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Trajectory optimization of aircraft based on intelligent bionic algorithm 7

Trajectory optimization of aircraft based on intelligent bio...

引用

7th International Conference on Automation Electronics and Electrical Engineering

作者： Guo, Qianchen Yin, Anlan Wang, Yichen Harbin Engn Univ Harbin 150001 Peoples R China

ISBN: (纸本)9798350377040;9798350377033

With the continuous advancement of AI intelligent algorithms, significant progress has been achieved in unmanned systems research. Among these, the intelligent selection of autonomous flight paths for unmanned aerial vehicles (UAVs) holds substantial research value. The application of bio-inspired intelligent algorithms to solve the optimal flight trajectory for UAVs is critically important. This study first establishes a spline interpolation model for UAV flight trajectories, deriving the mathematical expression of the trajectory based on multiple key points. Subsequently, a wolf pack optimization algorithm is developed to simulate and compute the optimal flight trajectory among infinite possible paths. Finally, comprehensive validation is conducted on the MATLAB simulation platform. Simulations under various initial conditions and scenarios with randomly generated obstacles demonstrate the ability to solve for the optimal flight path accurately. The results rigorously confirm the correctness of the algorithm's application and provide effective guidance for subsequent UAV flight path design.

关键词： Aircraft wolf pack optimization algorithm Spline interpolation MATLAB

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A New Wolves Intelligent optimization algorithm 20

A New Wolves Intelligent Optimization Algorithm

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20th IEEE/ACIS International Summer Semi-Virtual Conference on Computer and Information Science (ICIS)

作者： Sun Yanchao Chen, Wei Wu, Yuqing Beijing Informat Sci & Technol Univ Beijing Peoples R China

ISBN: (纸本)9781665418935

This paper proposes a new wolf pack intelligent optimization algorithm, which is based on an adaptive shrinking grid search chaotic wolf optimization algorithm with an adaptive standard deviation update amount. Theoretical research and experimental results show that compared with traditional genetic algorithm, particle swarm algorithm, wolf pack optimization algorithm based on leadership strategy, and chaotic wolf pack optimization algorithm, the algorithm proposed in this paper has better global optimization accuracy under the same conditions. Faster convergence speed and higher robustness.

关键词： optimization accuracy wolf pack optimization algorithm complex nonlinear function

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Application of Adaptive Fractional Order Control in Wire Rod Looper System 30

Application of Adaptive Fractional Order Control in Wire Rod...

引用

30th Chinese Control and Decision Conference (CCDC)

作者： Zhang Yong Zhu Hai-bo Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114051 Peoples R China

ISBN: (纸本)9781538612446

Aimed at the shortcomings of traditional PID control method, such as large overshoot, long dynamic response time and low control accuracy in wire rod looper control, an improved wolf pack algorithm optimizing approximation of fractional order control method is proposed. The method uses tractional order controller to improve the control precision of the looper control system, to realize the rational approximation of fractional calculus operator online optimization using the improved wolf pack optimization algorithm. The gravitational search mechanism introduced into the wolf pack algorithm effectively improves the global search ability and search efficiency of the wolf pack algorithm, and adds dynamic disturbance strategy to the optimal region of wolf pack algorithm to improve the search accuracy and avoid falling into the local optimum value. The improved wolf pack algorithm is applied to test the multimodal test function, the test results show that the wolf pack optimization algorithm based on gravitational search mechanism has better global search ability and higher search accuracy. The application of which into the fractional order wire rod loop control system improves the control accuracy, speed and robustness of loop system, and its comprehensive performance is better than other comparison algorithms.

关键词： Loop system wolf pack optimization algorithm Gravity search Fractional order controller

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Application of Adaptive Fractional Order Control in Wire Rod Looper System

Application of Adaptive Fractional Order Control in Wire Rod...

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第30届中国控制与决策会议

作者： Zhang Yong Zhu Hai-bo School of electronics and Information Engineering University of Science and Technology Liaoning

Aimed at the shortcomings of traditional PID control method, such as large overshoot, long dynamic response time and low control accuracy in wire rod looper control, an improved wolf pack algorithm optimizing approximation of fractional order control method is proposed. The method uses fractional order controller to improve the control precision of the looper control system, to realize the rational approximation of fractional calculus operator online optimization using the improved wolf pack optimization algorithm. The gravitational search mechanism introduced into the wolf pack algorithm effectively improves the global search ability and search efficiency of the wolf pack algorithm, and adds dynamic disturbance strategy to the optimal region of wolf pack algorithm to improve the search accuracy and avoid falling into the local optimum value. The improved wolf pack algorithm is applied to test the multimodal test function, the test results show that the wolf pack optimization algorithm based on gravitational search mechanism has better global search ability and higher search accuracy. The application of which into the fractional order wire rod loop control system improves the control accuracy, speed and robustness of loop system, and its comprehensive performance is better than other comparison algorithms.

关键词： Loop system wolf pack optimization algorithm Gravity search Fractional order controller

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