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Nonlinear control Design for an Unmanned Aerial Vehicle for Path Following

IFAC-PapersOnLine 2022年第1期55卷 592-597页

作者： Shivam Kumar Singh Abhinav Sinha Shashi Ranjan Kumar Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Mumbai India

In this work, we design a nonlinear controller for an autonomous unmanned aerial vehicle (UAV) to follow a predefined trajectory. The UAV is made to follow the desired path by driving the UAV’s relative distance to the path, and its look angle to zero. The proposed design is easy to implement as it does not need path curvature information and uses the philosophy of target pursuit to follow the predefined path. We further demonstrate the merits of the proposed method through simulations for various cases in accurately tracking straight line and curvilinear paths.

关键词： Trajectory tracking Autonomous vehicles Sliding mode control Path following Unmanned Aerial Vehicle (UAV)/Drone

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Fixed-time neuroadaptive formation control for multiple QUAVs with external disturbance

Advanced Control for Applications: Engineering and Industria...

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Advanced control for Applications: engineering and Industrial systems 2024年第3期6卷

作者： Cheng, Shuai Xin, Bin Du, Zhaofeng Chen, Jie School of Automation Beijing Institute of Technology Beijing China The National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing China The Department of Control Science and Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

This paper studies the formation control of multiple quadrotor unmanned aerial vehicle systems (MQUAVSs) with external disturbance. A new adaptive fixed-time cooperative control protocol is designed for MQUAVSs. A fixed-time command filtered compensation control technology is presented to overcome the "explosion of complexity" issue, and a new fixed-time error compensation signal is designed to compensate the filtering error, which improves the convergence speed of the system. Adaptive neural network technology is introduced to deal with unknown nonlinear functions in the system. A fixed-time stability theorem is presented for MQUAVSs to ensure that MQUAVSs can reach the predetermined formation and the formation tracking errors converge to the neighborhood of the origin in a fixed time. Finally, the effectiveness of the proposed method is verified by the formation simulation of MQUAVs. © 2024 John Wiley & Sons Ltd.

关键词： Error compensation

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Three-dimensional Nonlinear Impact Time Guidance Accounting for Autopilot Lag

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IFAC-PapersOnLine 2022年第1期55卷 26-31页

作者： Iftisam Abhinav Sinha Shashi Ranjan Kumar Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Mumbai India

In this paper, a nonlinear impact time constrained three-dimensional guidance strategy to intercept a stationary target is proposed. The guidance strategy is based on non-singular terminal sliding mode control that uses an improved time-to-go estimate in the design process, thereby provisioning for the interceptor’s large heading angle errors. Unlike existing approaches in the literature of three-dimensional terminal guidance, the proposed technique does not decouple the nonlinear three-dimensional engagement kinematics to design the guidance commands. Additionally, the proposed technique also considers the effect of autopilot whose dynamics are usually ignored. The stability of the proposed guidance strategy is certified using Lyapunov stability theory. Simulation results show the effective performance of the proposed guidance commands for various engagement conditions. The results in this paper are further backed with a comparison with an existing strategy that vindicates the superior performance of the proposed strategy.

关键词： Three-dimensional guidance Impact time Autopilot dynamics Nonlinear guidance Non-singular terminal sliding mode control Decoupled engagement kinematics

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Multi-Destination Cooperative Task Offloading in Blockchain-Based Vehicular Edge Computing Networks

Multi-Destination Cooperative Task Offloading in Blockchain-...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Lang, Ping Tian, Daxin Duan, Xuting Zhou, Jianshan State Key Lab of Intelligent Transportation System Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China School of Transportation Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798350316308

As a novel computing paradigm, the Vehicular Edge Computing (VEC) network provides an additional avenue for onboard task execution for connected and automated vehicles (CAVs) in unmanned systems. In a VEC network, CAVs can offload tasks to different external servers for execution and obtain results. However, existing task offloading studies only focus on the one-to-one offloading of onboard tasks to edge servers, ignoring the requirements of parallel task execution and security. In this paper, we propose a blockchain-based multi-destination cooperative task offloading architecture in a VEC network. Based on this architecture, we analyze the task offloading and blockchain models and formulate a multi-destination cooperative task offloading optimization problem. Finally, we compare the performance of different multi-destination task offloading methods in simulations and demonstrate the effectiveness of the proposed architecture and optimization. © 2023 IEEE.

