Finite-time Convergent Impact Angle Constrained Sliding Mode Guidance

Majumder, Kakoli; Kumar, Shashi Ranjan

doi:10.1016/j.ifacol.2020.06.015

Cited by 6 publications

(5 citation statements)

References 27 publications

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“…The guidance strategies for the stationary and the constant velocity target can be obtained as special cases of the maneuvering targets. Some of these cases were presented in Majumder K and Kumar SR 33 . In case of non-maneuvering targets, a T , truea˙T, and trueθ˙d become zero.…”

Section: Resultsmentioning

confidence: 99%

“…The major advantage of predefined-time notion is that it is possible to obtain an explicit relationship between the system parameters and the bound of the settling-time, thereby, the bound of settling-time is not a conservative estimate. A preliminary result on predefined-time SMC-based guidance law was presented in Majumder K and Kumar SR. 33 In view of the above-mentioned points, the main contributions of this work can be summarized as follows:• The SMC-based guidance strategy is designed using the concept of predefined-time stability that guarantees the interception of different types of targets at a desired impact angle within the predefined-time, from arbitrary initial engagement geometries. Owing to the use of a finite-time NDO, the proposed guidance strategy does not require the actual information on the target maneuvers, and thereby enhancing its applicability.• To achieve the guidance objectives with improved intercept performance and without exhibiting any singularity, the sliding surface is defined using the LOS angle error and its rate, along with the convergence time prescribed to them.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Remark 4. It can be observed from (18), ( 29), (33), and (39) that the lower bounds of the gain K are dependent on the initial engagement conditions, parameters of the system, and some constants. Any value of K larger than the given bound will satisfy the predefined-time convergence for the proposed guidance strategies.…”

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confidence: 99%

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Sliding mode control based impact angle constrained guidance with predefined convergence time

Majumder

Kumar

2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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This paper proposes predefined-time convergent guidance schemes that can drive the pursuer on a collision course corresponding to the target interception from a pre-specified impact direction, irrespective of initial engagement geometries. The target interception at the desired impact angle is first transformed into a problem of controlling the line-of-sight angle and its rate. Then, guidance commands are derived using sliding mode control (SMC) to ensure the convergence of corresponding errors to zero within a predefined time. A nonlinear disturbance observer is used to estimate the target’s maneuver, and the estimation error is treated as an uncertainty while rejecting its effect by virtue of SMC. Guidance commands are also derived for the case where the target maneuver is completely unknown except for its upper bound. It was shown that the gain could be selected based on the maximum bound on target maneuver to enforce sliding mode on the chosen surface, and thus guarantees target interception at a pre-specified impact angle, provided the closing speed of the engagement is positive. Owing to the use of a nonlinear framework while deriving pursuer guidance commands, the proposed guidance strategies remain valid even for engagements with large initial deviations where schemes based on linearized dynamics may fail or have degraded performance. The efficacy of the proposed guidance methods is validated through simulations for the pursuers having constant speed and time-varying speed, for various engagement geometries. The results of proposed strategies are compared with those of existing guidance and shown to be superior.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Sliding mode control based impact angle constrained guidance with predefined convergence time

Majumder

Kumar

2022

Proceedings of the Institution of Mechanical Engineers, Part G:

Self Cite

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“…The conventional guidance law can no longer meet these mission requirements, so more and more researchers have begun to study the guidance law with angle constraints. Constrained guidance was first proposed by Kim et al in 1973 [4], and, since then, various schemes have been proposed to meet different needs, including the biased proportional navigation (PN) schemes [5,6], sliding-mode variable structures [7,8], and optimal guidance laws [9,10]. However, sliding mode guidance laws can easily generate chattering, whereas the optimal guidance law often requires adopting certain assumptions, which can result in poor robustness.…”

Section: Introductionmentioning

confidence: 99%

Impact-Angle Constraint Guidance and Control Strategies Based on Deep Reinforcement Learning

Fan,

Dou,

2023

Aerospace

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In this study, two different impact-angle-constrained guidance and control strategies using deep reinforcement learning (DRL) are proposed. The proposed strategies are based on the dual-loop and integrated guidance and control types. To address comprehensive flying object dynamics and the control mechanism, a Markov decision process is used to solve the guidance and control problem, and a real-time impact-angle error in the state vector is used to improve the model applicability. In addition, a reasonable reward mechanism is designed based on the state component which reduces both the miss distance and the impact-angle error and solves the problem of sparse rewards in DRL. Further, to overcome the negative effects of unbounded distributions on bounded action spaces, a Beta distribution is used instead of a Gaussian distribution in the proximal policy optimization algorithm for policy sampling. The state initialization is then realized using a sampling method adjusted to engineering backgrounds, and the control strategy is adapted to a wide range of operational scenarios with different impact angles. Simulation and Monte Carlo experiments in various scenarios show that, compared with other methods mentioned in the experiment in this paper, the proposed DRL strategy has smaller impact-angle errors and miss distance, which demonstrates the method’s effectiveness, applicability, and robustness.

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Three-dimensional impact angle constrained nonlinear guidance with predefined convergence time

Majumder,

Kumar

2024

Nonlinear Dyn

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Finite-time Convergent Impact Angle Constrained Sliding Mode Guidance

Cited by 6 publications

References 27 publications

Sliding mode control based impact angle constrained guidance with predefined convergence time

Sliding mode control based impact angle constrained guidance with predefined convergence time

Impact-Angle Constraint Guidance and Control Strategies Based on Deep Reinforcement Learning

Three-dimensional impact angle constrained nonlinear guidance with predefined convergence time

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