Robust Fault Diagnosis for Quadrotor UAVs Using Adaptive Thau Observer

A robust Fault Diagnosis (FD) scheme for a real quadrotor Unmanned Aerial Vehicle (UAV) is proposed in this paper. Firstly, a novel Adaptive Thau observer (ATO) is developed to estimate the quadrotor system states and build a set of offset residuals to indicate actuators’ faults. Based on these residuals, some rules of Fault Diagnosis (FD) are designed to detect and isolate the faults as well as estimate the fault offset parameters. Secondly, a synthetic robust optimization scheme is presented to improve Fault Estimation (FE) accuracies, three key issues include modeling uncertainties, and magnitude order unbalances as well as noises are addressed. Finally, a typical fault of rotors is simulated and injected into one of four rotors of the quadrotor, and experiments for the FD scheme have been carried out. Unlike former research works on the FD schemes for quadrotors, our proposed FD scheme based on the ATO can not only detect and isolate the failed actuators, but also estimate the fault severities. Regardless of roughness of the real flying data, the FD results still have sufficient FE accuracies.     

An Impedance Force Control Approach to a Quad-Rotor System Based on an Acceleration-Based Disturbance Observer

This article presents the contact force control approach for a quad-rotor system to perform tasks of interacting with the environment. The hovering capability of the quad-rotor system allows the force in the altitude direction to be regulated by realizing the impedance function. To obtain the better force control performance, inherent and external disturbances to the quad-rotor system are suppressed by designing the acceleration-based disturbance observer (AbDOB). Force tracking impedance control is applied to regulate the contact force to the environment. Simulation studies of force tracking control for changing a light bulb on the ceiling are performed to evaluate the feasibility of the proposed force control task for a quad-rotor system.     

An Observer and Post Filter Based Scheme for Fault Estimation of Nonlinear Systems

International Journal of Control, Automation and Systems - The problem of actuator fault estimation for a kind of nonlinear discrete time varying (NDTV) systems is investigated. Norm bounded...     

Stabilization and Trajectory Tracking of a Quad-Rotor Using Vision

We propose a vision-based position control method, with the purpose of providing some level of autonomy to a quad-rotor unmanned aerial vehicle. Our approach estimates the helicopter X-Y-Z position with respect to a landing pad on the ground. This technique allows us to measure the position variables that are difficult to compute when using conventional navigation systems, for example inertial sensors or Global Positioning Systems in urban environment or indoor. We also present a method to measure translational speed in a local frame. The control strategy implemented is based on a full state feedback controller. Experimental results validate the effectiveness of our method.     

Robust Sliding Mode Observer based Fault Estimation for Certain Class of Uncertain Nonlinear Systems

This paper proposes a new scheme for estimating the actuator and sensor fault for Lipschitz nonlinear systems with unstructured uncertainties using the sliding mode observer (SMO) technique. Initially, a coordinate transformation is introduced to transform the original state vector into two parts such that the actuator faults only appear in the dynamics of the second state vector. The concept of equivalent output error injection is then employed to estimate the actuator fault. The effects of system uncertainties on the estimation errors of states and faults are minimized by integrating an uncertainty attenuation level into the observer. The sufficient conditions for the state estimation error to be bounded and satisfy a prescribed performance are derived and expressed as a linear matrix inequality (LMI) optimization problem. Furthermore, the proposed actuator fault estimation method is extended to sensor fault estimation. Finally, the effectiveness of the proposed scheme in estimating actuator and sensor faults has been illustrated considering an example of a single‐link flexible joint robot system.     

