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10th Indian control Conference, ICC 2024

作者： Buriuly, Somnath Vachhani, Leena The Center of Excellence in Oil Gas and Energy IIT Bombay India Systems and Control Engineering IIT Bombay India

ISBN: (纸本)9798331517212

Industrial problems, like pipeline inspection and railway track geometry inspection inside tunnels, require accurate offline estimation of the state trajectories, to determine the infrastructure parameters, say pipeline GPS coordinates, rail-track’s attitude and placement, etc. These problems are cursed with loss of observability due to the unavailability of localization data, like GPS, inside pipelines and tunnels. In addition, the states at the start and end of the recorded data are observable but not accurately or entirely known. Furthermore, a deviation is observed in the initial calibration of the Inertial Measurement Unit (IMU) sensors, and hence the recorded data are approximated sensor readings. Since the accuracy of these estimated outcomes impacts the maintenance cost of the infrastructure, it is essential to obtain the best possible estimate from the offline available sensor data. In this work, we propose an optimization-based solution to estimate the entire trajectory and self-calibrate the sensor readings, simultaneously. In particular, we formulate an offline state trajectory estimation problem with self-calibration features for the sensor readings, compute the gradients for the decisions, and propose a Lagrangian-based gradient descent algorithm. We compare the results with the state-of-the-art Extended Kalman Filter and show improvement in the mean square error values of the estimates. © 2024 IEEE.

关键词： Trajectories

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Adaptive Continuous Terminal Sliding Mode control for Unmanned Aerial Vehicle 10

Adaptive Continuous Terminal Sliding Mode Control for Unmann...

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10th Indian control Conference, ICC 2024

作者： Kumar, Sunil Yesmin, Asifa Sinha, Arpita Guha, Anirban TIH Foundation for IoT and IoE Indian Institute of Technology Bombay Mumbai India IDP in Systems and Control Engineering Indian Institute of Technology Bombay Mumbai India Department of Mechanical Engineering Indian Institute of Technology Bombay Mumbai India

ISBN: (纸本)9798331517212

This paper introduces an improved control strategy for tracking the altitude and attitude of the quadcopter unmanned aerial vehicle (UAV) in the presence of external disturbance, known as adaptive super-twisting terminal sliding mode control (AST-TSMC). This approach ensures finite-time convergence of the sliding variable and error trajectories using a real second-order sliding mode. An adaptive super-twisting approach is incorporated to reduce the reliance on the upper bound of the unknown disturbance and achieve continuous control. A nonlinear sliding surface is designed to ensure the finite time convergence of the sliding variable and the tracking error. The Lyapunov-based stability analysis is presented to confirm the finite-time convergence. Comparative simulation results of AST-TSMC, ST-TSMC, and TSMC are presented to demonstrate the strategy’s performance. The effectiveness of the proposed approach is validated through MATLAB simulation results. © 2024 IEEE.

关键词： Sliding mode control

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A Principal Bundle Framework for Generalised Notions of Formation and Rigidity ⁎

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IFAC-PapersOnLine 2024年第6期58卷 262-267页

作者： Rama Seshan C Ravi N Banavar Arun D Mahindrakar Control and Optimization Group IIT Madras India Systems and Control Engineering IIT Bombay India

In this work, the notions of formation and rigidity (first developed for formation control in Euclidean spaces) are recast in a general framework of principal fiber bundles and a control law is derived for second order systems for driving the system to a given formation. The Euclidean inter-agent distance measurements and congruence transformations are generalised as output maps and Lie group actions respectively, to capture more generic scenarios.

关键词： Formation Rigidity fiber Bundle Multi-Agent systems Geometric Mechanics

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Formation control with Collision Avoidance: Adaptive Sliding Mode Approach

Formation Control with Collision Avoidance: Adaptive Sliding...

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International Workshop on Variable Structure systems, VSS

作者： Asifa Yesmin Kiran Kumari Arpita Sinha IDP in Systems and Control Engineering Indian Institute of Technology Bombay India

ISBN: (数字)9798350353686

ISBN: (纸本)9798350353693

This paper introduces a formation control framework for a double integrator multi-agent system (MAS) utilizing adaptive sliding mode control (SMC) integrated with a collision avoidance strategy. To prevent inter-agent collisions, the artificial potential function is employed, leveraging inter-agent positions and predefined safe and avoidance zones. A new sliding surface is defined to enhance tracking performance while incorporating collision avoidance functionalities. Additionally, a proportional reaching law-based control scheme is devised to expedite the convergence of sliding trajectories. The asymptotic stability of the tracking error system is demonstrated through Lyapunov analysis. A numerical calculation has been performed to evaluate the performance of SMC and adaptive SMC based on different indices. MATLAB simulation results are presented to illustrate the effectiveness of the proposed controller design.

关键词： Variable structure systems Upper bound Heuristic algorithms Simulation Formation control Trajectory Collision avoidance MATLAB Sliding mode control Convergence

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A Moreau Envelope Approach for LQR Meta-Policy Estimation 63

A Moreau Envelope Approach for LQR Meta-Policy Estimation

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Aravind, Ashwin Toghani, Mohammad Taha Uribe, Cesar A. Iit Bombay Centre for Systems and Control MH Mumbai India Rice University Department of Electrical and Computer Engineering HoustonTX United States

ISBN: (纸本)9798350316339

We study the problem of policy estimation for the Linear Quadratic Regulator (LQR) in discrete-time linear timeinvariant uncertain dynamical systems. We propose a Moreau Envelope-based surrogate LQR cost, built from a finite set of realizations of the uncertain system, to define a meta-policy efficiently adjustable to new realizations. Moreover, we design an algorithm to find an approximate first-order stationary point of the meta-LQR cost function. Numerical results show that the proposed approach outperforms naive averaging of controllers on new realizations of the linear system. We also provide empirical evidence that our method has better sample complexity than Model-Agnostic Meta-Learning (MAML) approaches. © 2024 IEEE.

