Search

The interference calculation is essential to the flight dynamic analysis especially for multi-rotors configurations. To analyze the flight dynamic characteristics of a small tandem helicopter precisely, a vortex method is utilized to obtain the aerodynamic interaction between the tandem rotors and the fuselage. Specially, the unsteady air loads and the wake of the rotors are developed using a lifting surface method and the viscous vortex particle theory, respectively, and the fuselage is modeled by the panel method to simulate the blocking effect on the rotors. Then the aerodynamic interference of the small tandem helicopter is analyzed under the conditions of different vertical or horizontal distance between the rear and front rotors. Subsequently, to save calculation time during flight dynamic analysis, a hybrid optimization trimming method combining the equilibrium optimizer and the improved delta method is proposed. At last, the flight dynamic analysis for the small tandem helicopter with different configurations are carried out and the results indicate that configuration in which the rear rotor is located higher than the front rotor and the one with larger longitudinal distance between tandem rotors are beneficial to increase the stability in lateral and longitudinal directions, respectively.

To achieve the three-dimensional free movement of the slung load, a load-leading hierarchical control strategy has been adopted recently which divides the cooperative multi-lift system into a load layer, a cable layer, and an aircraft layer. But there exists a non-convex optimization problem in the cable layer when computing the force of each cable, and more control difficulties of the aircraft due to the additional disturbances resulting from the load movement. To solve these problems, an application of the social spider optimization (SSO) algorithm and the improved active disturbance rejection controller (IADRC) in hierarchical control of cooperative multi-lift with four unmanned helicopters is proposed in this study. First, the unmanned helicopters as well as the load are modeled. Then the three layers mentioned above are designed, respectively. Specifically, an optimization method combining SSO with the MATLAB/fmincon function is proposed to solve the non-convex problem in the cable layer. And within the unmanned helicopter layer, the fuzzy theory is introduced into the nonlinear error feedback control strategy of the traditional active disturbance rejection controller (ADRC) to realize the control of the unmanned helicopter. At last, some simulations are carried out, and the results indicate that the system has higher calculation efficiency, smaller steady-state error, and better adaptability to trajectory change or load release with the designed hierarchical control strategy.

Unmanned helicopters are widely used in military and civil fields. One of the most important applications is flying with an underslung load, but the pendulum-like behavior of the load can cause damage or even forced landing to the helicopter. To solve this problem, a control strategy to stabilize the helicopter/load system based on active disturbance rejection control (ADRC) and improved sliding mode control (ISMC) algorithms is proposed in this paper. First, the helicopter/load system is modelled using Newton-Euler equations according to the multi-body dynamics theory. Then a manipulation strategy which can reduce the swing angle of the load and an overall control strategy for the helicopter/load system are presented. Specifically, ADRC is applied to attitude control due to its ability to regard the pendulum-like behavior as the internal uncertainties of the system, meanwhile ISMC to position control. Within ISMC, two sliding surfaces with adjustable weights are constructed by employing the position of the helicopter as well as the swing angle of the load. In addition, a real-time beetle antennae search algorithm is designed to online modify the weights by taking the minimum error at current time as the optimization objective. Besides, the radial basis function neural network is introduced to approach the uncertainty coefficients considering the system’s complexity. At last, relevant simulations are carried out and the results indicate that the system is capable of not only controlling the attitude and position of the helicopter precisely but also stabilizing the underslung load rapidly with ADRC and ISMC.