Estimation of Sinusoidal Frequencies and Amplitudes Using Adaptive Identifier and Observer

A simple method is proposed for estimation of amplitudes of multiple sinusoids. The estimation is based on the existing adaptive identifier which offers the globally convergent estimate of sinusoidal frequencies. To deal with possible singularities of the amplitude estimation, adaptive observers are also proposed for estimation of sinusoidal amplitudes. Simulations illustrate the results     

Polynomial Fuzzy Observer Designs: A Sum-of-Squares Approach

This paper presents a sum-of-squares (SOS) approach to polynomial fuzzy observer designs for three classes of polynomial fuzzy systems. The proposed SOS-based framework provides a number of innovations and improvements over the existing linear matrix inequality (LMI)-based approaches to Takagi-Sugeno (T-S) fuzzy controller and observer designs. First, we briefly summarize previous results with respect to a polynomial fuzzy system that is a more general representation of the well-known T-S fuzzy system. Next, we propose polynomial fuzzy observers to estimate states in three classes of polynomial fuzzy systems and derive SOS conditions to design polynomial fuzzy controllers and observers. A remarkable feature of the SOS design conditions for the first two classes (Classes I and II) is that they realize the so-called separation principle, i.e., the polynomial fuzzy controller and observer for each class can be separately designed without lack of guaranteeing the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. Although, for the last class (Class III), the separation principle does not hold, we propose an algorithm to design polynomial fuzzy controller and observer satisfying the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. All the design conditions in the proposed approach can be represented in terms of SOS and are symbolically and numerically solved via the recently developed SOSTOOLS and a semidefinite-program solver, respectively. To illustrate the validity and applicability of the proposed approach, three design examples are provided. The examples demonstrate the advantages of the SOS-based approaches for the existing LMI approaches to T-S fuzzy observer designs.     

基于观测器的LPV系统故障检测方法

针对一类线性参数变化(LPV)连续系统的故障检测问题,通过构造合适的输出观测器,获得残差生成器,并通过优化设计步骤,实现对干扰的有效抑制和对故障的灵敏检测。利用依赖参数的Lyapunov函数,在保证残差生成器稳定性的基础上,给出观测器存在的充分条件。应用投影定理,借助附加矩阵解除了基于参数的Lyapunov函数矩阵与系统矩阵的耦合,得到以线性矩阵不等式(LMI)形式表示的求解条件。对于参数变化系统,基于LMI的求解条件为无穷维问题,借助基函数和参数网格化方法,使其转变为可求解的问题。仿真结果表明,应用该方法可以在一定程度上抑制干扰,并能灵敏有效地实现故障检测。     

基于观测器的网络控制系统的故障检测

研究了具有输出传输长时延的网络控制系统基于观测器的故障检测,在总结其设计方法的基础上利用预测状态作为控制器的输入,设计了具有延迟补偿功能的状态观测器,通过求取观测器增益矩阵来使得状态重构能跟上实际状态的响应性能。产生的残差信号对干扰信号和不确定项具有较强的鲁棒性,同时对故障信号具有较高的灵敏度。最后给出了网络控制系统基于观测器的故障检测的设计步骤。     

基于非线性观测器的疾病发生率的估计

在传染病动力学模型中,对疾病发生率的估计是传染病流行趋势预测和预防工作的重要部分.本文研究了一类非线性观测器在传染病动力学模型中的应用,利用非线性观测器估计疾病的发生率和传染率系数,并通过数值仿真验证了以上这些结论.     

Hybrid Observer for Global Frequency Estimation of Saturated Signals

A hybrid observer for the on-line global estimation of the frequency and the bias of a saturated sinusoidal signal is proposed. Robustness of the observer against unknown saturation level is discussed.     

基于非线性观测器的疾病发生率的估计

在传染病动力学模型中,对疾病发生率的估计是传染病流行趋势预测和预防工作的重要部分。本文研究了一类非线性观测器在传染病动力学模型中的应用,利用非线性观测器估计疾病的发生率和传染率系数,并通过数值仿真验证了以上这些结论。     

一类不确定线性系统的鲁棒故障观测器设计

研究线性时不变系统的鲁棒故障观测器设计问题,给定故障检测率,降低误报率作为优化指标,对故障和未知扰动在残差信号中的输出进行滤波。再考虑不确定性影响,运用模型匹配方法,提出了具有不确定性线性系统的鲁棒故障观测器设计方法,并以线性矩阵不等式形式给出问题求解算法。通过求解具有线性矩阵不等式约束的凸优化问题获得观测器的全局最优解。通过仿真表明,改进的设计方法可有效保障残差信号对故障信号的灵敏度,并改善了诊断性能。     

一类非线性系统的鲁棒故障估计

针对一类非线性系统,研究基于自适应观测器的故障估计问题.设计了保证诊断系统稳定的实现故障估计的自适应调节律, 并通过H∞跟踪性能,分析了调节律中的参数对故障估计精度的影响.数值仿真验证了该方法的有效性.     

