Research On Modeling Techniques And Performance Seeking Control Of Variable Cycle Engine

By adjusting the geometric parameters, the variable cycle engine(VCE) can change its aerodynamic thermodynamic cycle, and meet different requirements of the plane under different flight conditions. So VCE can provide relatively high thrust and low fuel consumption in overall flight envelope, and possesses the advantageous properties of both the turbofan engine and the turbojet engine. As a consequence, it has gradually become the main research direction in the field of aero-engine. In this dissertation, a component level model of VCE was established, and the multivariable robust control and performance seeking control(PSC) of VCE were carried out based on the nonlinear model.The approach of establishing the component level mathematical model of VCE was researched firstly. Modeling methods were analyzed for the feature components of VCE. Subsection modeling for hub and tip of the fan was adopted. The artificial intelligent network was set up based on fluid analysis to model the relationship among the valve angle, the total pressure, the dynamic pressure of the bypass import to the total pressure loss coefficient of the bypass. The numerical simulations showed the validity of the model compared with the references. The VCE model has more working and balancing equations, bringing difficulty in solving the corresponding equations. Thus, the self-tuning Broyden quasi-newton method was put forward. Combined with the square convergence properties of Newton method and superlinear convergence properties of Broyden quasi-newton method, the self-tuning Broyden quasi-newton method can achieve better computational performance in nonlinear systems by adjusting calculation step length and correction function adaptively. The static and dynamic simulations of VCE model show that the self-tuning Broyden quasi-newton method has faster convergence speed and stronger adaptability to environment than the Newton method and Broyden quasi-newton method. In addition, a state observer module was designed based on Kalman filter to estimate the performance degradation of the VCE engine.Secondly, the multivariable robust control method of VCE was studied. The controlled parameters of VCE were selected from its many outputs based on robust stability and condition number(RSCN) analysis. The way to develop steady state control law of VCE was also researched. To ensure that the system has the properties of interference suppression and robust tracking, a multi-objective differential evolution(MODE) algorithm was adopted to search the best control parameters of the 3-input, 3-output LQ/H∞ controller. For its strong anti-interference property, the active disturbance rejection control was adopted to protect the engine from over limit. By adjusting the reference value of the main loop, the over limit protection of multi-constraints could be achieved. To verify the properties of the LQ/H∞ controller and the over limit protection controller, simulations were carried out at the transient states, and the switching state between different engine modes. The results demonstrate that the LQ/H∞ controller possesses satisfied dynamic performance and robust tracking properties. And the over limit protection controller can constrain multi-parameter within bounds quickly and efficiently via correcting the references of the main loop.The performance seeking control(PSC) simulation platform for VCE was established on the basis of component level model and robust control system. The feasibility of sequential quadratic constrained quadratic programming(SQCQP) algorithm for PSC was studied, and the differential evolution algorithm was proposed to solve the QCQP problems, which made SQCQP algorithms feasible to be realized in engineering. The PSC based on SQCQP for VCE was designed. Compared with SQP, which was commonly used in the PSC of aero-engine, the SQCQP method shows faster performance seeking speed.The sequential equations quadratic programming(SEQP) algorithm was proposed based on SQCQP algorithm and sequential systems of linear equations(SSLE) algorithm. To ensure the convergence speed and accuracy, the second-order constraints of SQCQP were moved, and the locus prediction of the iterative point was advanced to get the effective constraint and the integral equations. The iterative point can be renewed by those equations. The global convergence property and the strong convergence ability under certain conditions of the SEQP algorithm were proved. The simulation results show that the SEQP algorithm achieves faster optimization speed, better convergence accuracy than SQP algorithm. It has obvious advantages in the performance seeking control for the VCE.Finally, the adoption of swarm intelligent algorithms in the PSC was researched. By fusing the characteristics of the self-organizing migrating algorithm(SOMA) and the particle swarm algorithm(PSO), a particles swarm migrating algorithm(PSMA) was proposed to solve optimization problems under equality constrains and inequality constrains with adaptive adjustment of penalty function and leaders migration strategy. Through the standard functions tests, the PSMA algorithm shows higher convergence accuracy and faster convergence speed than other typical swarm intelligent algorithms. The PSC results of PSMA are much better than other swarm intelligent algorithms, and better than SQP algorithm in the minimum fuel consumption control and the minimum turbine temperature control both of which have equality constraints. The results demonstrate the feasibility of PSMA in optimization control for the variable cycle engine.