Q Ping Chu

Selective Velocity Obstacle Method for Cooperative Autonomous Collision Avoidance System for Unmanned Aerial Vehicles

Autonomous collision avoidance system (ACAS) for Unmanned Aerial Vehicles (UAVs) is set as a tool to prove that they can achieve the equivalent level of safety, required in context of integrating UAVs flight into the National Airspace System (NAS). This paper focus on the cooperative avoidance part, aiming to define an algorithm that can provide avoidance between cooperative UAVs in general, while still be restricted by some common rules. The algorithm is named the Selective Velocity Obstacle (SVO) method, which is an extension of the Velocity Obstacle method. The algorithm gives guidelines for UAVs to select between three basic modes for avoidance, i.e., to Avoid, Maintain, or Restore. The variation of those three modes gives flexibility for UAVs to choose how will they avoid. By modeling the algorithm as a hybrid system, simulations on various UAVs encounters scenario were conducted and shows satisfying result. Monte Carlo simulations are then conducted to conclude the performance even more. Randomizing the initial parameters, including speed, attitude, positions and avoidance starting point, more than 10 encounter scenario were tested, involving up until five UAVs. A parameter called the Violation Probability is then derived, showing zero violations in the entire encounter samples.

Robustness and Tuning of Incremental Backstepping Approach

Incremental Backstepping (IBS) approach is robust to the uncertainties in the plant dynamics term f(x). However, its robustness to the uncertainties in the control effectiveness term g(x) remains unknown especially in the presence of actuator dynamics. Furthermore, it requires the assumption of the availability of fast actuator dynamics. In this paper, the robustness is analyzed with and without the actuator dynamics. It is found that uncertainties with γ > 1 are advantageous for the stability of the complete system. Then, the tuning of the IBS is introduced. Two methods which can increase the robustness of the IBS are proposed: γ tuning and actuator compensator. The design of an actuator compensator requires the parameter of the actuator whereas the γ tuning methods does not. Finally, the robustness to model uncertainties is verified by simulation examples, which show the effectiveness of the proposed approaches.

Velocity Obstacle Method for Non-cooperative Autonomous Collision Avoidance System for UAVs

Unmanned Aerial Vehicles (UAVs) are required to have Autonomous Collision Avoidance System (ACAS) to resolve conflicts, especially when flying in the National Airspace System (NAS). This paper focused on the non-cooperative concept for avoidance, where UAVs face rogue obstacle that does not cooperatively share their flight data, nor they follows the rule of the air. UAVswill rely on its on-board sensor for avoidance, in space and time range that is limited. The limitation make the entire process of sense, detect, and avoid (SDA) mostly not applicable, and sense and avoid (SA) manner is more preferable and safe. A method called SA-VO that extend the use of the known Velocity Obstacle (VO-) method is introduce to handle the problem. The method produce more efficient avoidance in the non-cooperative space than SA manner of avoidance, without fully run the SDA process. Probability of collision map based on ranges of obstacle range of positions and velocity is predefine to replace the detection part of SDA. The method is then tested using simulations of encounters between UAV and an obstacle. The simulations show that SA-VO can be a middle ground between the SDA and SA manner of avoidance.

SHERPA: a safe exploration algorithm for Reinforcement Learning controllers

The problem of an agent exploring an unknown environment under limited prediction capabilities is considered in the scope of using a reinforcement learning controller. We show how this problem can be handled by the Safety Handling Exploration with Risk Perception Algorithm (SHERPA) that relies on interval estimation of the dynamics of the agent during the exploration phase along with limited capability from the agent to perceive the presence of incoming fatal instances. An application to a simple quadrotor model is included to show the algorithm performance.

A Joint Sensor Based Backstepping Approach For Fault-Tolerant Flight Control of a Large Civil Aircraft

The sensor based backstepping (SBB) control law, based on singular perturbation theory and Tikhonov’s theory, is a novel incremental type high gain control approach. This Lyapunov function based method is not susceptible to model uncertainties since it uses measurements instead of reconstructed modeling variables. Considering these merits, we extended the SBB method, in this paper, to handle sudden structural changes in the fault tolerant flight control of a fixed wing aircraft. A new double-loop joint SBB attitude controller has been developed for a Boeing 747-200 aircraft using the backstepping technique. Compared with the double-loop NDI attitude control approach, the double-loop SBB attitude control setup enables the verification of the system stability and allows relatively more interaction between the angular rate loop and the angular loop. The benchmark rudder runaway and engine separation failure scenarios are employed to evaluate the proposed method. The simulation results show that the proposed joint SBB attitude control method can lead to a zero tracking error performance in the nominal condition and can guarantee the stability of the closed-loop system under the failures.

