Chams Eddine Mballo
(Advisor: Prof. J.V.R. Prasad)
will propose a doctoral thesis entitled,
Model-Based Life Extending Control for Rotorcraft
Thursday, June 25 at 3:30 p.m.
In forward flight, as the helicopter's main rotor rotates and simultaneously advances, a very complex aerodynamic environment dominated by large dynamic loads is created. The large magnitude and high application rate of these loads are detrimental to many helicopter components as they are the main cause of premature fatigue failure. The failure of critical helicopter components can lead to catastrophic events. Many of those critical components are located in the rotor system which creates challenges for accurate real-time load monitoring of those components and hence obstructing the development of state-of-the-art control strategies for critical component life extension. This research aims at developing real-time algorithms for the estimation of component level dynamic loads which enable real-time load monitoring of critical rotor components and control strategies to alleviate/limit fatigue damage. Both components of this research are used for critical component life extension.
A nonlinear helicopter model with 33-inflow states and elastic blade representation is modeled in FLIGHTLAB®. The developed nonlinear model gives a suitable representation of the dynamic loads that the rotor system experiences. From the nonlinear model, a first order linear time periodic (LTP) model of coupled body/rotor/inflow dynamics is extracted by performing a linearization about a periodic equilibrium point. The LTP model is transformed into a linear time invariant (LTI) model using harmonic decomposition methodology. The obtained LTI model which has 1513 states is used for real-time estimation of the effect of control inputs on component harmonic loads in the rotating system, and hence, provides real-time load monitoring capability. The fidelity of the 1513 states LTI model is assessed in the frequency domain via comparison with flight test data. A model order reduction approach based on singular perturbation theory is used to reduce the 1513 states LTI model to a 10th order LTI model. The 10th order LTI model retains relevant physical states information and the fidelity of the dynamic load prediction of the 1513 states LTI model.
Using the reduced order LTI model, two component load limiting strategies to limit fatigue damage are pursued. The first one is based on a receding horizon model predictive control while the second one is based on active rotor control. In both approaches, component life extension is achieved by directly limiting fatigue life usage associated with harmonic loads. In the receding horizon model predictive control formulation, an optimal control problem is formulated where given a desired user defined maximum harmonic load limit, the estimate of control margin associated with the component load limit is found and used in the form of pilot cueing/automatic limiting to prevent the component harmonic load from exceeding the max limit. In this approach, the use of the reduced order LTI model is twofold. The component harmonic load estimation from the reduced order LTI model is used in the detection of limit violation. Furthermore, the reduced order LTI model is used to generate a mapping between limit and control margin. Subsequently, the component load limiting scheme via model predictive control is integrated within a nonlinear flight controller. The synthesis of an integrated flight and component load limiting controller is achieved via both command limiting and control limiting architectures. The resultant flight controllers obtained from this synthesis are used to understand the trade-off between maneuver performance and component load limiting through extensive linear and nonlinear model simulations.
The proposed future work is then focused on the design of a component load limiting scheme based on active rotor control. The development of a closed loop load limiting controller using individual blade control will be developed using the reduced order LTI model. Furthermore, the performance of the obtained controller will be tested using batch and piloted simulations. Finally, we will compare the two proposed life extending control schemes in terms of their performance and impact on vehicle handling qualities.
- Prof. J.V.R. Prasad – School of Aerospace Engineering (advisor), Georgia Institute of Technology
- Prof. Mark F. Costello– School of Aerospace Engineering, Georgia Institute of Technology
- Prof. Joseph F. Horn – School of Aerospace Engineering, Pennsylvania State University