Fault detection, isolation, and reconfiguration (FDIR) is an important and challenging problem in many engineering applications and continues to be an active area of research in the control community. This paper presents a survey of the various model-based FDIR methods developed in the last decade. In the paper, the FDIR problem is divided into the fault detection and isolation (FDI) step, and the controller reconfiguration step. For FDI, we discuss various model-based techniques to generate residuals that are robust to noise, unknown disturbance, and model uncertainties, as well as various statistical techniques of testing the residuals for abrupt changes (or faults). We then discuss various techniques of implementing reconfigurable control strategy in response to faults.

The analytic solution for the time-to-go of the pure proportional navigation guidance law against a stationary target is derived considering full nonlinear engagement kinematics without near-collision course approximation. The solution is globally exact for all flying directions with respect to the target and is generally exact for all possible values of the guidance gain. The time-to-go solution is used to design an almost-globally asymptotically stable guidance law for intercepting a stationary target with the impact time constraint. The impact-time-control guidance law is designed based on the pure proportional navigation guidance law with a modified nonlinear time-varying guidance gain. The proposed impact-time-control guidance law does not have the drawbacks of the existing impact-time-control guidance laws, such as a narrow capture zone, a limited set of feasible initial conditions, restricted achievable impact time, singularity, and nonzero terminal lateral acceleration command. Numerical simulations are performed to support the theoretical findings and to demonstrate the performance of the proposed method.

Nonlinear guidance laws that consider impact time constraints are proposed. Two-dimensional and three-dimensional impact time control guidance laws are derived using Lyapunov stability theory. Under the consideration of the nonlinear kinematics, it is shown that the missile states converge to the desired equilibrium point by the Lyapunov stability theory. The singularity issue of the proposed guidance laws is also analyzed. Numerical simulations are performed to verify the performance of the proposed guidance laws.

A new parameter estimation method is proposed in the framework of composite model reference adaptive control for improved parameter convergence without persistent excitation. The regressor filtering scheme is adopted to perform the parameter estimation with signals that can be obtained easily. A new framework for residual signal construction is proposed. The incoming data are first accumulated to build the information matrix, and then its quality is evaluated with respect to a chosen measure to select and store the best one. The information matrix is built to have full rank after sufficient but not persistent excitation. In this way, the exponential convergence of both tracking error and parameter estimation error can be guaranteed without persistent oscillation in the external command, which drives the system. Numerical simulations are performed to verify the theoretical findings and to demonstrate the advantages of the proposed adaptation law over the standard direct adaptation law.

Collision avoidance strategies for multiple unmanned aerial vehicles (UAVs) based on geometry are investigated in this study. The proposed strategies allow a group of UAVs to avoid obstacles and separate if necessary through a simple algorithm with low computation by expanding the collision-cone approach to formation of UAVs. The geometric approach uses line-of-sight vectors and relative velocity vectors where dynamic constraints are included in the formation. Each UAV can determine which plane and direction are available for collision avoidance. An analysis is performed to define an envelope for collision avoidance, where angular rate limits and obstacle detection range limits are considered. Based on the collision avoidance envelope, each UAV in a formation determines whether the formation can be maintained or not while avoiding obstacles. Numerical simulations are performed to demonstrate the performance of the proposed strategies.

This paper presents an autonomous vision-based netrecovery system for small fixed-wing unmanned aerial vehicles (UAVs). A fixed-wing UAV platform is constructed using various avionic sensors, and integrated with a flight control system and a vision system. The ground operation system consists of a vision station and ground control station that provide operation commands and monitor the UAV status. The vision algorithm to detect the recovery net and provide the bearing angle to the guidance algorithm is explained, along with the discussions on the techniques employed to improve the reliability of visual detection. The system identification process and controller are described, which enables to track given waypoints and to approach the detected net under the pursuit guidance law. Experimental results show the autonomous capabilities including take-off, waypoint following, and vision-based net recovery. The proposed technique can be an effective solution to recover fixed-wing UAVs without resorting to a complicated structure such as an instrumented landing system or expensive sensors such as a differential GPS.