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arXiv 2022年

作者： ul Haque, Shaan Chandak, Siddharth Chiariotti, Federico Gündüz, Deniz Popovski, Petar Department of Electrical Engineering Indian Institute of Technology Bombay India Department of Electrical Engineering Stanford University United States Department of Electronic Systems Aalborg University Denmark Department of Electrical and Electronic Engineering Imperial College London United Kingdom

The rapid development of Industrial Internet of Things (IIoT) technologies has not only enabled new applications, but also presented new challenges for reliable communication with limited resources. In this work, we define a deceptively simple novel problem that can arise in these scenarios, in which a set of sensors need to communicate a joint observation. This observation is shared by a random subset of the nodes, which need to propagate it to the rest of the network, but coordination is complex: as signaling constraints require the use of random access schemes over shared channels, each sensor needs to implicitly coordinate with others with the same observation, so that at least one of the transmissions gets through without collisions. Unlike the existing medium access control schemes, the goal here is not to maximize total goodput, but rather to make sure that the shared message gets through, regardless of the sender. The lack of any signaling, aside from an acknowledgment or lack thereof from the rest of the network, makes determining the optimal collective transmission strategy a significant challenge. We analyze this coordination problem theoretically, prove its hardness, and provide low-complexity solutions. While a low-complexity clustering-based approach is shown to provide near-optimal performance in certain special cases, for the general scenarios, we model each sensor as a multi-armed bandit (MAB), and provide a learning-based solution. Numerical results show the effectiveness of this approach in a variety of cases. Copyright © 2022, The Authors. All rights reserved.

关键词： Medium access control

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Deep learning enables early stage prediction of preterm birth using vaginal microbiota

Microbiota and Host

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Microbiota and Host 2024年第1期2卷

作者： Kaushik Karambelkar Mayank Baranwal Data and Decision Sciences Tata Consultancy Services Ltd. Thane Maharashtra India Systems and Control Engineering Indian Institute of Technology Bombay Mumbai Maharashtra India

Graphical abstract Abstract Objective Preterm birth (PTB) is one of the leading issues concerning infant health and is a problem that plagues all parts of the world. Vaginal microbial communities have recently garnered attention in the context of PTB; however, the vaginal microbiome varies greatly from individual to individual, and this variation is more pronounced in racially, ethnically, and geographically diverse populations. Additionally, microbial communities have been reported to evolve during the duration of the pregnancy, and capturing such a signature may require higher, more complex modeling paradigms. In this study, we develop a neural controlled differential equation (CDE)-based framework for identifying early PTBs in racially diverse cohorts from irregularly sampled vaginal microbial abundance data. Methods We obtained relative abundances of microbial species within vaginal microbiota using 16S rRNA sequences obtained from vaginal swabs at various stages of pregnancy. We employed a recently introduced deep learning paradigm known as ‘neural CDEs’ to predict PTBs. This method, previously unexplored, analyzes irregularly sampled microbial abundance profiles in a time-series format. Results Our framework is able to identify signatures in the temporally evolving vaginal microbiome during trimester 2 and can predict incidences of PTB (mean test set ROC–AUC = 0.81, accuracy = 0.75, F1 score = 0.71) significantly better than traditional ML classifiers, thus enabling effective early-stage PTB risk assessment. Conclusion and significance Our method is able to differentiate between term and preterm outcomes with a substantial accuracy, despite being trained using irregularly sampled microbial abundance profiles, thus overcoming the limitations of traditional time-series modeling methods.

关键词： preterm birth deep learning vaginal microbiome time-series modeling

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Three-Dimensional Finite-time Suboptimal Nonlinear Impact Angle Guidance

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IFAC-PapersOnLine 2020年第1期53卷 252-257页

作者： Rohit V. Nanavati Shashi Ranjan Kumar Arnab Maity Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Powai Mumbai 400076 India

Interceptor guidance strategies are crucial in efficiently achieving desired terminal objectives. In this paper, a guidance strategy is proposed for interception of targets at pre-specified impact angle within finite time, by an interceptor in three dimensional space. The impact angle is defined as the azimuth and elevation of line-of-sight in the inertia reference frame, at interception. A suboptimal nonlinear guidance law is derived using the finite-time state dependent Riccati equation technique, for coupled engagement dynamics. The performance of the proposed guidance is tested for stationary and constant velocity targets using numerical simulations.

