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

Author(s):  
Piaoyi Su ◽  
Weiming Feng ◽  
Yang Kun ◽  
Zhao Junfeng

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.

2021 ◽  
Vol 2068 (1) ◽  
pp. 012021
Author(s):  
Fei Ren

Abstract The continuous-thrust far-distance cooperative rendezvous problem between two spacecraft is investigated. The indirect optimization method, based on Pontryagin’s maximum principle (PMP), is applied to optimize fuel consumption. To overcome the difficulty in nonsmooth integration caused by the bang-bang control, the homotopy method is adopted to solve the fuel-optimal problem from a related energy-optimal problem. The quantum-behaved particle swarm optimization (QPSO) algorithm is used to obtain the energy-optimal solutions. The energy-optimal solutions are used as the initial values for the homotopic procedure to obtain the fuel-optimal solutions and optimal bang-bang control law. A hybrid algorithm combined homotopy method and sequential quadratic programming (SQP) algorithm is proposed. This hybrid algorithm can effectively obtain feasible optimal solutions even though the indirect optimization method exhibits a narrow convergence domain. Simulations of high-thrust and low-thrust rendezvous problems are provided and the proposed hybrid algorithm is verified. Moreover, the necessity of radial thrust is investigated.


Author(s):  
Trevor Place ◽  
Greg Sasaki ◽  
Colin Cathrea ◽  
Michael Holm

Strength and leak testing (AKA ‘hydrotesting’, and ‘pressure testing’) of pipeline projects remains a primary method of providing quality assurance on new pipeline construction, and for validating structural integrity of the as-built pipeline [1][2][3]. A myriad of regulations surround these activities to ensure soundness of the pipeline, security of the environment during and after the pressure testing operation, as well as personnel safety during these activities. CAN/CSA Z662-11 now includes important clauses to ensure that the pipeline designer/builder/operator consider the potential corrosive impacts of the pressure test media [4]. This paper briefly discusses some of the standard approaches used in the pipeline industry to address internal corrosion caused by pressure test mediums — which often vary according to the scope of the pipeline project (small versus large diameter, short versus very long pipelines) — as well as the rationale behind these different approaches. Case studies are presented to highlight the importance of considering pressure test medium corrosiveness. A practical strategy addressing the needs of long-distance transmission pipeline operators, involving a post-hydrotest inhibitor rinse, is presented.


2011 ◽  
Vol 219-220 ◽  
pp. 546-550
Author(s):  
Ming Shan Cai ◽  
Ling Shuang Kong

Based on the strong coupling and interval requirement of multiple quality indices, the interval-index-oriented optimization method is proposed to effectively realize the optimal control of alumina blending process. Firstly, the lexicographic interval goal programming model is built to describe the process requirements for quality indices. Then, based on the characteristics of the programming model, a kind of classificatory knowledge base is constructed by using the empirical knowledge accumulated in long-term production and the expert reasoning strategy is proposed to realize the optimal control of quality indexes with interval constraints. The results of industrial application shows that the proposed method can realize the optimal control of quality indices. It provides a good optimization mode for other blending processes of nonferrous metal production.


2021 ◽  
Vol 2113 (1) ◽  
pp. 012022
Author(s):  
Chao Sun

Abstract In this paper, taking the feeding process as a form of impulsive and considering the time-delay in fermentation process. A robust model with the time-delay system as the control variable and the time-delay system as the constraint is established. In order to solve this optimal control problem, we have propose an particle swarm optimization method to solve problem. Numerical results show that 1,3-PD yield at the terminal time increases compared with the experimental result.


Author(s):  
Fouad Yacef ◽  
Nassim Rizoug ◽  
Laid Degaa ◽  
Omar Bouhali ◽  
Mustapha Hamerlain

Unmanned aerial vehicles are used today in many real-world applications. In all these applications, the vehicle endurance (flight time) is an important constraint that affects mission success. This study investigates the limitations of embedded energy for a quadrotor aerial vehicle. We consider a quadrotor simple tasked to travel from an initial hover configuration to a final hover configuration. In order to have a precise approximation of the consumed energy, we propose a power consumption model with battery dynamic, motor dynamic, and rotor efficiency function. We then introduce an optimization algorithm to minimize the energy consumption during quadrotor aerial vehicle mission. The proposed algorithm is based on an optimal control problem formulated for the quadrotor model and solved using nonlinear programming. In the optimal control problem, we seek to find control inputs (rotor velocity) and vehicle trajectory between initial and final configurations that minimize the consumed energy during a point-to-point mission. We extensively test in simulation experiments the proposed algorithm under normal and windy weather conditions. We compare the proposed optimization method with a nonlinear adaptive control approach to highlight the saved amount of energy.


2019 ◽  
Vol 32 (4) ◽  
pp. 04019030 ◽  
Author(s):  
Gang Liu ◽  
Weiming Feng ◽  
Kun Yang ◽  
Junfeng Zhao

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