online estimation algorithm that allows the controller to adapt to various working conditions, to avoid performance degradation. Parallel and robust estimation algorithms are designed, tackling the challenges of bursting and noise in the system. Validation and evaluation of the adaptive controller are performed on a large-scale experimental HPC platform, showing higher robustness than the state-of-the-art in highly varying conditions. Reproducible analysis are available at doi:10.5281/zenodo.11961696.

关键词： Adaptive control control for Computing High Performance Computing

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Combined ILC and DOB for Repetitive control with Application to Fast Tool Servo System 20

Combined ILC and DOB for Repetitive Control with Application...

引用

20th ieee/ASME International conference on Mechatronic and Embedded Systems and applications (MESA)

作者： Jing, Yajie Hou, Beibei Lin, Pengbo Lu, Shuaishuai Yan, Peng Qilu Univ Technol Sch Mech Engn Shandong Acad Sci Jinan Peoples R China Shandong Inst Mech Design & Res Jinan Peoples R China Shandong Univ Sch Mech Engn Key Lab High Efficiency & Clean Mech Manufacture Minist Educ Jinan Peoples R China

ISBN: (纸本)9798331516246;9798331516239

Fast tool servo (FTS) systems using piezoelectric technology show great promise for ultra-precise machining due to their high precision and responsiveness. However, during machining, these systems often struggle with tracking accuracy due to factors like system complexity and external disturbances. To address this, we propose a robust control method specifically for piezo-driven FTS. Our approach aims to improve tracking accuracy and disturbance rejection during machining. We use a robust repetitive control scheme with a disturbance observer (DOB) to minimize the effect of interference on tracking. However, in practice, solving the inverse model of the controlled object can introduce uncertainty. To enhance the disturbance observer's performance, we add iterative learning control (ILC). This helps refine control actions based on past errors, improving overall system performance.

关键词： FTS DOB iterative learning control

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Fuzzy Fault-Tolerant control Design for Intelligent Vehicles 19

Fuzzy Fault-Tolerant Control Design for Intelligent Vehicles

引用

ieee 19th conference on Industrial Electronics and applications (ICIEA)

作者： Yang, Weixin Pan, Juntao Song, Yanzhen Bian, Xiangyuan Zhang, Xueyuan Gao, Xulang North Minzu Univ Sch Elect & Informat Engn Yinchuan Ningxia Peoples R China

ISBN: (纸本)9798350360875;9798350360868

This study examines the development of a fault-tolerant control (FTC) algorithm for intelligent vehicles using a Takagi-Sugeno (TS) fuzzy model. The vehicle is a very intricate nonlinear system, making it challenging to design FTC algorithms. One effective option is to construct a TS fuzzy model for the vehicle's nonlinear system. This model can minimize the computing burden and accurately estimate the vehicle's state. Furthermore, the implementation of a feed-forward and feedback combination controller in the vehicle system enhances system stability, decreases response time, and enhances the reliability and efficiency of vehicle operation. The state feedback FTC algorithm is developed to regulate vehicle dynamics by employing feedback signals from the vehicle's state variables. This algorithm is validated through a high-fidelity Simulink simulation, which is used to determine the state feedback control gain for the vehicle system. The objective is to achieve fault-tolerant control of the vehicle in the event of a failure.

关键词： Intelligent vehicles TS fuzzy modeling fault-tolerant control

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Model Predictive control Design for Unlocking the Energy Flexibility of Heat Pump and Thermal Energy Storage Systems

Model Predictive Control Design for Unlocking the Energy Fle...

引用

ieee conference on control technology and applications (CCTA)

作者： Tang, Weihong Li, Yun Walker, Shalika Keviczky, Tamas Delft Univ Technol Delft Ctr Syst & Control Delft Netherlands Kropman BV Zwolle Netherlands

ISBN: (纸本)9798350370959;9798350370942

Heat pump and thermal energy storage (HPTES) systems, which are widely utilized in modern buildings for providing domestic hot water, contribute to a large share of household electricity consumption. With the increasing integration of renewable energy sources (RES) into modern power grids, demand-side management (DSM) becomes crucial for balancing power generation and consumption by adjusting end users' power consumption. This paper explores an energy flexible Model Predictive control (MPC) design for a class of HPTES systems to facilitate demand-side management. The proposed DSM strategy comprises two key components: i) flexibility assessment, and ii) flexibility exploitation. Firstly, for flexibility assessment, a tailored MPC formulation, supplemented by a set of auxiliary linear constraints, is developed to quantitatively assess the flexibility potential inherent in HPTES systems. Subsequently, in flexibility exploitation, the energy flexibility is effectively harnessed in response to feasible demand response (DR) requests, which can be formulated as a standard mixed-integer MPC problem. Numerical experiments, based on a real-world HPTES installation, are conducted to demonstrate the efficacy of the proposed design.