关键词： Guidance impact angle non-maneuvering targets three-dimensional engagements

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Transient and Asymptotic Properties of Robust Adaptive controllers in the Presence of Non-Coercive Lyapunov Functions

Transient and Asymptotic Properties of Robust Adaptive Contr...

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IEEE Conference on Decision and control

作者： Aditya A. Paranjape Vivek Natarajan Supratim Ghosh TCS Research Imperial College London Systems and Control Engineering Group Indian Institute of Technology Bombay Mumbai India TCS Research Tata Consultancy Services Limited India

ISBN: (纸本)9781665436601

Adaptive control architectures often make use of Lyapunov functions to design adaptive laws. We are specifically interested in adaptive control methods, such as the well-known ${{\mathcal{L}}_1}$ adaptive architecture, which employ a parameter observer for this purpose. In such architectures, the observation error plays a critical role in determining analytical bounds on the tracking error as well as robustness. In this paper, we show how the non-existence of coercive Lyapunov operators can impact the analytical bounds, and with it the performance and the robustness of such adaptive systems.

关键词： Transient response Conferences Coercive force Observers Robustness Closed loop systems Adaptive control

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Real-time gesture control UAV with a low resource framework

Real-time gesture control UAV with a low resource framework

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2021 International Symposium of Asian control Association on Intelligent Robotics and Industrial Automation, IRIA 2021

作者： Bhat, Manohar Mahto, Gopikishan Kesaria, Smit Femandes, Vikrant Arya, Kavi BMS College of Engineering Dept. of Electrical and Electronics Bangalore560019 India UPU Government Polytechnic Dept. of Computer Science and Engg. Durg491001 India Indian Institute of Technology Dept. of Systems and Control Mumbai400076 India Indian Institute of Technology Dept. of Computer Science and Engg. Mumbai400076 India

ISBN: (纸本)9781665433235

This study showcases a low-resource framework that enables people with no technical know-how to interact with drones, it also explores the capabilities of 2D- computer vision and deep learning techniques for gesture based interface systems on a low-cost micro drone with an onboard RGB camera. This Human-Robot Interaction system processes the real-time human pose to allow a user to command the drone, i.e., by providing direction to move and execute actions. A linear PD controller and image processing techniques are implemented to track humans whilst maintaining a safe distance from the user by perceiving depth information through pose estimation. We incorporated the gesture recognition results into a drone using the Robot Operating System (ROS) and evaluated system performance indoor and outdoor. This low computation framework can be applied further to control robotic arms or mobile robots. © 2021 IEEE.

关键词： Drones

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Novel min-max reformulations of linear inverse problems

arXiv

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arXiv 2020年

作者： Sheriff, Mohammed Rayyan Chatterjee, Debasish Systems & Control Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India

In this article we dwell into the class of so called ill-posed Linear Inverse Problems (LIP) which simply refers to the task of recovering the entire signal from its relatively few random linear measurements. Such problems arise in variety of settings with applications ranging from medical image processing, recommender systems, etc. We propose a slightly generalised version of the error constrained linear inverse problem and obtain a novel and equivalent convex-concave min-max reformulation by providing an exposition to its convex geometry. Saddle points of the min-max problem are completely characterised in terms of a solution to the LIP, and vice versa. Applying simple saddle point seeking ascend-descent type algorithms to solve the min-max problems provides novel and simple algorithms to find a solution to the LIP. Moreover, reformulation of an LIP as the min-max problem provided in this article is crucial in developing methods to solve the dictionary learning problem with almost sure recovery constraints. Copyright © 2020, The Authors. All rights reserved.

关键词： Differential equations

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Deviated Pursuit based Cooperative Simultaneous Interception against Moving Targets

Deviated Pursuit based Cooperative Simultaneous Interception...

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American control Conference

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

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

This work focuses on achieving cooperative simultaneous interception against moving targets using the concepts of deviated pursuit guidance strategy. Unlike most existing salvo guidance strategies which use estimates of time-to-go, based on proportional navigation guidance, the present strategy uses exact expression for time-to-go to ensure simultaneous interception. The guidance command is derived considering nonlinear engagement kinematics. Weighted consensus in time-to-go over a pseudo-undirected graph is used to intercept a moving target cooperatively. It has been shown that through a judicious choice of these weights, the achievable set of interception times expands. Simulations are provided to vindicate the effectiveness of the proposed strategy.