Control for Underactuated Systems Using Sliding Mode Observer

In this work, first we estimate all the system’s state vector, with guarantied precision, for a category of second order underactuated mechanical systems (UMS), exploiting the triangular observer (TO) model that suits to the structure of these systems. Then we propose a sliding mode controller (SMC). The latter uses the estimated states given by the observer. The underactuated system is decomposed into two subsystems, where the sliding surface is constructed in two levels for each subsystem. The proposed controller guaranties the tracking performances, with minimization of chattering phenomenon, due to the constructed observer, even for system with uncertainties. Simulation results show the effectiveness of this strategy of control.

     

Time-Optimal Control of a Hovering Quad-Rotor Helicopter

The time-optimal control problem of a hovering quad-rotor helicopter is addressed in this paper. Instead of utilizing the Pontryagin's Minimum Principle (PMP), in which one needs to solve a set of highly nonlinear differential equations, a nonlinear programming (NLP) method is proposed. In this novel method, the count of control steps is fixed initially and the sampling period is treated as a variable in the optimization process. The optimization object is to minimize the sampling period such that it will be below a specific minimum value, which is set in advance considering the accuracy of discretization. To generate initial feasible solutions of the formulated NLP problem, genetic algorithms (GAs) are adopted. With the proposed method, one can find a time-optimal movement of the helicopter between two configurations. To show the feasibility of the proposed method, simulation results are included for illustration.     

Combining Stereo Vision and Inertial Navigation System for a Quad-Rotor UAV

This paper presents the development of a quad-rotor robotic platform equipped with a visual and inertial motion estimation system. Our objective consists of developing a UAV capable of autonomously perform take-off, positioning, navigation and landing in unknown environments. In order to provide accurate estimates of the UAV position and velocity, stereo visual odometry and inertial measurements are fused using a Kalman Filter. Real-time experiments consisting on motion detection and autonomous positioning demonstrate the performance of the robotic platform.     

基于线性二次高斯的四旋翼飞行器姿态控制

以自主研发的四旋翼飞行器为研究对象,主要讨论姿态控制器的设计方法。首先根据动力学原理和系统辨识得到姿态角系统的近似线性数学模型。其次,为获取姿态控制所必需的姿态角信息,提出采用高性价比的陀螺仪结合加速度计,并利用卡尔曼滤波器推测姿态角的方法。最后,根据所得模型和卡尔曼滤波器设计了线性二次高斯控制器。实验结果表明,设计的控制器具有良好的稳态和跟踪性能,从而验证了姿态角推测方法及控制器的可行性。     

Unknown Input Fault Detection and Isolation Observer Design for Neutral Systems

This paper deals with actuator fault diagnosis of neutral delayed systems with multiple time delays using an unknown input observer. The main purpose is to design an observer that guarantees the asymptotic stability of the estimate error dynamics and the actuator fault detection. The existence conditions for such an observer are established. The main problem studied in this paper aims at designing observer‐based fault detection and isolation. The designed observer enhances the robust diagnosis performance, including rapidity and accuracy, and generates residuals that enjoy perfect decoupling properties among faults. Based on Lyapunov stability theory, the design of the observer is formulated in terms of linear matrix inequalities, and the diagnosis scheme is based on a bank of unknown input observers for residual generation that guarantees fault detection and isolation in the presence of external disturbances. A numerical example is presented to illustrate the efficiency of the proposed approach.