Avijit Banerjee

Bio: Avijit Banerjee is an academic researcher from Indian Institute of Science. The author has contributed to research in topics: Soft landing & Observer (quantum physics). The author has an hindex of 4, co-authored 13 publications receiving 27 citations. Previous affiliations of Avijit Banerjee include Luleå University of Technology & Jadavpur University.

Multi-phase MPSP Guidance for Lunar Soft Landing

Abstract: In this paper, an autonomous optimal guidance algorithm for multi-phase lunar soft landing is presented. Various stringent requirements of a typical multi-phase soft landing are incorporated in guidance formulation. The proposed guidance law is formulated using the model predictive static programming (MPSP), which is an emerging computational guidance algorithm. High accuracy on the terminal position and velocity at the end of each phase is ensured, as the formulation of the MPSP inherently poses terminal output as a set of hard constraints. The spacecraft terminal orientation requirement is embedded in the guidance formulation in a soft constrained manner. Moreover, to facilitate a smooth transition between successive segments, an initial continuity of the guidance command is also attempted in an approximate manner. The effectiveness of the proposed method is demonstrated with simulation results. A processor-in-loop simulation study has been presented to demonstrate the feasibility of the proposed guidance law for possible on-board implementation.

Optimal guidance for accurate lunar soft landing with minimum fuel consumption using Model Predictive Static Programming

Abstract: In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.

Platform motion disturbances attenuation in a missile seeker subsystem using Internal Model Control

Abstract: In this paper two degree of freedom Internal Model Controller (2-DOF IMC) is used to attenuate the platform (missile body) disturbance that couples to the gimbal inner axis (elevation axis) angular rate of the seeker i.e. the angular rate of the inner (elevation) axis of the seeker gimbal in the pitch plane. IMC is an efficient robust controller and its use in process control system is very common. It can track reference input and simultaneously it also rejects the external disturbances that enter into the system. In this paper these features have been utilized to attenuate the base disturbances and disturbance torque in the seeker system.

Construction of full order observer for linear time invariant systems using generalized matrix inverse

Abstract: In this paper a procedure for construction of full order observer for linear time invariant system represented by state space description is proposed. The construction procedure makes use of the theory of generalized matrix inverse and does not presuppose the observer structure and impose no restriction on the structure of the system output matrix. The construction is straightforward and easy. Illustrative numerical example with simulation results are included.

Inverse polynomial based explicit guidance for lunar soft landing during powered braking

Abstract: In this paper an explicit guidance law for the powered descent phase of the soft lunar landing is presented. The descent trajectory, expressed in polynomial form is fixed based on the boundary conditions imposed by the precise soft landing mission. Adapting an inverse model based approach, the guidance command is computed from the known spacecraft trajectory. The guidance formulation ensures the vertical orientation of the spacecraft during touchdown. Also a closed form relation for the final flight time is proposed. The final time is expressed as a function of initial position and velocity of the spacecraft (at the start of descent) and also depends on the desired landing site. To ensure the fuel minimum descent the proposed explicit method is extended to optimal guidance formulation. The effectiveness of the proposed guidance laws are demonstrated with simulation results.

An adaptive decoupling control for three-axis gyro stabilized platform based on neural networks

Abstract: In order to improve the tracking and stabilization performance of three-axis gyro stabilized platform, an adaptive decoupling control based on neural networks is developed. The dynamic model of three-axis GSP is developed based on traditional Newton–Euler method. The nonlinearity and coupling system is full-state-linearized using feedback linearization, and neural networks are used to compensate for the disturbances and uncertainties. The stability of the proposed scheme is analyzed by the Lyapunov criterion. Comparative simulations and experiments results show the effectiveness of the proposed control approach compared with the conventional control.

Constrained optimal multi-phase lunar landing trajectory with minimum fuel consumption

Abstract: A Legendre pseudo spectral philosophy based multi-phase constrained fuel-optimal trajectory design approach is presented in this paper. The objective here is to find an optimal approach to successfully guide a lunar lander from perilune ( 18 km altitude) of a transfer orbit to a height of 100 m over a specific landing site. After attaining 100 m altitude, there is a mission critical re-targeting phase, which has very different objective (but is not critical for fuel optimization) and hence is not considered in this paper. The proposed approach takes into account various mission constraints in different phases from perilune to the landing site. These constraints include phase-1 (‘braking with rough navigation’) from 18 km altitude to 7 km altitude where navigation accuracy is poor, phase-2 (‘attitude hold’) to hold the lander attitude for 35 sec for vision camera processing for obtaining navigation error, and phase-3 (‘braking with precise navigation’) from end of phase-2 to 100 m altitude over the landing site, where navigation accuracy is good (due to vision camera navigation inputs). At the end of phase-1, there are constraints on position and attitude. In Phase-2, the attitude must be held throughout. At the end of phase-3, the constraints include accuracy in position, velocity as well as attitude orientation. The proposed optimal trajectory technique satisfies the mission constraints in each phase and provides an overall fuel-minimizing guidance command history.

Multi-phase MPSP Guidance for Lunar Soft Landing

Abstract: In this paper, an autonomous optimal guidance algorithm for multi-phase lunar soft landing is presented. Various stringent requirements of a typical multi-phase soft landing are incorporated in guidance formulation. The proposed guidance law is formulated using the model predictive static programming (MPSP), which is an emerging computational guidance algorithm. High accuracy on the terminal position and velocity at the end of each phase is ensured, as the formulation of the MPSP inherently poses terminal output as a set of hard constraints. The spacecraft terminal orientation requirement is embedded in the guidance formulation in a soft constrained manner. Moreover, to facilitate a smooth transition between successive segments, an initial continuity of the guidance command is also attempted in an approximate manner. The effectiveness of the proposed method is demonstrated with simulation results. A processor-in-loop simulation study has been presented to demonstrate the feasibility of the proposed guidance law for possible on-board implementation.

Adaptive super-twisting sliding mode control for stabilization platform of laser seeker based on extended state observer

Abstract: In this paper, the stabilization platform of the seeker is analyzed to stabilize the photo-electric device by isolating the disturbances caused by vibration and turbulence from external conditions, as well as mechanical coupled torque, coiling, unbalanced torque and plant parameter uncertainty due to inner conditions. There are two important indexes to describe the performance of disturbance isolation, and these are the coupling coefficient and disturbance rejection rate. In order to improve the disturbance isolation performance of the stabilization platform of the seeker, an adaptive super-twisting sliding mode controller with an extended state observer is proposed. The adaptive super-twisting sliding mode control strategy is designed to achieve stabilized control of the stabilization platform of the seeker. The extended state observer is used to estimate and compensate for disturbances and model uncertainties. The stability analysis of the control strategy is discussed using Lyapunov stability theory. Simulation and experimental results are also presented to illustrate the effectiveness of the proposed control strategy. The proposed controller provides a better level of disturbance rejection compared to the conventional PI-DOB controller.

Waypoint Constrained Multi-Phase Optimal Guidance of Spacecraft for Soft Lunar Landing

Abstract: A waypoint constrained multi-phase nonlinear optimal guidance scheme is presented in this paper for the soft landing of a spacecraft on the Lunar surface by using the recently developed computation...