Traditional active flutter suppression controllers are designed based on model. However, as the aircraft becomes more and more powerful, the modeling of aeroelastic system becomes difficult and the model-free requirement of controller design becomes more and more urgent. The complexity of industrial processes has brought about massive operational data generated online. Aviation industry development has entered the era of big data. Breaking through the traditional theoretical framework, mining the correlation, evolution and dynamic characteristics of the system from the data is the inevitable choice to meet this demand. In this paper, a data-driven model-free controller is designed, which relies on ridge regression of the input and output variation at each operating point of the closed-loop controlled system to recursively derive the iterative format of the control signals and ensure the numerical stability of the signals. The controller can only use the real-time measurement of the system’s online input and output data for continuous correction, to achieve the purpose of flutter suppression. Then flutter suppression of a three-degree-of-freedom binary wing with a control surface is studied, and the superiority of model-free controller is demonstrated by comparing it with the optimal controller.

Control laws for implementing active flutter suppression are generally derived from linear aeroelastic models. In this paper, families of control laws for implementing an active flutter suppression system were initially designed using linearised aeroelastic models based on the doublet lattice method after ignoring the aerodynamic loads associated with relatively faster time scales. Using these preliminary sets of control laws and the nonlinear transonic small disturbance theory, near-optimum control laws were chosen in the transonic domain to maximally increase the flutter speed of a typical aircraft wing by at least 16% or more. Thus it is shown that it is feasible to systematically design near-optimal control laws for active flutter suppression using computational models in transonic flow. The doublet lattice method coupled with the zeroth-order matrix Padé approximant provided the fastest method for synthesising a large number of preliminary control laws. The methodology was successfully demonstrated by applying it to two benchmarking examples.