# Dynamic Modeling and Altitude Control for Flying Cars Based on Active Disturbance Rejection Control
###### Abstract  
Flying cars offer huge advantages due to their deformable structure, which can adapt to external environments and mission requirements. They represent a novel system that can realize vertical takeoff and landing. However, the structure of a flying car is complicated, placing higher requirements on modeling accuracy and control effectiveness. Thus, in this paper, a dynamic model of a flying car is proposed by combining a car body, motor, and propellers. Then, a double-loop controller based on active disturbance rejection control is proposed to accurately control its flight altitude. Utilizing the extended state observer, external wind and other disturbances are regarded as an extended state, which can be dynamically observed and compensated to significantly improve tracking accuracy. The effectiveness of the proposed controller is validated through detailed simulations and flight experiments. The proposed controller significantly improves control accuracy and disturbance rejection capability. flying car; active disturbance rejection control; propeller model; hovering control; altitude control +
Footnote †: journal: Applied  
0000-0001-9993-3227][PERSON]  
0000-0001-9993-3227][PERSON]  
0000-0002-0002-3327-3270][PERSON]  
0000-0002-327-3270][PERSON]  
0000-0002-3270-3270][PERSON]  
0000-0002-3270-327  
Ref. [20] built a dynamic model of a flying car with four contra-rotating propeller units. A moving computational domain method was also designed to track the reference trajectory. Besides the modeling method, the control and simulation problem of flying cars is also an important issue. Ref. [21] optimized the airframe of flying cars for medical emergencies. Ref. [22] proposed the concept of rectangular-shaped unmanned surveillance flying cars and designed an adaptive fuzzy algorithm. Ref. [23] tested the takeoff and landing performance of flying cars in a wind tunnel. Ref. [24] proposed a nonlinear controller for both the position and attitude of flying cars. A strategy was also presented to avoid saturation of the distributed propulsion control inputs. Ref. [25] built a 6-DOF model by considering the interaction between the fluid and rigid body and conducted a numerical simulation of the flying car in a sudden rotor-stop scenario. Ref. [26] designed a hierarchical control strategy for flying cars with two models: one for ground operation and one for aerial operation. The proposed method can realize accurate tracking control and improve fuel economy. Ref. [27] explored a method for a new VTOL-propelled wing design for flying cars. Ref. [28] proposed a marker-based 3D position-prediction algorithm to predict the trajectory of flying cars in two modes. Ref. [29] designed a novel flight control system for flying cars based on [PERSON]'s principle. Based on the above discussion, it can be seen that current research tends to focus more on the 'flight' aspect of flying cars, especially in the vertical takeoff and landing stages. However, the aerodynamic characteristics of flying cars are more complicated. There is also relatively less consideration for disturbances, with most studies limited to investigating their nonlinear characteristics and designing nonlinear controllers, leading to insufficient disturbance resistance. For this reason, in this paper, we focus on the altitude control of the flying car during the flight portion. Firstly, the model of the flying car is proposed. The model consists of an unmanned vehicle body, motor, and propellers, enabling accurate simulation of the dynamic characteristics of a flying car. It provides a viable testing platform for controller design and controller parameter tuning. Meanwhile, a double-loop controller based on active disturbance rejection control (ADRC) is designed to accurately control its flight altitude. The double-loop controller is applied to control the rotation speed of the motor and the flight altitude. ADRC was originally designed by [PERSON] [30]. Refs. [31; 32; 33; 34; 35] also explored nonlinear ADRC and presented stability proofs.