关键词： Predictive control systems

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control Co-Design for Electric Vehicles with Driving Cycle Synthesis Encoding Road Traffic and Driver Characteristics

Control Co-Design for Electric Vehicles with Driving Cycle S...

引用

ieee conference on control technology and applications (CCTA)

作者： Park, Seho Wang, Yebin Qiao, Hongtao Sakamoto, Yusuke Wang, Bingnan Liu, Dehong Penn State Univ Dept Mech Engn University Pk PA 16802 USA Mitsubishi Elect Res Labs MERL Cambridge MA 02139 USA MERL Cambridge MA USA Mitsubishi Electr Corp Adv Technol R&D Ctr Amagasaki Hyogo Japan

ISBN: (纸本)9798350370959;9798350370942

This paper employs the control co-design paradigm to determine optimal motor size and optimal Heating Ventilation Air Conditioning (HVAC) control for system-level optimal performance of electric vehicle. Our work is motivated by the realization that whether an electric vehicle design and its control strategy best fit consumer depends on who operates it, where and how it is operated. To this end, we first propose a novel method to synthesize a customer-specific driving cycle which encodes traffic information and driver characteristics, effectively addressing where and by whom the electric vehicle is operated;then conduct physics-based model reduction and data-driven modeling for motor sizing and HVAC control design;and apply established control co-design approaches to jointly optimize the motor size and HVAC power control for a given driving cycle, addressing how it is operated. The proposed method is validated by performing electric motor design and open-loop HVAC control in numerical simulation, showcasing that the control co-design practice leads to an appropriate combination of motor size and HVAC control and more efficient operation for the given customer-specific driving cycle.

关键词： HVAC

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Flatness-based control in successive loops of the attitude of reentry space vehicles

Flatness-based control in successive loops of the attitude o...

引用

ieee conference on control technology and applications (CCTA)

作者： Rigatos, Gerasimos Busawon, Krishna Abbaszadeh, Masoud Pomares, Jorge Gao, Zhiwei Cuccurullo, Gennaro Ind Syst Inst Unit Ind Automat Rion 26504 Greece Univ Northumbria Dept Mech Engn Newcastle NE1 8ST England Rensselaer Polytech Inst Dept ECS Engn Troy NY 12065 USA Univ Alicante Dept Syst Engn Alicante 03690 Spain Univ Northumbria Dept Elect Engn Newcastle NE1 8ST England Univ Salerno Dept Ind Engn I-84094 Fisciano Italy

ISBN: (纸本)9798350370959;9798350370942

In this article, the control problem for the multivariable and nonlinear 6-DOF dynamics of the attitude of autonomous reentry space vehicles is solved with the use of a flatness-based control approach which is implemented in successive loops. To apply this control scheme, the state-space model of the 6-DOF attitude dynamics of the autonomous reentry space vehicles is separated into two subsystems, which are connected between them through cascading loops. Each one of these subsystems can be viewed independently as a differentially flat system and control about it can be performed with inversion of its dynamics as in the case of input-output linearized flat systems. The state variables of the second subsystem become virtual control inputs for the first subsystem. In turn, exogenous control inputs are applied to the second subsystem. The global stability properties of the control method are also proven through Lyapunov stability analysis. The proposed method achieves stabilization of the attitude dynamics of the space vehicle without the need of diffeomorphisms and complicated state-space model transformations.

关键词： Attitude control

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Model Predictive control with Virtual Delayed Resonator for Constant Force Interaction of Robotic Manipulator with Environmental Surface 19

Model Predictive Control with Virtual Delayed Resonator for ...

引用

ieee 19th conference on Industrial Electronics and applications (ICIEA)

作者： Xie, Nanzhi Wang, Gang Zhang, Qi Lu, Chongji Wang, Yuanhao Beijing Univ Posts & Telecommun Sch Automat Beijing Peoples R China

ISBN: (纸本)9798350360875;9798350360868

Admittance control is considered an effective method for achieving constant force contact with a manipulator. However, the presence of unknown environmental stiffness and non-uniformity of the contact surface can adversely affect the manipulator's ability to maintain constant force contact, leading to jitter or even bouncing during the process. To address this issue, this paper introduces a novel constant force control method using Model Predictive control (MPC) with virtual delayed resonator admittance control. The virtual delayed resonator can effectively mitigate the adverse effects on the admittance controller caused by external interference during the manipulator's contact with the environment, thus reducing jitter. MPC ensures that the manipulator can quickly track the desired constant force required during contact with the environment. Finally, simulation experiments demonstrate that the virtual delayed resonator admittance control method based on MPC exhibits good robustness in constant force tracking tasks and can effectively achieve the desired constant force tracking.

