Ascent Trajectory Optimization for Air-Breathing Hypersonic Vehicles Based on IGS-MPSP

2021 ◽  
Vol 01 (02) ◽  
pp. 2150010
Author(s):  
Lei Liu ◽  
Qianwei He ◽  
Bo Wang ◽  
Wenzhe Fu ◽  
Zhongtao Cheng ◽  
...  
Keyword(s):  
Computational Efficiency ◽  
Trajectory Optimization ◽  
Hypersonic Vehicles ◽  
Penalty Function Method ◽  
Control Input ◽  
Sensitivity Matrix ◽  
Decision Variables ◽  
Representation Technique ◽  
And Control ◽  
High Computational Efficiency

This paper proposes an improved Generalized Quasi-Spectral Model Predictive Static Programming (GS-MPSP) algorithm for the ascent trajectory optimization for hypersonic vehicles in a complex flight environment. The proposed method guarantees the satisfaction of constraints related to the state and control vector while retaining its high computational efficiency. The spectral representation technique is used to describe the control variables, which reduces the number of decision variables and makes the control input smooth enough. Through Taylor expansion, the constraints are transformed into an inequality containing only decision variables, such that it can be added into GS-MPSP framework. By Gauss quadrature collocation method, only a few collocation points are needed to solve the sensitivity matrix, which greatly accelerates the calculation. Subsequently, the analytical expression is obtained by combining the static optimization with the penalty function method. Finally, the simulation results demonstrate that the proposed improved GS-MPSP algorithm can achieve both high computational efficiency and high terminal precision under the constraints.

scholarly journals A Rapid Penetration Trajectory Optimization Method for Hypersonic Vehicles

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Binbin Yan ◽  
Ruifan Liu ◽  
Pei Dai ◽  
Muzeng Xing ◽  
Shuangxi Liu
Keyword(s):  
Trajectory Optimization ◽  
Optimization Method ◽  
Hypersonic Vehicle ◽  
Hypersonic Vehicles ◽  
Relaxation Techniques ◽  
Computational Performance ◽  
Second Order Cone ◽  
Ballistic Missiles ◽  
And Control

The evasion maneuver problem of hypersonic vehicles differs from those of ballistic missiles and other traditional weapons, showing distinctive properties including expansive maneuver range and weak maneuverability. How to avoid the disadvantage of low available overload and ensure follow-up tasks are the main concerns of the hypersonic penetration. This paper presents a penetration trajectory optimization algorithm for an air-breathing hypersonic vehicle, where the prerequisite penetration condition is analyzed and control costs are chosen as an objective function to minimize the fuel consumption and maneuver range. This paper focuses on how to formulate the complex, highly constrained nonconvex penetration problem to be a sequence of easily solved second-order cone programming through a combination of successive linearization and relaxation techniques. Innovation lies in the raising of the penetration angle and the relaxation technique of nonlinear and nonconvex elements. Various numerical simulations are conducted to verify the validity of penetration condition and to demonstrate that the proposed method is effective and has a good computational performance irrespective of initial guesses.

Reentry Trajectory Optimization of Airbreathing Hypersonic Vehicles Based on Gauss Pseudospectral Method

2011 ◽  
Vol 383-390 ◽  
pp. 7375-7380 ◽  
Author(s):  
Bo Yang ◽  
Shang Sun
Keyword(s):  
Trajectory Optimization ◽  
Optimization Problems ◽  
Kinetic Equations ◽  
Pseudospectral Method ◽  
Hypersonic Vehicles ◽  
Gauss Pseudospectral Method ◽  
Suboptimal Solution ◽  
Reentry Trajectory ◽  
Reentry Trajectory Optimization ◽  
And Control

According to the nonlinear, multivariable and multi-constraint features of the reentry trajectory optimization problem of airbreathing hypersonic vehicles, a suboptimal solution method is developed. The reentry trajectory generation is converted to a nonlinear programming (NLP) problem by using Gauss pseudospectral method (GPM). The state and control variables on Gauss nodes are chosen as parameters to be optimized and the minimum total heat absorption is chosen as the optimal performance index. Then the sequential quadratic programming (SQP) method is used to solve the NLP problem. The states of optimized trajectory are compared with the states obtained by the integral of kinetic equations. By simulating on an example of airbreathing hypersonic vehicles, it is demonstrated that the above method is not sensitive to the estimate of motion states and is easier to converge. And the method is effective to solve trajectory optimization problems.

