Hybrid QPSO and SQP Algorithm with Homotopy Method for Optimal Control of Rapid Cooperative Rendezvous

Focusing on the long-distance rapid cooperative rendezvous of two spacecraft under finite continuous thrust, this paper proposes a practical strategy for space operation using multiple specific-direction thrusts. Based on the orbital dynamic theory and Pontryagin’s maximum principle, the dynamic equations and optimal control equations for radial, circumferential, and normal thrust are determined. The optimization method is a hybrid algorithm. The initial costate variables for the fuel-optimal rapid cooperative rendezvous problem are obtained using quantum particle swarm optimization and subsequently set as the initial values in the sequence quadratic programming to search for the exact convergent solution. The elliptical and near-circular mission orbital rendezvous for spacecraft with multiple specific-direction thrusts are simulated and optimized. Numerical examples verifying the proposed method are provided. The results facilitate easier realization of rapid spacecraft maneuvering under continuous thrust conditions.

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“…30 and Liu et al. 40 proves that both stability and convergence of calculation results are significantly improved by employing SQP correction.…”

Section: Quantum-behaved Pso and Sqpmentioning

confidence: 97%

Optimal control of rapid cooperative spacecraft rendezvous with multiple specific-direction thrusts

Feng

Yang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part G:

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“…SQP is executed in numerous optimisation models of numerous complexes as well as non-stiff systems. Presently, it is used to investigate the guidewire deformation in blood vessels [42], in the power system stabiliser design [43], optimal control of rapid cooperative rendezvous [44], 3D deformable prostate model pose estimation in minimally invasive surgery [45], deterministic constrained production optimisation of hydrocarbon reservoirs [46], prediction differential system [47] and in the optimisation of an auxetic jounce bumper [48]. To switch the sluggishness of GA, hybridisation of the GA-SQP process is implemented along with the necessary steps, as provided in Table 1.…”

Section: Optimisation Measures: Mwnns-ga-sqpmentioning

confidence: 99%

Design of Morlet wavelet neural network to solve the non-linear influenza disease system

Sabir

Umar

Raja

et al. 2021

Applied Mathematics and Nonlinear Sciences

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In this study, the solution of the non-linear influenza disease system (NIDS) is presented using the Morlet wavelet neural networks (MWNNs) together with the optimisation procedures of the hybrid process of global/local search approaches. The genetic algorithm (GA) and sequential quadratic programming (SQP), that is, GA-SQP, are executed as the global and local search techniques. The mathematical form of the NIDS depends upon four groups: susceptible S(y), infected I(y), recovered R(y) and cross-immune individuals C(y). To solve the NIDS, an error function is designed using NIDS and its leading initial conditions (ICs). This error function is optimised with a combination of MWNNs and GA-SQP to solve for all the groups of NIDS. The comparison of the obtained solutions and Runge–Kutta results is presented to authenticate the correctness of the designed MWNNs along with the GA-SQP for solving NIDS. Moreover, the statistical operators using different measures are presented to check the reliability and constancy of the MWNNs along with the GA-SQP to solve the NIDS.

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“…Real‐world OCPs involve realistic constraints upon controls 1‐4 . Regularization, control smoothing, and homotopic (continuation) approaches are key enablers for solving OCPs with control constraints using indirect methods 13‐27 . Trigonometric functions have been employed as useful tools especially in Aerospace engineering for developing various approaches to control the dynamical systems involved.…”

Section: Introductionmentioning

confidence: 99%

Solving complex optimal control problems with nonlinear controls using trigonometric functions

Mall

Grant

Taheri

2020

Optim Control Appl Methods

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This study investigates the use of trigonometric functions to resolve two major issues encountered when solving practical optimal control problems (OCPs) that are characterized by nonlinear controls. First, OCPs with constraints on nonlinear controls require the solution to a multipoint boundary value problem, which poses additional computational difficulties. Second, in certain unconstrained OCPs with nonlinear controls, the extremum found from the necessary conditions can be opposite than expected (e.g., a maximum instead of a minimum) due to the absence of control options. The aforementioned issues and their effective resolution by using trigonometric functions are explained through two examples including a second‐order system problem and an aerocapture problem of a slender entry vehicle in the Martian atmosphere.

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Hybrid QPSO and SQP Algorithm with Homotopy Method for Optimal Control of Rapid Cooperative Rendezvous

Cited by 8 publications

References 37 publications

Optimal control of rapid cooperative spacecraft rendezvous with multiple specific-direction thrusts

Optimal control of rapid cooperative spacecraft rendezvous with multiple specific-direction thrusts

Design of Morlet wavelet neural network to solve the non-linear influenza disease system

Solving complex optimal control problems with nonlinear controls using trigonometric functions

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