TY - GEN
T1 - Trajectory optimization for arrival aircraft using a hybrid IPSO-SQP algorithm
AU - Yang, Chen
AU - Yu, Yingrong
AU - Li, Qingdong
AU - Ren, Zhang
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/1/20
Y1 - 2017/1/20
N2 - This paper introduces an algorithm for solving the problem of arrival aircraft trajectory optimization. Under the constraints of terminal status and aircraft performance, the algorithm aims to find the best input (including thrust and load factor) to generate a vertical flight profile with the required time of arrival (RTA). The paper first identifies aircraft aerodynamic and fuel consumption models based on an open-source database called Base of Aircraft Data (BADA). The hybrid IPSO-SQP method which based on combining an improved particle swarm optimization (IPSO) with successive quadratic programming (SQP) is then used for trajectory optimization. During this process, IPSO is used to obtain a near optimum solution and then switch to SQP to accelerate the process and find an accurate solution. Finally, to validate the performance of the IPSO-SQP method, it is compared with standard PSO. Results show that the hybrid IPSO-SQP is an effective method for trajectory optimization problem.
AB - This paper introduces an algorithm for solving the problem of arrival aircraft trajectory optimization. Under the constraints of terminal status and aircraft performance, the algorithm aims to find the best input (including thrust and load factor) to generate a vertical flight profile with the required time of arrival (RTA). The paper first identifies aircraft aerodynamic and fuel consumption models based on an open-source database called Base of Aircraft Data (BADA). The hybrid IPSO-SQP method which based on combining an improved particle swarm optimization (IPSO) with successive quadratic programming (SQP) is then used for trajectory optimization. During this process, IPSO is used to obtain a near optimum solution and then switch to SQP to accelerate the process and find an accurate solution. Finally, to validate the performance of the IPSO-SQP method, it is compared with standard PSO. Results show that the hybrid IPSO-SQP is an effective method for trajectory optimization problem.
UR - http://www.scopus.com/inward/record.url?scp=85015244977&partnerID=8YFLogxK
U2 - 10.1109/CGNCC.2016.7829126
DO - 10.1109/CGNCC.2016.7829126
M3 - Conference contribution
AN - SCOPUS:85015244977
T3 - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
SP - 2159
EP - 2163
BT - CGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Y2 - 12 August 2016 through 14 August 2016
ER -