Jangho Lee

Autopilot design of tilt-rotor UAV using particle swarm optimization method

This paper describes an autopilot design of tilt-rotor UAV, which is being developed by KARI as a Smart UAV Development Program in Korea, using particle swarm optimization (PSO) method. The tilt-rotor UAV considered in this paper holds five control modes in the stability and control augmentation system (SCAS) depending on flight mode. Flight control systems designed via the classical approach have been performed in such a way that yields linear models about several trim flight conditions, designing linear controllers for each condition, and integrating these design points with a gain scheduling scheme. However, it is very tedious and time-consuming to design an autopilot of a tilt-rotor UAV which represents various dynamic characteristics, nonlinearity, and uncertainty via classical control technique, because there are many design points and operating conditions throughout the flight envelope. To solve this problem, an automatic tool for control system design using PSO method is developed and applied to autopilot design of tilt-rotor UAV. The desired output of control system is chosen to satisfy the control system requirement. Gain margin and phase margin of control system are additionally considered as a penalty term in the objective function. The designed control system guarantees the satisfaction of the control system requirement ensuring a sufficient stability margin of the control system. Also, the gain scheduling scenario and SCAS switching logic of each control mode are successfully designed. Fully nonlinear 6-DOF simulation for an automatic landing scenario is performed to verify the performance of autopilot system of tilt-rotor UAV. The results from the nonlinear simulation show good control performance of the tilt-rotor UAV.

Control system design and testing for a small‐scale autonomous helicopter

Purpose – The purpose of this paper is to conduct the design, development and testing of a controller for an autonomous small‐scale helicopter.Design/methodology/approach – The hardware in the loop simulation (HILS) platform is developed based on the nonlinear model of JR Voyager G‐260 small‐scale helicopter. Autonomous controllers are verified using the HILS environment prior to flight experiments.Findings – The gains of the multi‐loop cascaded control architecture can be effectively optimized within the HILS environment. Various autonomous flight operations are achieved and it is demonstrated that the prediction from the simulations is in a good agreement with the result from the flight test.Research limitations/implications – The synthesized controller is effective for the particular test‐bed. For other small‐scale helicopters (with different size and engine specifications), the controller gains must be tuned again.Practical implications – This work represents a practical control design and testing pro...

Fault Tolerant Control of Hexacopter for Actuator Faults using Time Delay Control Method

A novel attitude tacking control method using Time Delay Control (TDC) scheme is developed to provide robust controllability of a rigid hexacopter in case of single or multiple rotor faults. When the TDC scheme is developed, the rotor faults such as the abrupt and/or incipient rotor faults are considered as model uncertainties. The kinematics, modeling of rigid dynamics of hexacopter, and design of stability and controllability augmentation system (SCAS) are addressed rigorously in this paper. In order to compare the developed control scheme to a conventional control method, a nonlinear numerical simulation has been performed and the attitude tracking performance has been compared between the two methods considering the single and multiple rotor faults cases. The developed control scheme shows superior stability and robust controllability of a hexacopter that is subjected to one or multiple rotor faults and external disturbance, i.e., wind shear, gust, and turbulence.

Development of a Reconfigurable Flight Controller Using Neural Networks and PCH

This paper presents a neural network based adaptive control approach to a reconfigurable flight control law that keeps handling qualities in the presence of faults or failures to the control surfaces of an aircraft. This approach removes the need for system identification for control reallocation after a failure and the need for an accurate aerodynamic database for flight control design, thereby reducing the cost and time required to develope a reconfigurable flight controller. Neural networks address the problem caused by uncertainties in modeling an aircraft and pseudo control hedging deals with the nonlinearity in actuators and the reconfiguration of a flight controller. The effect of the reconfigurable flight control law is illustrated in results of a nonlinear simulation of an unmanned aerial vehicle Durumi-II.

Reconfiguration Control Using LMI-based Constrained MPC

In developing modern aircraft, the reconfiguration control that can improve the safety and the survivability against the unexpected failure by partitioning control surfaces into several parts has been actively studied. This paper deals with the reconfiguration control using model predictive control method considering the saturation of control surfaces under the control surface failure. Linearized aircraft model at trim condition is used as the internal model of model predictive control. We propose the controller that performs optimization using LMI (linear matrix inequalities) based semi-definite programming in case that control surface saturation occurs, otherwise, uses analytic solution of the model predictive control. The performance of the proposed control method is evaluated by nonlinear simulation under the flight scenario of control surface failure.

Experimental Evaluation of Model-free Hybrid Fault Detection and Isolation

This paper deals with a model-free hybrid fault detection and isolation scheme subject to sequential triple faults in inertial measurement sensors. An additional small-sized and lowcost inertial measurement unit is added to the original inertial measurement unit of the UAV system. The parity space method and inline monitoring method are combined to increase the tolerance to sequential multiple faults in the skew-configured inertial measurement system. The first and the second sensor faults are detected and isolated by the parity space method. The third sensor fault is detected and isolated by the parity equation and the inline monitoring method based on the discrete wavelet transform. Hardware in-the-loop simulation test and the flight experiments were performed to verify the performance of the proposed fault diagnosis scheme.