Reentry Terminal Guidance Through Sliding Mode Control

Harl, Nathan; Balakrishnan, S. N.

doi:10.2514/1.42654

Cited by 70 publications

(35 citation statements)

References 6 publications

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“…As pointed out by the Harl and Balakrishnan [31] the adaptive nature of the guidance law is such that the system cannot be maintained on the first sliding surface for t > t F (see . However, for the soft landing guidance problem, the latter is a non-issue as the problem is over as soon as the system reaches the final time.…”

Section: Multiple Sliding Surface Guidance Development: Hosc Approachmentioning

confidence: 96%

“…Whereas theoretical studies on the finite-convergence properties of arbitrary-order sliding mode control are currently underway (e.g. Levant [20]), 2-sliding controllers have been already applied in practical problems of interest in space and aerospace applications including missile guidance [6,24,25,27], reentry terminal guidance [31] as well as lunar and asteroid landing guidance [28,30]. Importantly, Harl and Balakrishnan [31] set the stage on how to apply HOSC principles for terminal landing guidance problems.…”

Section: Sliding Control Theory For Systems Of Higher Relative Degreementioning

confidence: 99%

“…the dynamical system reaches the surface for the first time at the landing location (with the desired velocity). Such approach has been first proposed and discussed by Harl and Balakrishnan who applied HOSC to design a class of sliding-based guidance algorithms for the terminal guidance of an unpowered lifting vehicle during the approach and landing phase [31].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Terminal Multiple Surface Sliding Guidance for Planetary Landing: Development, Tuning and Optimization via Reinforcement Learning

et al. 2015

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The problem of achieving pinpoint landing accuracy in future space missions to planetary bodies such as the Moon or Mars presents many challenges, including the requirements of higher accuracy and degree of flexibility. These new challenges may require the development of a new class of guidance algorithms. In this paper, a nonlinear guidance algorithm for planetary landing is proposed and analyzed. Based on Higher-Order Sliding Control (HOSC) theory, the Multiple Sliding Surface Guidance (MSSG) algorithm has been specifically designed to take advantage of the ability of the system to reach multiple sliding surfaces in a finite time. As a result, a guidance law that is both globally stable and robust against unknown, but bounded perturbations is devised. The proposed MSSG does not require any offline trajectory generation, but the acceleration command is instead generated directly as function of the current and final (target) state. However, after initial analysis, it has been noted that the performance of MSSG critically depends on the choice in J of Astronaut Sci guidance gains. MSSG-guided trajectories have been compared to an open-loop fuelefficient solution to investigate the relationship between the MSSG fuel performance and the selection of the guidance parameters. A full study has been executed to investigate and tune the parameters of MSSG utilizing reinforcement learning in order to truly optimize the performance of the MSSG algorithm in powered descent scenarios. Results show that the MSSG algorithm can indeed generate closed-loop trajectories that come very close to the optimal solution in terms of fuel usage. A full comparison of the trajectories is included, as well as a further Monte Carlo analysis examining the guidance errors of the MSSG algorithm under perturbed conditions using the optimized set of parameters.

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Section: Multiple Sliding Surface Guidance Development: Hosc Approachmentioning

confidence: 96%

Section: Sliding Control Theory For Systems Of Higher Relative Degreementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Terminal Multiple Surface Sliding Guidance for Planetary Landing: Development, Tuning and Optimization via Reinforcement Learning

et al. 2015

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“…Kluever [8] developed an onboard trajectory-planning algorithm that recomputes a new reference trajectory based on the wind conditions, the energy state, and the aerodynamic performance. Harl et al [9] and Zhao et al [10] presented an A & L guidance method that computes an online reference path based on sliding mode control.…”

Section: Several Researchers Have Developed Guidance Systems For the mentioning

confidence: 99%

Automatic Approach and Landing Trajectory Planner for Unpowered Reusable Launch Vehicle

Al-Bakri¹,

Kluever²

2017

AAST

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A new guidance scheme for the approach and landing (A & L) phase of an unpowered reusable launch vehicle (RLV) has been developed. The main advantage of the new guidance is the use of glide-efficiency factor as the independent variable to compute the geometrical flare parameters by a set of analytical functions. The trajectory-planning algorithm generates its reference geometry based on the steep and shallow subphases, respectively. During the steep segment, the quasi-equilibrium glide (QEG) solution, which assumes a constant dynamic pressure and flight-path angle during the flight, is used to create the flight reference while the shallow segment is defined by polynomial functions for altitude and dynamic pressure profiles. Standard linearization methods are used to design a closed-loop command in order to track the QEG profile. Furthermore, proportion-derivative (PD) control is used to modulate the lift coefficient during the flare flight. Once the reference trajectory is created, a closed-loop simulation is obtained to track the reference. Off-nominal conditions, in terms of change in initial glide-efficiency factor, dynamic pressure, flight-path angle, and altitude are tested using a Monte-Carlo simulation. The simulated results demonstrate the effectiveness of the proposed algorithm to land the vehicle successfully under large dispersions of glide-efficiency factor.

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“…[5][6][7][8][9] Applying a sliding mode control (SMC) may cause an undesirable high-frequency input, which is so called 'chattering 10) phenomena'. A high-order sliding mode (HOSM), 8,[11][12][13] which includes a second-order sliding mode (SOSM) used in this study, mitigates the chatter problems associated with SMC. The authors propose an IGA design scheme for autonomous path-following applications 14) using an SOSM-based IGA and an HOSM differentiator.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Path-Following Flight with Uncertainty and Disturbance Compensation

Yamasaki

Takano

Yamaguchi

2014

AEROSPACE TECHNOLOGY JAPAN

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This paper focuses on autonomous path-following flight taking uncertainty and external disturbances into account. Integrated guidance and autopilot are developed using a second-order sliding mode approach that is one of the well-known approaches for mitigating so-called 'chattering phenomena'. The input magnitude for such a higher-order sliding mode approach tends to be extremely large in the initial reaching phase. In this paper, a novel sliding surface is developed using Ackermann and Utkin's method for reaching the surface smoothly to attenuate such extremely large initial inputs along with uncertainty and disturbance compensation. The potential of the proposed methodology is demonstrated with some path-following application under wind turbulence. Performance comparison with a conventional higher-order sliding mode approach is also presented.

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Reentry Terminal Guidance Through Sliding Mode Control

Cited by 70 publications

References 6 publications

Terminal Multiple Surface Sliding Guidance for Planetary Landing: Development, Tuning and Optimization via Reinforcement Learning

Terminal Multiple Surface Sliding Guidance for Planetary Landing: Development, Tuning and Optimization via Reinforcement Learning

Automatic Approach and Landing Trajectory Planner for Unpowered Reusable Launch Vehicle

Autonomous Path-Following Flight with Uncertainty and Disturbance Compensation

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