Quad tilt-rotor(QTR) UAV is a nonlinear time-varying system in full flight mode. It is difficult and inaccurate to model the nonlinear time-varying system, which cannot fully reflect the problem of controlling input and system response output in the full flight mode. In order to solve the above problems, a novel neural network model was adopt to identify the nonlinear time-varying system of quad tilt-rotor in full flight mode. An adaptive learning rate algorithm based on foraging strategy is proposed based on the global error BP neural network. Corresponding to the nonlinear time-varying system, BP neural network is set as the time-invariant system structure with constant network structure and continuously changing weights at multiple times, and the nonlinear input-output relationship under the time-varying system is jointly described by fitting the network at all times. The extended Kalman filtering algorithm is used to track the network connection weights by modifying the network weights at the current moment with the input and output data at the next moment. The final identification result shows that the smaller mean square error of both only transition process and full flight mode, shows that using this optimization algorithm can well describe the input and output characteristics of the nonlinear time-varying systems. When the same network structure is adopted, no matter for transition mode or full mode, the BP optimization algorithm based on foraging strategy is better than the global BP algorithm for system identification of the full mode quad tilt-rotor. Therefore, when the BP neural network based on foraging strategy is adopted, the same network structure can be adopted to systematically identify the full mode of quad tilt-rotor by changing the weight.

The tilt quad rotor (TQR) has the problem of manipulation redundancy due to the aerodynamic structure changing in conversion mode. The tilting path is limited by the conversion corridor. In order to solve the problem of manipulation redundancy in conversion mode and find out the optimal tilting path in conversion corridor, the aerodynamic model of the TQR based on Goldstein vortex theory is established to obtain the manipulation derivative matrix and conversion corridor. A novel manipulation strategy is proposed, the altitude, forward velocity and tilt angle are introduced into the manipulation strategy to ensure the stability of the altitude and attitude in conversion process. To find out the optimal tilting path in conversion corridor, a novel tilting strategy is proposed based on Ant Colony Optimization (ACO) algorithm and compared with another three tilting path. To verify the credibility of the flight dynamics model, the effectiveness of manipulation strategy and tilting path optimization, the simulation and flight test were carried out. The simulation and flight test results show that the manipulation strategy proposed in this paper can solve the manipulation redundancy in conversion mode very well, and the proposed tilting path can ensure the stability of the altitude and attitude in conversion corridor.

To solve the problem of manipulation redundancy and coupling in transition mode of tilt quad rotor, this paper studied the manipulation strategy in transition mode, and carried out the design of the attitude controller based on active disturbance rejection control (ADRC) with sliding mode control in nonlinear state error feedback (NLSEF). According to the characteristics of flight in transition mode, the rudders and propellers were assigned different control rights. The differential output of the tracking differentiator was used as the attitude angular rate instruction to simplify the structure of the attitude controller. Extended state observer was used to estimate and compensate internal and external uncertainties. The sliding mode control in NLSEF was used to improve response speed of the controller. Through the flight control simulation and flight test of the tilt quad rotor, the validity of the control system and the rationality of the manipulation strategy were verified.

Helicopters have unique characteristics enable it to flywith an underslung load in many civil and military operations. But the slung load’s pendulum-like behaviour makes it a highly hazardous and notoriously difficult task which will reduce the helicopter’s flight envelope. To eliminate the slung load’s pendulum-like behaviour, this paper discusses a control strategy for helicopters with slung load by combining Active Disturbance Rejection Control (ADRC) and Input Shaper Technology. The motion of the helicopter/load complex was modeled by the Newton-Euler equations in terms of generalized coordinates and velocities. This mathematical model was then used in conjunction with the control strategy to stabilize the helicopter/load complex. The control results by combining ADRC and Input Shaper Technology were compared with the PID control, and the improvements related to eliminate the slung load’s pendulum-like behaviour were significant.

Improve the efficiency of propulsion system is an effective mean to archive flight performance improvement of electric-powered tilt-rotor. In this paper, the motor is constructed by combining the motor equivalent circuit model and the positive polynomial loss model. The proprotor is modeled by Goldstein vortex theory and the validity is verified. Based on this, aimed at an effective optimization goal, a comprehensive optimization method for the propulsion system is proposed using optimization algorithm. Then the optimization of the propulsion system was carried out and an effective optimization program was obtained for a small electric-powered tilt quad rotor. The research results show that this optimization method can effectively solve the problem of motor and proprotor matching. By optimizing the design of the propulsion system, the power demand can be effectively reduced and the flight performance can be improved.