Research On Fidelity Of Motion Cueing System In Flight Simulator

As a semi-physical simulated device, flight simulator may realistically simulateflight. It not only plays an important pole in the research on flight performance anddevelopment of new aircraft, but also gets the potential economic benefits on flighttraining. The technologies of flight simulator in our country quite fall behind theoversea level, specially the low fidelity of motion cueing system in flight simulatorbecause of the difficulty of objectively assessing fidelity of motion cueing system.Aiming at the problem that the current objectively assessing method is limited inapplication, the outputs of pilot’s control behavior considering as an assessing targetis applied for the objective assessment process about fidelity of motion cueingsystem. To improve fidelity of motion cueing system, the coordination washoutalgorithm is optimized based on objective assessment results.After analysizing the characteristics of objective assessment on fidelity ofmotion cueing system, the power spectrum of output of pilot’s control behavior isregarded as assessment target based on the definition of fidelity of motion cueingsystem. The model of aircraft dynamic according to flight tasks simulation is given,and also, the6-DOD motion platform is integrated modeled. To verify assessmenttarget, the systems of pilot-aircraft and pilot-simulator are modeled for objectiveassessment method. The contrast results indicate that it is correct and universal toassessing the fidelity of motion cueing system by the power spectrum of outputsignals of pilot’s control behavior.Pilot’s control behavior is modeled according to external behaviorcharacteristic and physiological feature. As a precondition, principle of perceivingand processing exterior information is analyzed. Considering lead, lag and delayactions, the pilot’s visual system is firstly modeled by control method. Secondly, thepilot’s vestibular system is model due to structural similarity between vestibularorgans and mass-spring-damper, and meanwhile the pilot’s neuromuscular system ismodel due to its driving function. Finally, these above models reflecting pilot’scontrol behavior are integrated. The experimental results reveal that the model cancorrectly reflect pilot’s control behavior in real flight.The model parameters must be identified after pilot’s control behavior ismodeled. In order to correctly explanting the pilot’s control behavior by parameters,pilot’s behavior adapting to flight dynamics is considered in parameters identifyingprocess. To eliminate noise in datum for identification, the datum are preprocessedby method which consist of outliers searching, outliers complementing andsmoothing. And then arming at uncertainty of identification results when the solution is local converged, a particle swarm optimization method based on chaoticsearch is used to identify model parameters. Finally it is test that the identificationresults are correct in climbing flight task.The parameter values of coordination washout algorithm are got. Parameters ofwashout algorithm are still got by experience until now, and the experiential methodleads to low fidelity of motion cueing system. After constitution of co-ordinatedwashout algorithm are in detail analyzed, the parameters are initialized according toSinacori criterion and adjusted according to objective assessment results of motioncueing system fidelity. The simulation results reveal that the method can improvefidelity of motion cueing system.Finally, this research is tested by6-DOF motion platform and equipment forstudy on the flight simulator key technique in three flight tasks which consist oftaking off, langding and cruise. The test objectives comprise objectively methodused for assessing fidelity of motion cueing system, pilot’s control behavior modeland parameters identification, and coordination washout algorithm.