Modeling the Load System of the Helicopter Engine Test Bench and Designing the Developed Gain-Scheduling Adaptive PI Controller

Document Type : Research Paper

Authors

Department of Electrical and Computer Engineering, Semnan University, Semnan, Iran

Abstract

The helicopter engine test bench is a safe environment for checking the performance of the engine in its various operational areas. In order to check the performance of the engine in different operating areas, a load application system is needed. The torque generated by this system has a strong non-linear relationship with the angular velocity of the shaft and the vortex velocity of the fluid. The linear controller does not perform well in the face of the nonlinear behavior of the dynamometer and it fluctuates strongly in different areas. In this paper, by examining and studying the behavior of dynamometer and helicopter engine in different functional areas, models of engine and dynamometer torque production are presented in relation to effective input parameters. According to the nonlinear behavior of the dynamometer, a developed gain-scheduling adaptive PI controller is designed .The performance of this controller is simulated in the MATLAB software environment with the extracted model. To implement the controller, the time characteristics of the control system components are extracted by considering the controller loop time. The controller is executed in the real system with the designed hardware. The performance of the controller is investigated in different areas of required performance tests. Due to the fact that the linear controller adjusted in each functional area had severe fluctuations in other areas, Experiments showed that the developed gain-scheduling adaptive controller has no fluctuationin all functional areas of the engine and has an error of less than 0.5% in the stable state.

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References

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Journal of Modeling in Engineering
Volume 23, Issue 83
December 2025
Pages 27-39

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History

  • Receive Date: 16 September 2024
  • Revise Date: 19 November 2024
  • Accept Date: 09 December 2024

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