To carry out a scaled-model flight test of a high-gain aircraft with a proportional plus integral plus derivative (PID) flight control design, the similarity relations of the flight control law parameters of scaled-model and full-size aircraft must be systematically studied. In this article, the general similarity relations applicable to commonly used flight control law configurations and feedback signals are derived and analyzed. Based on the control principle, PID control parameters are divided into two types: feedback gains and series combined dynamic elements. The general similarity relations for the control parameters of these two types of elements are derived from system similarity theory. Finally, closed-loop flight control simulations of a fighter aircraft and its scaled model are completed. The simulation results show that the scaled-model and full-size aircraft with similar PID control law parameters are physically similar, validating the similarity relation conclusions proposed in this article.

The upset state is an unexpected flight state, which is characterized by an unintentional deviation from normal operating parameters. It is difficult for the pilot to recover the aircraft from the upset state accurately and quickly. In this paper, an upset recovery strategy and pilot assistance system (PAS) based on reinforcement learning is proposed. The man–machine closed-loop system was established and the upset state, such as a high angle of attack and large attitude angle, was induced. The upset recovery problem was transformed into a sequential decision problem, and the Markov decision model of upset recovery was established by taking the deflection change of the control surface as the action. The proximal policy optimization (PPO) algorithm was selected for the strategy training. The adaptive pilot model and the reinforcement learning method proposed in this paper were used to make the aircraft recover from the upset state. Based on the correspondence between the flight state, the recovery method, and the recovery result, the aircraft upset recovery safety envelopes were formed, and the four-level upset recovery PAS with alarm warning, coordinated control, and autonomous recovery modes was constructed. The results of the digital virtual flight simulation and ground flight test show that compared with a traditional single pilot, the aircraft upset recovery strategy, the upset recovery safety envelopes, and the PAS established in this study could reduce the handling burden of the pilot and improve the success rate and effect of upset recovery. This research has certain theoretical reference values for flight safety and pilot training.

High-precision control problems for carrier-based UAVs are challenging due to the requirements for safety, high-performance operation and uncertain ocean environments. To address such problems, this paper proposes a direct lift landing control method that can ensure the safe operation of UAVs using intelligent optimization of control performance indicators and dynamic optimal allocation methods. The direct lift control (DLC) scheme is adopted to improve the operability of the control by introducing flap channels to achieve the fast correction of vertical disturbances. To improve the landing control performance, an intelligent optimization method for DLC gain is proposed, and a neural network relationship between parameter uncertainty and optimal DLC gain is established. In addition, a recursive least-squares identification method is used to estimate the uncertain parameters in real time, so that the established neural network can be used to generate the optimal DLC commands online, and the generated control commands can be assigned to multiple actuators of the carrier-based UAV through a dynamic optimal assignment algorithm. Finally, the superiority of the method is verified using simulation comparison.

The stall aerodynamic model based on Kirchhoff’s theory of flow separation is widely used in the identification and modeling of stall aerodynamic parameters. However, it has two defects. First, its model structure is significantly different from the pre-stall model used for a small attack angle, meaning the identification results cannot be combined with the pre-stall model to form the full flight envelope model. Second, the pitching moment model, which is used in conjunction with the Kirchhoff lift model, cannot accurately describe the aircraft stall pitching moment characteristics. To ensure the compatibility of the two models, this paper proposes a method to determine some unknown parameters in the stall model. The mechanism for the pitching moment generation of the aircraft stall is analyzed, and two high-order correction terms are added to the pitching moment model to better describe the longitudinal stall aerodynamic characteristics. Based on the identification of aerodynamic parameters, a longitudinal stall aerodynamic modeling method used for the aircraft stall process is developed. The identification and simulation validation results based on the quasi-steady stall flight data of a civil aircraft show that the improved stall model can accurately describe the quasi-steady stall pitching moment. The established stall aerodynamic model can accurately characterize the longitudinal quasi-steady stall aerodynamic characteristics of aircraft under different stall degrees.

For aircraft employing the fly-by-wire technique, the closed-loop dynamic characteristics are determined by both the configuration design and the flight control system. As the capacity of the control system has certain limitations, the configuration parameters are also constrained by the requirements of the closed-loop flying qualities. This paper presents an aircraft configuration parameter boundaries determination method based on closed-loop flying qualities requirements independent of the actual flight control law design, mainly aiming at the parameters that affect the stability and control characteristics. First, a nonlinear dynamic inversion-based flight control law is adopted to decouple the control law gains from the configuration parameters and to study the relationship between the configuration parameters and closed-loop flying qualities. Second, a flying qualities evaluation scheme is established by selecting the most severe flight conditions and the evaluation criteria that are most sensitive to changes in the parameters. Finally, the parameter boundaries according to the requirements of Level 1 flying qualities are determined by searching for the critical values that lead to degradation of the flying qualities. The proposed method is verified by an application example of the design ranges of a sample aircraft’s wing position, horizontal tail area, center of gravity, vertical tail area and vertical tail position.

When considering the robust control of fixed-wing Unmanned Aerial Vehicles (UAVs), a conflict often arises between addressing nonlinearity and meeting fast-solving requirements. In existing studies, the less nonlinear robust control methods have shown significant improvements that parallel computing and dimensionality reduction techniques in real-time applications. In this paper, a nonlinear fast Tube-based Robust Compensation Control (TRCC) for fixed-wing UAVs is proposed to satisfy robustness and fast-solving requirements. Firstly, a solving method for discrete trajectory tubes was proposed to facilitate fast parallel computation. Subsequently, a TRCC algorithm was developed that minimized the trajectory tube to enhance robustness. Additionally, considering the characteristics of fixed-wing UAVs, dimensionality reduction techniques such as decoupling and stepwise approaches are proposed, and a fast TRCC algorithm that incorporates the control reuse method is presented. Finally, simulations verify that the proposed fast TRCC effectively enhances the robustness of UAVs during tracking tasks while satisfying the requirements for fast solving.