Thrust estimator design based on least squares support vector regression machine

In order to realize direct thrust control instead of traditional sensor-based control for aero-engines,it is indispensable to design a thrust estimator with high accuracy,so a scheme for thrust estimator design based on the least square support vector regression machine is proposed to solve this problem. Furthermore,numerical simulations confirm the effectiveness of our presented scheme. During the process of estimator design,a wrapper criterion that can not only reduce the computational complexity but also enhance the generalization performance is proposed to select variables as input variables for estimator.

INVESTIGATION ON THE APPLICATION OF THE BOUNDARY ELEMENT METHOD TO THE SPILL GROOVED THRUST BEARING

An application of the boundary element method (BEM) is presented to calculate the behaviors of a spiral grooved thrust bearing (SGTB). The basic reason is that the SGTB has very complex boundary conditions that can hinder the effective or sufficient applications of the finite difference method (FDM) and the finite element method (FEM), despite some existing work based on the FDM and the FEM. In other to apply the BEM, the pressure control equation, i. e., Reynolds' equation, is first transformed into Laplace's and Poisson's form of the equations. Discretization of the SGTB with a set of boundary elements is thus explained in detail, which also includes the handling of boundary conditions. The Archimedean SGTB is chosen as an example of the application Of BEM, and the relationship between the behaviors and structure parameters of the bearing are found and discussed through this calculation. The obtained results lay a solid foundation for a further work of the design of the SGTB.

PTVC-M for Ultra-Agile VTOL and 300+ km·h-1 Cruising

There remains a need to develop improved VTOL techniques that are cost-effective and with minimum compromise on cruising flight performance for fixed-wing aircraft. This work proposes an elegant VTOL control method known as PTVC-M (pitch-axis thrust vector control with moment arms) for tailsitters. The hallmark of the approach is the complete elimination of control surfaces such as elevators and rudder. Computer simulations with a 1580 mm wing span airplane reveal that the proposed technique results in authoritative control and unique maneuverability such as inverted vertical hover and stall-spin with positive climb rate. Zero-surface requirement of the PTVC-M virtually eliminates performance tradeoffs between VTOL and high-speed flight. In this proof-of-concept study, the VTOL-capable aircraft achieves a VH of 360 km·h-1 at near sea-level. The proposed technique will benefit a broad range of applications including high-performance spinsonde that can directly measure 10-m surface wind, tropical cyclone research, and possibly serving as the cornerstone for the next-generation sport aerobatics.

Reduced-dimensional MPC controller for direct thrust control

With the development of the aircraft gas turbine engine, a control system should be able to achieve effective thrust control to gain better operability. The main contribution of this paper is to develop a novel direct thrust control approach based on an improved model predictive control method through a strategy that reduces the dimension of control sequence. It can not only achieve normal direct thrust control tasks but also maximize the thrust level within the safe operation boundaries. Only the action of switching the objective functions is required to achieve the switch of these two thrust control modes while there is no modification to the control structure. Besides,a shorter control sequence is defined for multivariable control by updating only one control variable at every simulation time instant. Therefore, the time requirement for the solving process of the optimal control sequence is reduced. The proposed controller is implemented to a twin-spool engine.Simulations are conducted in the wide flight envelope, and results show that the average timeconsumption can be reduced up to 65% in comparison with the standard model predictive control,and the thrust can be increased significantly when maximum thrust mode is implemented by using engine limit margins.

Direct thrust control for multivariable turbofan approach

A novel turbofan Direct Thrust Control(DTC)architecture based on Linear ParameterVarying(LPV)approach for a two-spool turbofan engine thrust control is proposed in this paper.Instead of transforming thrust command to shaft speed command and pressure ratio command,the thrust will be directly controlled by an optimal controller with two control variables.LPV model of the engine is established for the designing of thrust estimator and controller.A robust LPV H∞filter is introduced to estimate the unmeasurable thrust according to measurable engine states.The thrust estimation error system is proved to be Affinely Quadratically Stable(AQS)in the whole parameter box with a prescribed H∞performance indexγ.Due to the existence of overdetermined equations,the solving of controller parameters is a multi-solution problem.Therefore,Particle Swarm Optimization(PSO)algorithm is used to optimize the controller parameters to obtain satisfactory control performance based on the engine’s LPV model.Numerical simulations show that the thrust estimator can acquire smooth and accurate estimating results when sensor noise exists.The optimal controller can receive desired control performance both in steady and transition control tasks within the engine working states above the idle,verifying the effectiveness of the proposed DTC architecture’s application in thrust direct control problem.

Neural network-based model predictive control with fuzzy-SQP optimization for direct thrust control of turbofan engine

A nonlinear model predictive control method based on fuzzy-Sequential Quadratic Programming(SQP)for direct thrust control is proposed in this paper for the sake of improving the accuracy of thrust control.The designed control system includes four parts,namely a predictive model,rolling optimization,online correction,and feedback correction.Considering the strong nonlinearity of engine,a predictive model is established by Back Propagation(BP)neural network for the entire flight envelope,whose input and output are determined with random forest algorithm and actual situation analysis.Rolling optimization typically uses SQP as the optimization algorithm,but SQP algorithm is easy to trap into local optimization.Therefore,the fuzzy-SQP algorithm is proposed to prevent this disadvantage using fuzzy algorithm to determine the initial value of SQP.In addition to the traditional three parts of model predictive control,an online correction module is added to improve the predictive accuracy of the predictive model in the predictive time domain.Simulation results show that the BP predictive model can reach a certain degree of predictive accuracy,and the proposed control system can achieve good tracking performance with the limited parameters within the safe range。

SIMULATION RESEARCH OF ACTIVE VIBRATION CONTROL FOR ELASTIC MISSILE WITH SWING NOZZLE THRUST VECTOR CONTROL

Aiming at the deficiencies of notch filters on the aspect of vibration suppression for elastic missile with swing nozzle thrust vector control(SNTVC),an active vibration controller(AVC)is proposed.It is composed of an optimal state feedback controller(OSFC)and an optimal minimal order state observer(OMOSO),which can be respectively designed based on the separation principle.The design rules of these two elements are successively given.Computer simulation results present that AVC can realize strong vibration suppression and good convergence property after disturbing.Moreover,it has simple design and then it is easily implemented in engineering.In addition,the AVC scheme can also resolve the poor system stability to a great extent,which is resulted from the bad static stability of missile body.