6-DOF Modeling and 3D Trajectory Tracking Control of a Powered Parafoil System

Abstract

The powered parafoil system is obtained by adding the propeller thrust to the unpowered parafoil system, and has coupling and nonlinear characteristics, which make its precise control more difficult than that of the unpowered parafoil system. To achieve the trajectory tracking control of the powered parafoil system in the field of precision airdrop, a mathematical model of the 6-DOF of the powered parafoil system is established first. Then, a new trajectory tracking strategy is proposed, which can overcome the limitations of the traditional guidance-based trajectory tracking strategy. We design lateral, longitudinal, and velocity controllers on the basis of the motion characteristics of the powered parafoil system. Then, we adopt the widely used PID control strategy in engineering. In response to the difficult of the PID controller parameter tuning of the powered parafoil system, we achieve the PID controller parameter tuning with the ecosystem particle swarm optimization (ESPSO) of the swarm intelligence optimization algorithm. The effectiveness of the algorithm is verified by simulation experiments. Results show that the proposed algorithm can obtain high trajectory tracking accuracy even when a deviation in the initial state and a random gust wind disturbance in the outside world occur regardless of the method of the multiphase homing or the optimal control homing adopted. The proposed trajectory tracking strategy also has strong robustness and adaptability.

Dynamics Modeling and Autonomous Landing for Flexible Parafoil-Vehicle Multibody System

“…The mass of the suspension line is unconsidered, thus the line tension F a s acting on the aircraft is opposite to the tension F p i s on the canopy. The calculation of the moment M a s is similar to the procedure in (18) and (20).…”

“…To correct directional errors, Prakash and Ananthkrishnan [19] designed a controller using the nonlinear dynamic inversion method and kept longitudinal and lateral loops open given the natural pendulum stability of the parafoil. Other traditional control methods were used for the parafoil [20], [21], [22], including proportional-integralderivative (PID) control with parameter optimization, model predictive control, etc. Gockel [23] discovered that the deviation from the planned path is mostly caused by the wind prediction error rather than the observation error and delay of the flight state within a certain range.…”

An intelligent control for reducing third-party interference in oil and gas pipeline using Deep Q-Networks (DQN)

“…Author [7] performed an extensive risk assessment of a submerged pipeline transporting LNG through the integration of the fuzzy approach alongside the bow-tie approach. Li et al [8] designed three proportional-integral-derivative (PID) controllers for the lateral motion, longitudinal motion, and velocity on the basis of the motion characteristics of the parafoil system, which overcame the limitations of the traditional guidance-based tracking strategy. As for actual airdrop scenarios, the PID controller still occupies a dominant position, but the PID controller cannot achieve high tracking accuracy, especially under the disturbances of a complex environment.…”

Intelligent Trajectory Tracking Linear Active Disturbance Rejection Control of a Powered Parafoil Based on Twin Delayed Deep Deterministic Policy Gradient Algorithm Optimization

“…There are very few research results on parafoil trajectory tracking control. Li et al [15] transformed tracking errors into guidance commands for the yaw angle and glide slope angle and employed PID controllers to achieve trajectory tracking control. For a powered parafoil without forward thrust, we proposed a new guidance law and initially realized trajectory tracking control [16].…”