Time Delayed Incremental Nonlinear Control

A sensor-based approach of Incremental Nonlinear Control is applied to flight control law design in this paper. It allows the usage of the same control law on different types of aircraft without the need for redesign. The derivation of this set of sensor-based control laws assumes fast control action. Due to actuator lags and delays, the implementation of control commands cannot necessarily be considered fast. This mitigates the stability guarantee provided by Lyapunov theory. Therefore, a novel technique to estimate the time delay margins of the incremental Lyapunov-based controlled systems is proposed in this paper. It provides an important stability measure for possible certification, aids in choosing appropriate controller gains and widens the application range of Incremental Nonlinear Control. The outcome is a simple, yet effective, control design methodology that gives control laws showing positive robustness properties with respect to model uncertainties, unknown parameters, external disturbances and time delay effects. In an example, it is applied to a DA 42 aircraft model as a (pilot-in-the-loop) rate controller. The implementation requires measurements of the aircrafts angular accelerations and control surface deflections but shows very positive results.

Design, Implementation and Flight-Tests of Incremental Nonlinear Flight Control Methods

This paper presents the design and implementation of incremental backstepping (IBS) flight control laws for the attitude control and stabilization on a fixed-wing aircraft. The design consists of multiple functionalities such as command-filtered backstepping, angle of attack control and body attitude control, that are based around an incremental control inner loop that tracks the angular rates of the aircraft. The results include flight data of an integrated IBS design that validate simulation results of control laws shown previously in literature. The results show that it is possible to implement robust nonlinear flight control laws that are easy to tune and require only little knowledge about the system dynamics parameters.

Design and Flight Testing of Incremental Nonlinear Dynamic Inversion-based Control Laws for a Passenger Aircraft

This paper describes the design, implementation and flight testing of flight control laws based on Incremental nonlinear Dynamic Inversion (INDI). The method compares commanded and measured accelerations to compute increments on the current control deflections. This results in highly robust control solutions with respect to model uncertainties as well as changes in aircraft dynamic characteristics of failure cases during flight. At the same time, the complexity of the algorithms is similar to classical ones. The key for practical implementation is in ensuring synchronization between angular acceleration and control deflection measurements or estimates. The underlying theory and practical design methods of INDI are very well understood, but implementation and testing has remained limited to sub-scale UAVs. The main contribution of this paper is to present the design and validation of manual attitude control functions for a Cessna Citation II experimental aircraft, covering control structure design, application of INDI, design optimization, robustness analyses, software implementation, ground and flight testing. For comparison, also control laws based on classical Nonlinear Dynamic Inversion were implemented and flown. The flight tests were highly successful and marked the first successful demonstration of INDI on a CS-25 certified aircraft. The flight test results proved that INDI clearly outperforms NDI and provided valuable lessons-learnt for future applications.

Flexible Aircraft Gust Load Alleviation with Incremental Nonlinear Dynamic Inversion

In this paper, an Incremental Nonlinear Dynamic Inversion (INDI) controller is developed for the flexible aircraft gust load alleviation (GLA) problem. First, a flexible aircraft model captures both inertia and aerodynamic coupling effects between flight dynamics and structural vibration dynamics is presented. Then an INDI GLA controller is designed for this aircraft model based on sensor measurements and the Kalman filter online estimation. Besides, the fifth order Pade approximation is used to model the pure time delay in the state estimation. Furthermore, simulations of the flexible aircraft flying through various spatial turbulence and gust fields demonstrate the effectiveness of the proposed controller on rigid-body motion regulation, vertical load alleviation, wing root bending moment reduction and elastic modes suppression. Additionally, numerical perturbation tests and a Monte-Carlo study show the robustness of the proposed controller to aerodynamic model uncertainties.

Aircraft Damage Identification and Classification for Database-driven Online Safe Flight Envelope Prediction

Safe flight-envelope prediction is essential for preventing aircraft loss of control after the occurrence of sudden structural damage and aerodynamic failures. Considering the unpredictable nature of such failures, many challenges remain in the process of implementing such a prediction system. In this paper, an approach to online safe flight-envelope prediction is proposed that is based on the retrieval of information from offline-assembled databases. One of the key steps of this approach is determining the structural damage of the state of the aircraft by using the identification, detection, and classification methods presented in this paper. The estimated damage cases will lead to structural damage indices in the database corresponding to those safe flight envelopes that are “closest” to the actual safe flight envelope of the damaged aircraft. The feasibility of the proposed database-driven approach is proved by simulation results, where three damage cases are successfully detected and classified.