Generalized quasi-spectral model predictive static programming method using Gaussian quadrature collocation

Zhou, Cong; Yan, Xiaodong; Tang, Shuo

doi:10.1016/j.ast.2020.106134

Cited by 13 publications

(7 citation statements)

References 22 publications

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“…Refs. [21][22][23][24][25][26][27] verified that the MPSP algorithm is feasible for solving guidance problems online. However, during integral prediction, modeling errors will cause the accumulation of estimation errors, affecting the algorithm's performance and stability.…”

Section: Literature Reviewmentioning

confidence: 91%

“…Refs. [23][24][25][26][27] improved the computational efficiency of the MPSP algorithm through further improvements and designed angle-constrained guidance methods, respectively. Refs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…(2) As one of the predictive guidance methods, MPSP-based guidance can avoid the model mismatch and thus can derive a better guidance performance, which has been verified in Refs. [21][22][23][24][25][26][27]. (3) The existing MPSP-based guidance methods are mainly focused on the angle constraint only.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Cubature Kalman Filters Model Predictive Static Programming Guidance Method with Impact Time and Angle Constraints Considering Modeling Errors

Xie

Wei

et al. 2023

Mathematics

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This paper proposes a CKF-MPSP guidance method for hitting stationary targets with impact time and angle constraints for missiles in the presence of modeling errors. This innovative guidance scheme is composed of three parts: First, the model predictive static programming (MPSP) algorithm is used to design a nominal guidance method that simultaneously satisfies impact time and angle constraints. Second, the cubature Kalman filter (CKF) is introduced to estimate values of the influence of the inevitable modeling errors. Finally, a one-step compensation scheme is proposed to eliminate the modeling errors’ influence. The proposed method uses a real missile dynamics model, instead of a simplified one with a constant-velocity assumption, and eliminates the effects of modeling errors with the compensation scheme; thus, it is more practical. Simulations in the presence of modeling errors are conducted, and the results illustrate that the CKF-MPSP guidance method can reach the target with a high accuracy of impact time and angles, which demonstrates the high precision and strong robustness of the method.

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Section: Literature Reviewmentioning

confidence: 91%

“…Refs. [23][24][25][26][27] improved the computational efficiency of the MPSP algorithm through further improvements and designed angle-constrained guidance methods, respectively. Refs.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Cubature Kalman Filters Model Predictive Static Programming Guidance Method with Impact Time and Angle Constraints Considering Modeling Errors

Xie

Wei

et al. 2023

Mathematics

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show abstract

“…In the simulation scenario, a missile is engaging a high-speed target with specific impact angle in the mid-course phase. 33 It is assumed that the solid motor of the missile has cut off and the position of predict intercept point (PIP) is given. 33 The missile pass through the thin air with a high height from top to bottom based on the high-throw reentry interception mode.…”

Section: Mission Applicationmentioning

confidence: 99%

“…33 It is assumed that the solid motor of the missile has cut off and the position of predict intercept point (PIP) is given. 33 The missile pass through the thin air with a high height from top to bottom based on the high-throw reentry interception mode. Hence, the angle of attack α and the sideslip angle β could be considered as 0, which is approximately assumed that the lift force Y≈0 and the side force Z≈0.…”

Section: Mission Applicationmentioning

confidence: 99%

Uncertain trajectory planning integrating polynomial chaos and convex programming

Tan

Jing

Gao

2022

Proceedings of the Institution of Mechanical Engineers, Part G:

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The present work explores the robust trajectory optimization scheme considering both the initial state disturbance and multiple constraints. An uncertain multi-constraint optimization model has been first established. Due to the existence of the stochastic disturbance, standard numerical trajectory planning algorithms cannot be directly applied to address the considered issue. Hence, based on the intrusive polynomial chaos expansion, we present a deterministic quantification for the stochastic state and constraints, so that the transformed optimization model becomes solvable for standard numerical optimization methods. To obtain the enhanced computational performance, an hp pseudo-spectral sequential convex programming procedure combined with a penalty function and backtracking search is proposed. This is achieved by discretizing and convexifying the nonlinear dynamics/constraints using hp quadrature collocation and successive linearization, respectively, and by adjusting the confidence region manually in the iteration. The simulation of a three-dimensional interception with the specific impact angle is conducted to verify the effectiveness. The simulation results show that the initial solutions are insensitive to the convex optimization, and the control commands generated by the proposed algorithm are effective against the initial state disturbance.

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Ascent Predictive Guidance for Thrust Drop Fault of Launch Vehicles Using Improved GS-MPSP

Yan

Zhou

2023

Springer Series in Astrophysics and Cosmology

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Increasing complex space missions require launch vehicles to be with greater load-carrying capacity, better orbit injection accuracy and higher reliability. Such demands also cause the increased complexity of the vehicle, leading to a higher probability of fault, especially for the propulsion system. To remedy this issue, an advanced and robust ascent guidance capable of fault-tolerant is critical for the success of mission. Iterative guidance method [1] (IGM) and powered explicit guidance [2] (PEG) are two commonly used methods for the ascent phase of launch vehicles. These two guidance methods work well in the nominal condition and can adapt to many off-nominal conditions [3]. However, they lack of strong adaptive capacity, which cannot guarantee the reliability when the dynamic model or parameters change significantly. Alternatively, numerical approaches based on the optimal control theory may be the better choice. The existing algorithms can be divided into direct methods and indirect methods. Using the indirect methods, the guidance problem is transformed into Hamilton two-point boundary value problems [4] (TPBVP), but the solving process of this Hamilton two-point boundary value problem is complicated and highly sensitive to the initial guess. Using the direct method, the guidance problem is transformed into a nonlinear programming problem [5] (NLP). However, solving such problem is extremely computational intensive, which is difficult to meet the real-time requirement for online application.

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Generalized quasi-spectral model predictive static programming method using Gaussian quadrature collocation

Cited by 13 publications

References 22 publications

Cubature Kalman Filters Model Predictive Static Programming Guidance Method with Impact Time and Angle Constraints Considering Modeling Errors

Cubature Kalman Filters Model Predictive Static Programming Guidance Method with Impact Time and Angle Constraints Considering Modeling Errors

Uncertain trajectory planning integrating polynomial chaos and convex programming

Ascent Predictive Guidance for Thrust Drop Fault of Launch Vehicles Using Improved GS-MPSP

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