关键词： Cost functions

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Quantitative Estimates on the Domain of Feedback Linearization

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IFAC-PapersOnLine 2023年第1期56卷 144-149页

作者： Ashutosh Jindal Ravi Banavar Debasish Chatterjee Ronit M Chitre Systems and Control Engineering IIT Bombay Powai Mumbai 400076 India

Feedback linearization (FL) is a powerful tool to enable control synthesis for nonlinear systems. Since FL is a local construction, an important notion is the domain of validity of the procedure, and in particular, quantitative estimates of these domain of applicability of the procedure. Such quantification is missing in the existing literature and this article fills in this niche using the mathematical tool of the implicit function theorem. The results provide lower bounds on the region in which a given discrete time system is feedback linearizable.

关键词： Discrete Time control systems Feedback Linearization Numerical Integration

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Measure of controllability on SO(3)

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IFAC-PapersOnLine 2023年第1期56卷 361-366页

作者： Ashutosh Jindal Ravi Banavar Debasish Chatterjee Systems and Control Engineering IIT Bombay Powai Mumbai 400076 India

The classical notion of controllability provides us with a boolean variable — whether a given system is controllable or not. However, often as engineers we seek a notion of how ‘controllable’ a given system is, so as to classify systems that are ‘easier to control’ from those which are ‘difficult to control’. In this article we derive a quantitative measure of controllability for bilinear systems defined on the Lie group of rotations SO(3). Our controllability measure is based on the worst case cost of transferring the system from a given initial condition to a given final condition arbitrarily chosen over a set of interest. Here we consider a few frequently encountered cost functions such as control energy optimization and time optimal control, and obtain a relation between the worst case cost and the system parameters.

关键词： controllability Optimal Configuration Optimal control System Design

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Robust control Design for a linearized model of a LIGO subsystem

Robust Control Design for a linearized model of a LIGO subsy...

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European control Conference (ECC)

作者： Ashmita Roy Nishant Mittal Ravi N. Banavar Systems and Control Engineering IIT Bombay India Department of Electrical Engineering IIT Bombay India

Laser Interferometer Gravitational wave Observatory (LIGO) is a gravitational wave antenna used to detect the infinitesimal contraction and expansion of space by a passing gravitational wave. LIGO comprises several subsystems which isolate the optics from seismic noise. Of these, we focus on the quadruple pendulum suspension system and attempt to design a stabilizing controller for a simpler version of the system, the two wire simple pendulum. A nonlinear model of the two wire simple pendulum based on the Euler-Lagrange theory is derived. This is linearised about an equilibrium and a stabilising controller using a robust control paradigm called $H_{\infty} $ synthesis, is explored as a candidate design paradigm for the two wire simple pendulum. In particular, in this broad framework of $H_{\infty} $ synthesis we adopt a technique called coprime factorisation. Different types of uncertainties like parametric and nonlinear uncertainties have also been considered and an upper bound on the nonlinear uncertainties in the system is determined

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Self-Calibrating Offline Trajectory Estimation Technique for Sporadically Observable systems

Self-Calibrating Offline Trajectory Estimation Technique for...

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Indian control Conference (ICC)

作者： Somnath Buriuly Leena Vachhani Center of Excellence in Oil Gas and Energy IIT Bombay IITB-Monash Research Academy India Systems and Control Engineering IIT Bombay India

ISBN: (数字)9798331517212

ISBN: (纸本)9798331517229

Industrial problems, like pipeline inspection and railway track geometry inspection inside tunnels, require accurate offline estimation of the state trajectories, to determine the infrastructure parameters, say pipeline GPS coordinates, rail-track's attitude and placement, etc. These problems are cursed with loss of observability due to the unavailability of localization data, like GPS, inside pipelines and tunnels. In addition, the states at the start and end of the recorded data are observable but not accurately or entirely known. Furthermore, a deviation is observed in the initial calibration of the Inertial Measurement Unit (IMU) sensors, and hence the recorded data are approximated sensor readings. Since the accuracy of these estimated outcomes impacts the maintenance cost of the infrastructure, it is essential to obtain the best possible estimate from the offline available sensor data. In this work, we propose an optimization-based solution to estimate the entire trajectory and self-calibrate the sensor readings, simultaneously. In particular, we formulate an offline state trajectory estimation problem with self-calibration features for the sensor readings, compute the gradients for the decisions, and propose a Lagrangian-based gradient descent algorithm. We compare the results with the state-of-the-art Extended Kalman Filter and show improvement in the mean square error values of the estimates.

关键词： Accuracy Pipelines Estimation Inertial navigation Inspection Trajectory Kalman filters Observability Optimization Global Positioning System

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Novel min-max reformulations of linear inverse problems

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2022年第1期23卷 1271-1316页

作者： Mohammed Rayyan Sheriff Debasish Chatterjee Systems and Control Engineering IIT Bombay Mumbai India

In this article, we dwell into the class of so-called ill-posed Linear Inverse Problems (LIP) which simply refer to the task of recovering the entire signal from its relatively few random linear measurements. Such problems arise in a variety of settings with applications ranging from medical image processing, recommender systems, etc. We propose a slightly generalized 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 characterized 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, the 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.

关键词： linear inverse problems min-max problems dictionary learning

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