关键词： Admittance control Model Predictive control (MPC) virtual delayed resonator Constant force contact Suppress jitter

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A Heuristic Informative-Path-Planning Algorithm to Map Unknown Areas and A Benchmark Solution

A Heuristic Informative-Path-Planning Algorithm to Map Unkno...

引用

ieee conference on control technology and applications (CCTA)

作者： Orisatoki, Mobolaji O. Amouzadi, Mandi Dizqah, Arash M. Univ Sussex Sch Engn & Informat Smart Vehicle Control Lab SVeCLab Brighton E Sussex England Univ Greenwich Sch Comp & Math Sci London SE10 9LS England

ISBN: (纸本)9798350370959;9798350370942

Informative path planning algorithms are of paramount importance in applications like disaster management to efficiently gather information through a priori unknown environments. This is, however, a complex problem that involves finding a globally optimal path that gathers the maximum amount of information (e.g., the largest map with a minimum travelling distance) while using partial and uncertain local measurements. This paper addresses this problem by proposing a novel heuristic algorithm that continuously estimates the potential mapping gain for different sub-areas across the partially created map, and then uses these estimations to locally navigate the robot. Furthermore, this paper presents a novel algorithm to calculate a benchmark solution, where the map is a priori known to the planar, to evaluate the efficacy of the developed heuristic algorithm over different test scenarios. The findings indicate that the efficiency of the proposed algorithm, measured in terms of the mapped area per unit of travelling distance, ranges from 70% to 80% of the benchmark solution in various test scenarios. In essence, the algorithm demonstrates the capability to generate paths that come close to the globally optimal path provided by the benchmark solution.

关键词： Non-Convex Areas Unknown Areas Coverage Path Planning Voronoi partitioning Estimation of Information

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Safety Prioritization by Iterative Feedback Linearization control for Collaborative Robots

Safety Prioritization by Iterative Feedback Linearization Co...

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ieee conference on control technology and applications (CCTA)

作者： Arab, Aliasghar Mousavi, Yashar Yu, Kaiyan Kucukdemiral, Ibrahim Beklan NYU Dept Mech & Aerosp Engn New York NY 10012 USA NCAT Dept Elect Engn Greensboro NC USA Glasgow Caledonian Univ Sch Comp Engn & Built Environm Dept Appl Sci Glasgow G4 0BA Lanark Scotland SUNY Binghamton Dept Mech Engn Binghamton NY USA

ISBN: (纸本)9798350370959;9798350370942

In today's expanding landscape of intelligent autonomous robotic systems, their applications extend far beyond industrial settings, encompassing diverse operational domains and unconfined use cases, including close collaboration with humans. This proliferation of robots in human-centric environments necessitates advanced safety assurance methods, critical for achieving both physical and psychological safety, thereby fostering societal acceptance at the scale envisaged by the industry. Safety criteria vary across contexts, and diverse regulatory and standard organizations define safety differently. This paper introduces a versatile safe iterative feedback linearization control method capable of simultaneously addressing multiple safety scenarios and dynamically adjusting their priorities based on real-time conditions. Combining classic feedback linearization synthesis with nonlinear model predictive control and introducing a safety indicator, this approach offers adaptability in safety constraint prioritization. Experimental validation on a collaborative robot arm illustrates the method's efficiency and flexibility in managing safety constraints, underscoring its promise for safe human-robot interactions.

关键词： Collaborative robots

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Research on anti-rollover intelligent suspension control based on dynamic Bayesian network 19

Research on anti-rollover intelligent suspension control bas...

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ieee 19th conference on Industrial Electronics and applications (ICIEA)

作者： He, Qingshuo Li, Yang Yi, Sha Liu, Zhuopei Zhang, Xing Zhou, Chenyu Changan Univ Sch Automobile Xian Peoples R China

ISBN: (数字)9798350360868

ISBN: (纸本)9798350360875;9798350360868

To improve the vehicle active suspension performance under varying road and operational conditions, a T-S fuzzy merged optimal control strategy is introduced, which effectively balances the control objectives related to anti-rollover capability and ride comfort performance. Moreover, the integration of Bayesian theory facilitates the construction of fuzzy membership functions and enables rollover emergency prediction. The control objective can be flexibly switched between roll stability and ride comfort based on the Bayesian network technology for calculating rollover probability, in accordance with different operational requirements. The control method is validated through double lane change test, fishhook test, and ride comfort test. It is demonstrated that the roll angle can be explicitly reduced under both stability degree and harshness degree conditions, outperforming passive suspension. Moreover, the control objective effectively translates into enhanced ride comfort performance when rollover risk is minimized.

关键词： automobile active suspension control Bayesian network rollover avoidance T-S fuzzy method

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