关键词： Deviated pursuit Cooperative control Salvo Moving targets Consensus Cooperative guidance coordinated control interceptions Guidance Moving Concurrency

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Residual Life Prediction in the Presence of Human Error Using Machine Learning

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IFAC-PapersOnLine 2020年第3期53卷 119-124页

作者： Ram S. Mohril Bhupendra S. Solanki Makarand S. Kulkarni Bhupesh K. Lad Industrial and Systems Engineering Discipline of Mechanical Engineering Indian Institute of Technology Indore India Department of Mechanical Engineering Indian Institute of Technology Bombay India

Accurate maintenance decision making is important for military equipment. Extremely demanding situations like limited time availability for maintenance during the war escalate the possibility of human errors in the maintenance of such equipment. Human errors in maintenance negatively impact the life of the systems. Human Reliability Analysis (HRA) methodologies have evolved to systematically quantify the human error in terms of Human Error Probability (HEP). However, the exact effect of the human error on the life of the component is unknown yet. In the presence of the diverse operating profiles for military equipment, estimating such effects becomes a complex and mathematically challenging problem to be handled by the conventional statistical techniques. This paper presents a machine learning approach to estimate the residual life of a component by incorporating the effect of human error in maintenance. Based on the nature of the maintenance data, a decision tree based boosted ensemble machine learning model is developed which predicts the Remaining Useful Life (RUL) of the component while considering error induced by maintenance personnel during its maintenance. The developed model is illustrated in the decision-making of replacement of a component in a mission critical military system in pre-mission maintenance break.

关键词： Human Reliability Human error in maintenance Machine Learning

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Rigid Body Geometric Attitude Estimator using Multi-rate Sensors

Rigid Body Geometric Attitude Estimator using Multi-rate Sen...

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IEEE Conference on Decision and control

作者： Maulik Bhatt Srikant Sukumar Amit K. Sanyal Aerospace Engineering Indian Institute of Technology Bombay India Systems and Control Engineering Indian Institute of Technology Bombay India Mechanical and Aerospace Engineering Syracuse University Syracuse NY USA

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

A geometric estimator is proposed for the rigid body attitude under multi-rate measurements using discrete-time Lyapunov stability analysis in this work. The angular velocity measurements are assumed to be sampled at a higher rate compared to the attitude. The attitude determination problem from two or more vector measurements in the body-fixed frame is formulated as Wahba's problem. In the case when measurements are absent, a discrete-time model for attitude kinematics is assumed in order to propagate the measurements. A discrete-time Lyapunov function is constructed as the sum of a kinetic energy-like term that is quadratic in the angular velocity estimation error and an artificial potential energy-like term obtained from Wahba's cost function. A filtering scheme is obtained by discrete-time stability analysis using a suitable Lyapunov function. The analysis shows that the filtering scheme is asymptotically stable in the absence of measurement noise and the domain of convergence is almost global. For a realistic evaluation of the scheme, numerical experiments are conducted with inputs corrupted by bounded measurement noise. Simulation results exhibit convergence of the estimated states to a bounded neighborhood of the actual states.

关键词： Position measurement Velocity measurement Estimation Time measurement Measurement uncertainty Noise measurement Angular velocity

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Three-Dimensional Nonlinear Impact Time Guidance for Stationary Targets

Three-Dimensional Nonlinear Impact Time Guidance for Station...

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American control Conference

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

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

This work addresses the problem of designing an impact time constrained guidance strategy for three-dimensional engagements, without decoupling the engagement dynamics in two mutually orthogonal planes. The guidance command is derived while considering nonlinear engagement dynamics, and with a time-to-go prediction that accounts for the interceptor's heading error. Power rate reaching law is used while designing sliding mode guidance strategy, since this law offers inherent robustness, smooth control and finite-time convergence to the sliding manifold. Further, the interceptor lateral acceleration components are obtained using a control allocation technique, that minimizes the instantaneous lateral acceleration, which aids in minimizing the total drag during interceptor's flight. Conditions for the interceptor to reach the collision course are derived and analyses are presented. Finally, simulations are provided to demonstrate the efficacy of the proposed guidance scheme.

关键词： Three-dimensional guidance coupled engagement dynamics impact time sliding mode control nonlinear guidance Variable structure systems 3-dimensional guidance collision course Guidance Transverse acceleration

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