关键词： Blockchain

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Polynomial based Impact Time and Impact Angle Constrained Guidance

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IFAC-PapersOnLine 2022年第1期55卷 486-491页

作者： Prajakta Surve Arnab Maity Shashi Ranjan Kumar Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Mumbai India

A guidance strategy is proposed in this paper that ensures near-zero miss distance along with simultaneous control over the direction and time of impact. The line-of-sight angle between the interceptor and the target is shaped as a nonlinear polynomial function of relative range between them. This polynomial function provides the desired line-of-sight orientations to achieve the mission objectives. The coefficients of the line-of-sight polynomial are obtained by subjecting it to the boundary conditions that adhere to the desired terminal constraints. A controller is designed using the nonlinear dynamic inversion control technique to track the reference flight path directions derived using the desired line-of-sight orientations. The simulation results obtained from various numerical simulations validate the efficacy of the proposed guidance law.

关键词： Impact time impact angle terminal constraints LOS shaping dynamic inversion

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Survival of Unmanned Aerial Vehicles by Luring Pursuers in Angle Constrained Interception

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IFAC-PapersOnLine 2022年第1期55卷 20-25页

作者： Naveen Kumar S Shashi Ranjan Kumar Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Mumbai India

In this paper, a sliding mode control-based cooperative guidance strategy for a team of two unmanned aerial vehicles (aircraft), which ensures their survival against pursuers, is proposed. The pursuing interceptors are assumed to employ augmented proportional navigation guidance. The cooperating aircraft maneuver in a way to lure their respective pursuers to an impact angle constrained collision. The problem of controlling impact angle is first transformed to that of tracking line-of-sight angle and its rate, and then the same is achieved by enforcing sliding mode on appropriate chosen switching surface. Furthermore, the allocation of aircraft’s lateral accelerations is performed in a way to minimize the instantaneous aerodynamic drag acting on both unmanned aerial vehicles. Numerical simulations are presented to validate the effectiveness of the proposed guidance strategy under different engagement geometries.

关键词： Cooperative guidance impact angle nonlinear guidance sliding mode control aircraft survival

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Decentralized Cooperative Guidance for Time-constrained Rendezvous with Non-Accelerating Targets

Decentralized Cooperative Guidance for Time-constrained Rend...

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control Conference (ICC), 2019 Sixth Indian

作者： Rasesh Tabiyar Abhinav Sinha Shashi Ranjan Kumar Department of Aerospace Engineering Intelligent Systems & Control Lab Indian Institute of Technology Bombay India Unmanned Systems Lab The University of Texas at San Antonio USA

This paper addresses cooperative guidance for multiple interceptors targeting fast-moving non-accelerating targets. It proposes a strategy using arbitrary time consensus to establish unanimous agreement on interceptors' time-to-go values early on. This parameter is crucial for successful simultaneous target interception. The paper introduces two salvo guidance strategies based on deviated pursuit and true proportional navigation (TPN), which are modified using a definitive consensus protocol to achieve consensus on time-to-go values. By integrating this consensus mechanism into the guidance laws, interceptors can maneuver to adjust trajectories to rendezvous with targets. The paper also emphasizes collab.rative decision-making through neighbor-to-neighbor communication to enhance overall guidance performance. Extensive numerical simulations validate the proposed approach, high-lighting its ability to achieve simultaneous target interception consistently and emphasizing the importance of cooperative time-constrained guidance for successful mission outcomes.

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Random Search Optimization Approach for Human-Robot systems Modeling

Random Search Optimization Approach for Human-Robot Systems ...