Three-dimensional adaptive fixed-time guidance law against maneuvering targets with impact angle constraints and control input saturation

2021 ◽  
pp. 014233122110598
Author(s):  
Fei Ma ◽  
Yunjie Wu ◽  
Siqi Wang ◽  
Xiaofei Yang ◽  
Yueyang Hua
Keyword(s):  
Sliding Mode ◽  
Input Saturation ◽  
Three Dimensional ◽  
Fixed Time ◽  
Impact Angle ◽  
Guidance System ◽  
Control Input ◽  
Guidance Law ◽  
The Stability ◽  
And Control

This paper presents an adaptive fixed-time guidance law for the three-dimensional interception guidance problem with impact angle constraints and control input saturation against a maneuvering target. First, a coupled guidance model formulated by the relative motion equation is established. On this basis, a fixed-time disturbance observer is employed to estimate the lumped disturbances. With the help of this estimation technique, the adaptive fixed-time sliding mode guidance law is designed to accomplish accurate interception. The stability of the closed-loop guidance system is proven by the Lyapunov method. Simulation results of different scenarios are executed to validate the effectiveness and superiority of the proposed guidance law.

Riccati Discrete Time Transfer Matrix Method for Dynamic Modeling and Simulation of an Underwater Towed System

2012 ◽  
Vol 79 (4) ◽  
Author(s):  
Guoping Wang ◽  
Bao Rong ◽  
Ling Tao ◽  
Xiaoting Rui
Keyword(s):  
Modeling And Simulation ◽  
Dynamic Modeling ◽  
Computational Efficiency ◽  
Finite Segment ◽  
Modeling And Control ◽  
Global Dynamic ◽  
Transfer Equations ◽  
High Matrix ◽  
Towed Cable ◽  
And Control

Efficient, precise dynamic modeling and control of complex underwater towed systems has become a research focus in the field of multibody dynamics. In this paper, based on finite segment model of cable, by defining the new state vectors and deducing the new transfer equations of underwater towed systems, a new highly efficient method for dynamic modeling and simulation of underwater towed systems is presented and the pay-out/reel-in process of towed cable is studied. The computational efficiency and numerical stability of the proposed method are discussed. When using the method to study the dynamics of underwater towed systems, it avoids the global dynamic equations of system, and simplifies solving procedure. Irrespective of the degree of freedom of underwater towed system, the matrices involved in the proposed method are always very small, which greatly improve the computational efficiency and avoids the computing difficulties caused by too high matrix orders for complex underwater towed systems. Formulations of the method as well as numerical simulations are given to validate the proposed method.

scholarly journals Technical Note: Improving computational efficiency in large linear inverse problems: an example from carbon dioxide flux estimation

2012 ◽  
Vol 5 (4) ◽  
pp. 3325-3342
Author(s):  
V. Yadav ◽  
A. M. Michalak
Keyword(s):  
Carbon Dioxide ◽  
Inverse Problems ◽  
Computational Efficiency ◽  
Optimization Problems ◽  
Temporal Distribution ◽  
Carbon Dioxide Flux ◽  
Technical Note ◽  
Sensitivity Matrix ◽  
Direct Computation ◽  
Spatio Temporal

Abstract. Addressing a variety of questions within Earth science disciplines entails the inference of the spatio-temporal distribution of parameters of interest based on observations of related quantities. Such estimation problems often represent inverse problems that are formulated as linear optimization problems. Computational limitations arise when the number of observations and/or the size of the discretized state space become large, especially if the inverse problem is formulated in a probabilistic framework and therefore aims to assess the uncertainty associated with the estimates. This work proposes two approaches to lower the computational costs and memory requirements for large linear space-time inverse problems, taking the Bayesian approach for estimating carbon dioxide (CO2) emissions and uptake (a.k.a. fluxes) as a prototypical example. The first algorithm can be used to efficiently multiply two matrices, as long as one can be expressed as a Kronecker product of two smaller matrices, a condition that is typical when multiplying a sensitivity matrix by a covariance matrix in the solution of inverse problems. The second algorithm can be used to compute a posteriori uncertainties directly at aggregated spatio-temporal scales, which are the scales of most interest in many inverse problems. Both algorithms have significantly lower memory requirements and computational complexity relative to direct computation of the same quantities (O(n2.5) vs. O(n3)). For an examined benchmark problem, the two algorithms yielded a three and six order of magnitude increase in computational efficiency, respectively, relative to direct computation of the same quantities. Sample computer code is provided for assessing the computational and memory efficiency of the proposed algorithms for matrices of different dimensions.

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