A hybrid control system has been proposed for compressor surge, which combines the active method with the passive method. A bleed valve was selected as the actuator in the proposed system. As a submode of the hybrid system, a fuzzy logic based active controller was designed to extend the stability operating range of the compressor. Meanwhile, a surge avoidance controller was used as a backup-mode to improve the safety performance of the system. The simulation results showed that the compressor can operate steadily outside the surge line under active control mode and can be dragged back to inside the surge line by the passive control mode when the alternative fails. One advantage of the proposed control system is that it does not need a model of the compressor, and it works on any compression system. Passive surge control is a reliable and widely applied method in industrial compressors. The hybrid system makes the active control approach closer to the industrial implementation.

In this paper, a fuzzy logic based volume flow control method is proposed to precisely control the force of a pneumatic actuator in an electro-pneumatic system including four on-off valves. The volume flow feature, which is the relationship between the duty cycle of the pulse width modulation (PWM) period, pressure difference, and volume flow of an on-off valve, is based on the experimental data measured by a high-precision volume flow meter. Through experimental data analysis, the maximum and minimum duty cycles are acquired. A new volume flow control method is introduced for the pneumatic system. In this method, the raw measured data are innovatively processed by a segmented, polynomial fitting method, and a newly designed procedure for calculating the duty cycle is adopted. This procedure makes it possible to combine the original data with fuzzy logic control (FLC). Additionally, the method allows us to accurately control the minimum and maximum opening pulse width of the valve. Several experiments are performed based on the experimental data, instead of the traditional theoretical models. Only 0.141 N (1.41%) overshoot and 0.03 N (0.03%) steady-state error are observed in the step response experiment, and 0.123 N average error is found while tracking the sine wave reference.

Propeller synchrophasing is an effective way of reducing interior noise and vibration of turboprop-driven aircraft. However, synchrophasing has achieved limited success in practice for the reason that the predetermined phase angles are not acoustically optimized for maximum noise reduction during all flight conditions. An investigation has been conducted out which includes two folds: first, the noise vector based on laboratory experimental data has been modeled and second, optimal phase to acquire minimum noise is obtained via optimization search. An improved identification method of vector noise model which can be less dependent to noise phase message is presented. Compared with traditional methods, this method can greatly reduce the real-time requirement between phase optimization model and control model or sound acquiring model, so it can eliminate the influence which communication delay brings on identification precision. A synchrophasing experimental platform is established to verify the vector noise modeling. It adopts two propellers-driven servo motors to simulate the interior noise environment of the aircraft. The influence of the date sampling condition on identification is also researched. Ant colony optimization with two improvements is applied to phase optimization of four propellers. Simulation results show that the improved algorithm requires much less calculation.