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2022 International Russian Automation Conference, RusAutoCon 2022

作者： Zaitceva, Iuliia Kuznetsov, Nikolay V. Andrievsky, Boris St. Petersburg State University Control of Comlex Systems Lab. Institute of Problems in Mechanical Engineering of Ras Applied Cybernetics Department St.Petersburg Russia

ISBN: (数字)9781665466554

ISBN: (纸本)9781665466554

Human operator behavior in manual control of any electro-mechanical system can be complex and varied. It is possible to single out human operator behavior well described by linear differential equations. It allows for studying many tasks of monotonous manual control, such as tracking a reference signal. The analysis of such a system forms the basis for understanding its stability and controllab.lity features. It is necessary to know the parameters of the human operator model for studying and designing such a system, which may depend on the parameters of the plant. This paper proposes an approach to human operator parameters calculation in manual control systems based on derivative-free optimization method. For three coefficients of the PID controller, the parameters of the human operator model were calculated using the proposed algorithm in MATlab.Simulink. The evolution of the system parameters in the process of searching for the extremum of the selected function is illustrated graphically. The proposed method can be applied as part of the robot's intelligent control in real-time. © 2022 IEEE.

关键词： Human robot interaction

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Alzheimer's Disease Detection Based on Features Level Selection for CNN-SVM Combination

Alzheimer's Disease Detection Based on Features Level Select...

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Artificial Intelligence & Green Energy (ICAIGE), IEEE International Conference on

作者： Mohamed Amine Zayene Hend Basly Fatma Ezahra Sayadi Lab. Networked Objects Control and Communication Systems National School of Engineering School of Sousse Sousse Tunisia

Neurodegenerative disease especially dementia are reported as disease that leads to death, Alzheimer's Disease (AD) is kind dementia that cause progressive and irreversible brain disorder loss which leads to death. AD shows no symptoms in its early stages which makes diagnosing it its beginning a challenge and helpful for doctors as they can slow down its progress in its early stages. Computer-aided approaches such as machine learning which come up with several techniques to detect AD by extracting features from the given image data and use them to build a classifier. Recently, a subcategory of machine learning called deep learning has widely been employed to enhance the medical diagnosis by attempting notable performance. In fact, these approaches avoid the tricky manual feature extraction using Convolutional Neural Network (CNN) considered as a reference in the field of computer vision. This paper proposes a combination of machine-deep learning technics for early diagnosis of AD from positron emission tomography (PET). We first train our CNN on PET images to extract the most relevant features, then we select the most appropriate CNN's level from where the features will be extracted, which will be feed in a second step as input to a Support Vector Machine based classifier (SVM). The proposed approach achieves notable results that exceeded the performance obtained by various existing approaches.

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Two-Stage OD Flow Prediction for Emergency in Urban Rail Transit

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IEEE Transactions on intelligent Transportation systems 2024年第1期25卷 920-928页

作者： Zhu, Guangyu Ding, Jiacun Wei, Yun Yi, Yang Xu, Sendren Sheng-Dong Wu, Edmond Q. Beijing Jiaotong University Key Lab. of Transport Industry of Big Data Application Technologies for Comprehensive Transport The Beijing Research Center of Urban Traffic Information Sensing and Service Technologies Beijing100044 China Beijing Mass Transit Railway Operation Corporation Ltd. Beijing100014 China Yangzhou University College of Information Engineering Yangzhou225127 China National Taiwan University of Science and Technology Automation and Control Center The Graduate Institute of Automation and Control Taipei106335 Taiwan Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China The Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

Urban rail transit (URT) is vulnerable to natural disasters and social emergencies including fire, storm and epidemic (such as COVID-19), and real-time origin-destination (OD) flow prediction provides URT operators with important information to ensure the safety of URT system. However, hindered by the high dimensionality of OD flow and the lack of supportive information reflecting the real-time passenger flow changes, study in this area is at the beginning stage. A novel model consisting of two stages is proposed for OD flow prediction. The first stage predicts the inflows of all stations by Long Short-Term Memory (LSTM) in real time, where the dimension is reduced compared with predicting OD flows directly. In the second stage, the notion of separation rate, namely, the proportion of inbound passengers bounding for another station, is estimated. Finally, The OD flow is predicted by multiplying the inflow and separation rate. Experiments based on Hangzhou Metro dataset show the proposed model outperforms the contrast model in weighted mean average error (WMAE) and weighted mean square error (WMSE). Results also suggest that the proposed prediction model performs better on weekdays than on weekends, and with greater accuracy on larger OD flows. © 2000-2011 IEEE.

关键词： Forecasting

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