Browsing by Author "Yang, Congjie"

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    Disturbance observer-based backstepping terminal sliding mode aeroelastic control of airfoils
    (MDPI, 2024-10-25) Liu, Shiqian; Yang, Congjie; Zhang, Qian; Whidborne, James F
    This paper studies aeroelastic control for a two-dimensional airfoil–flap system with unknown gust disturbances and model uncertainties. Open loop limit cycle oscillation (LCO) happens at the post-flutter speed. The structural stiffness and quasi-steady and unsteady aerodynamic loads of the aeroelastic system are represented by nonlinear models. To robustly suppress aeroelastic vibration within a finite time, a backstepping terminal sliding-mode control (BTSMC) is proposed. In addition, a learning rate (LR) is incorporated into the BTSMC to adjust how fast the aeroelastic response converges to zero. In order to overcome the fact that the BTSMC design is dependent on prior knowledge, a nonlinear disturbance observer (DO) is designed to estimate the variable observable disturbances. The closed-loop aeroelastic control system has proven to be globally asymptotically stable and converges within a finite time using Lyapunov theory. Simulation results of an aeroelastic two-dimensional airfoil with both trailing-edge (TE) and leading-edge (LE) control surfaces show that the proposed DO-BTSMC is effective for flutter suppression, even when subjected to gusts and parameter uncertainties.
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    Neural network observer based LPV fault tolerant control of a flying-wing aircraft
    (IEEE, 2023-11-30) Liu, Shiqian; Lyv, Weizhi; Yang, Congjie; Wang, Feiyue; Whidborne, James F.
    For the problem of fault tolerant trajectory tracking control for a large Flying-Wing (FW) aircraft with Linear Parameter-Varying (LPV) model, a gain scheduled H ∞ controller is designed by dynamic output feedback. Robust synthesis of this gain scheduled H ∞ control is carried out by an affine Parameter Dependent Lyapunov Function (PDLF). The problem of trajectory tracking control for the LPV plant is transformed into solving an infinite number of linear matrix inequalities by the PDLF design, and the linear matrix inequalities are solved by convex optimization techniques. To overcome model uncertainties due to linearization and external disturbances, a radial basis function neural network disturbance observer is proposed, and to estimate actuator faults, an LPV fault estimator is designed. Furthermore, a composite controller is proposed to realize fault tolerant trajectory tracking control, which combines the LPV control with the fault estimator and disturbance observer, as well as an active-set based control allocation to avoiding actuator saturation. The approach is tested by simulation of two scenarios that show responses of the altitude, speed and heading angle to (i) unknown disturbances and (ii) actuator faults. The results show that the proposed neural network observer based LPV control has better performances for both disturbance rejecting and fault-tolerant trajectory tracking.