arXiv subjects

Bharat Kumar GVP

Publications and source records attributed to Bharat Kumar GVP.

7 recordsLinked to original sources

arXiv2026

Decoupled Thrust-Axis Attitude Control Using Quaternions for Chandrayaan-3 Lunar Landing Mission

Chandrayaan-3 mission achieved a historic milestone with its successful soft landing near the lunar south pole, highlighting the critical role of the navigation, guidance, and control (NGC) system. Navigation provided vehicle state estimates relative to the Moon center, while a polynomial based guidance scheme computed the required acceleration profile to meet terminal landing conditions. This acceleration demand was translated into total thrust magnitude and attitude commands generation. Attitude command generation involved aligning the thrust axis with the required acceleration vector and constraining rotation about the thrust axis, typically governed by mission-specific requirements. Although quaternion-based control laws are preferred for their singularity-free representation, they inherently couple all three rotational axes. This coupling can lead to undesirable interactions between guidance and control, especially during large rotations about the thrust axis, due to the quaternion shortest-path property. This paper proposes a novel quaternion-based decoupling method that enables independent thrust-axis control, mitigating guidance-control interaction and ensuring proper attitude commands generation for lander attitude control.

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arXiv2026

Real-Time Retargeting Using Controllability Boundary for Chandrayaan-3 Lunar Landing

This paper presents the real-time retargeting guidance policy developed for the Chandrayaan-3 lunar landing mission. The baseline guidance generates approximate fuel-optimal descent trajectories, while a high-level policy enables safe retargeting to alternate sites when the nominal site becomes infeasible. The retargeting strategy leverages a convex representation of the controllability boundary, allowing rapid feasibility checks and real-time target updates. To the best of the authors knowledge, this represents the first application of a data-driven retargeting framework in an operational lunar landing mission. Pre-flight simulations and Chandrayaan-3 flight results validate the effectiveness of the proposed approach.

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arXiv2025

Powered Descent Trajectory Optimization of Chandrayaan-3 using Radau Collocation and Controllable Sets

India achieved a significant milestone on August $23^{\text{rd}}$ 2023, becoming the fourth country to accomplish a soft landing on the Moon. This paper presents the powered descent trajectory design for the Chandrayaan-3 mission. The optimization framework is based on pseudospectral Radau collocation, and controllability-based waypoint refinement is employed to further enhance the robustness of the trajectory against state and control perturbations. Furthermore, the trade-off between fuel consumption and robustness is explicitly quantified, providing insights into the practical considerations of mission planning.

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arXiv2025

Closed-Loop Control Law for Low Thrust Orbit Transfer with Guaranteed Stability

Electric propulsion is used to maximize payload capacity in communication satellites. These orbit raising maneuvers span several months and hundreds of revolutions, making trajectory design a complex challenge. The literature typically addresses this problem using feedback laws, with Q-law being one of the most prominent approaches. However, Q-law suffers from closed-loop stability issues, limiting its suitability for real-time on-board implementation. In this work, we focus on closed-loop orbit raising rather than offline trajectory planning and address the stability limitations of the Q-law through a Lyapunov based control design. A Lyapunov-guided modification of the classical Q-law is proposed to ensure closed-loop stability and enable real-time implementation. The effectiveness of the proposed method is demonstrated through closed-loop orbit transfers across various scenarios, including co-planar transfers, equatorial to polar orbit transfers, and geostationary transfer orbit (GTO) to geostationary earth orbit (GEO) transfers.

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arXiv2025

Analysis of Optimal Thrust to Mass Ratio Requirement for Maximizing Payload Mass of Lunar Landing Mission

Recent successful lunar landing missions have generated significant interest among space agencies in establishing a permanent human settlement on the Moon. Building a lunar base requires multiple and frequent landing missions to support logistics and mobility applications. In these missions, maximizing payload mass defined as the useful cargo for human settlement is crucial. The landing mass depends on several factors, with the most critical being the maximum thrust available for braking and the engine's specific impulse (ISP). Generally, increasing engine thrust for braking reduces flight duration and, consequently, gravity losses. However, higher thrust also introduces trade-offs, such as increased engine weight and lower ISP, which can negatively impact payload capacity. Therefore, optimizing the descent trajectory requires careful consideration of these parameters to achieve a global solution that maximizes payload mass. Most existing research focuses on solving optimal control problems that minimize propellant consumption for a given thrust. These problems are typically addressed through trajectory optimization, where a minimum-fuel solution is obtained. The optimized trajectory is then executed onboard using polynomial guidance. In this paper, we propose an outer-layer optimization approach based on a Pareto-optimal solution. This method iterates on the maximum available thrust for descent trajectory optimization while incorporating a loss function that accounts for engine mass and ISP losses. By applying this approach, we identify a globally optimal solution that maximizes payload mass while ensuring an optimal landing trajectory.

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arXiv2025

Learning based Modelling of Throttleable Engine Dynamics for Lunar Landing Mission

Typical lunar landing missions involve multiple phases of braking to achieve soft-landing. The propulsion system configuration for these missions consists of throttleable engines. This configuration involves complex interconnected hydraulic, mechanical, and pneumatic components each exhibiting non-linear dynamic characteristics. Accurate modelling of the propulsion dynamics is essential for analyzing closed-loop guidance and control schemes during descent. This paper presents a learning-based system identification approach for modelling of throttleable engine dynamics using data obtained from high-fidelity propulsion model. The developed model is validated with experimental results and used for closed-loop guidance and control simulations.

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arXiv2025

Enhanced $A^{*}$ Algorithm for Mobile Robot Path Planning with Non-Holonomic Constraints

In this paper, a novel method for path planning of mobile robots is proposed, taking into account the non-holonomic turn radius constraints and finite dimensions of the robot. The approach involves rasterizing the environment to generate a 2D map and utilizes an enhanced version of the $A^{*}$ algorithm that incorporates non-holonomic constraints while ensuring collision avoidance. Two new instantiations of the $A^{*}$ algorithm are introduced and tested across various scenarios and environments, with results demonstrating the effectiveness of the proposed method.

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