Adaptive Sensor-Fault Tolerant Control of Unmanned Underwater Vehicles With Input Saturation

This paper investigates the tracking control problem for unmanned underwater vehicles(UUVs)systems with sensor faults,input saturation,and external disturbance caused by waves and ocean currents.An active sensor fault-tolerant control scheme is proposed.First,the developed method only requires the inertia matrix of the UUV,without other dynamic information,and can handle both additive and multiplicative sensor faults.Subsequently,an adaptive fault-tolerant controller is designed to achieve asymptotic tracking control of the UUV by employing robust integral of the sign of error feedback method.It is shown that the effect of sensor faults is online estimated and compensated by an adaptive estimator.With the proposed controller,the tracking error and estimation error can asymptotically converge to zero.Finally,simulation results are performed to demonstrate the effectiveness of the proposed method.

Reinforcement learning based parameter optimization of active disturbance rejection control for autonomous underwater vehicle

This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.

Fractional Gradient Descent RBFNN for Active Fault-Tolerant Control of Plant Protection UAVs

With the increasing prevalence of high-order systems in engineering applications, these systems often exhibitsignificant disturbances and can be challenging to model accurately. As a result, the active disturbance rejectioncontroller (ADRC) has been widely applied in various fields. However, in controlling plant protection unmannedaerial vehicles (UAVs), which are typically large and subject to significant disturbances, load disturbances andthe possibility of multiple actuator faults during pesticide spraying pose significant challenges. To address theseissues, this paper proposes a novel fault-tolerant control method that combines a radial basis function neuralnetwork (RBFNN) with a second-order ADRC and leverages a fractional gradient descent (FGD) algorithm.We integrate the plant protection UAV model’s uncertain parameters, load disturbance parameters, and actuatorfault parameters and utilize the RBFNN for system parameter identification. The resulting ADRC exhibits loaddisturbance suppression and fault tolerance capabilities, and our proposed active fault-tolerant control law hasLyapunov stability implications. Experimental results obtained using a multi-rotor fault-tolerant test platformdemonstrate that the proposed method outperforms other control strategies regarding load disturbance suppressionand fault-tolerant performance.

Experimental Study of a Modified Command Governor Adaptive Controller for Depth Control of an Unmanned Underwater Vehicle

Command governor–based adaptive control(CGAC)is a recent control strategy that has been explored as a possible candidate for the challenging task of precise maneuvering of unmanned underwater vehicles(UUVs)with parameter variations.CGAC is derived from standard model reference adaptive control(MRAC)by adding a command governor that guarantees acceptable transient performance without compromising stability and a command filter that improves the robustness against noise and time delay.Although simulation and experimental studies have shown substantial overall performance improvements of CGAC over MRAC for UUVs,it has also shown that the command filter leads to a marked reduction in initial tracking performance of CGAC.As a solution,this paper proposes the replacement of the command filter by a weight filter to improve the initial tracking performance without compromising robustness and the addition of a closed-loop state predictor to further improve the overall tracking performance.The new modified CGAC(M-CGAC)has been experimentally validated and the results indicate that it successfully mitigates the initial tracking performance reduction,significantly improves the overall tracking performance,uses less control force,and increases the robustness to noise and time delay.Thus,M-CGAC is a viable adaptive control algorithm for current and future UUV applications.

Technology Development of Unmanned Underwater Vehicles (UUVs)

In recent years, the weapon systems have been changing drastically because of the advancement of science technology and the change of military concept of combat. There is an unmanned system at the center of all those changes. Especially, in case of maritime environment, as the center stage of combat has changed from ocean to coastal areas, it is difficult for the existing naval forces to effectively operate in shallow waters. Therefore, unmanned underwater vehicles (UUVs) are being required at an increasing pace. In this paper, we analyze the characteristics of already developed UUVs, which are the key unmanned system of the marine battlefield environment in the future. Through the analysis of development cases and the investigation of the essential technologies, the critical design issues of UUVs are elaborated. We also suggest the future directions of the UUV technologies based on the case analysis.

A new robust fuzzy method for unmanned flying vehicle control

A new general robust fuzzy approach was presented to control the position and the attitude of unmanned flying vehicles(UFVs). Control of these vehicles was challenging due to their nonlinear underactuated behaviors. The proposed control system combined great advantages of generalized indirect adaptive sliding mode control(IASMC) and fuzzy control for the UFVs. An on-line adaptive tuning algorithm based on Lyapunov function and Barbalat lemma was designed, thus the stability of the system can be guaranteed. The chattering phenomenon in the sliding mode control was reduced and the steady error was also alleviated. The numerical results, for an underactuated quadcopter and a high speed underwater vehicle as case studies, indicate that the presented adaptive design of fuzzy sliding mode controller performs robustly in the presence of sensor noise and external disturbances. In addition, online unknown parameter estimation of the UFVs, such as ground effect and planing force especially in the cases with the Gaussian sensor noise with zero mean and standard deviation of 0.5 m and 0.1 rad and external disturbances with amplitude of 0.1 m/s2 and frequency of 0.2 Hz, is one of the advantages of this method. These estimated parameters are then used in the controller to improve the trajectory tracking performance.

Analysis of a uniform passive fault-tolerant control method for multicopters

For the multicopter with more than four rotors,the rotor fault information is unobservable,which limits the applica-tion of active fault-tolerant on multicopters.This paper applies an existing fault-tolerant control method for quadcopter to multi-copter with more than four rotors.Without relying on rotor fault information,this method is able to stabilize the multicopter with multiple rotor failures,which is validated on the hexacopter and octocopter using the hardware-in-the-loop simulations.Addi-tionally,the hardware-in-the-loop simulations demonstrate that a more significant tilt angle in flight will inhibit the maximum tolera-ble number of rotor failures of a multicopter.The more signifi-cant aerodynamic drag moment will make it difficult for the mul-ticopter to regain altitude control after rotor failure.

PID-type fault-tolerant prescribed performance control of fixed-wing UAV

This paper introduces a fault-tolerant control(FTC)design for a faulty fixed-wing unmanned aerial vehicle(UAV).To constrain tracking errors against actuator faults,error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions.Then,the commonly used and powerful proportional-integral-derivative(PID)control concept is employed to filter the transformed error variables.To handle the fault-induced nonlinear terms,a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety.It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds.Experimental results are presented to verify the feasibility of the developed FTC scheme.

A review on fault-tolerant cooperative control of multiple unmanned aerial vehicles

This paper presents the recent developments in Fault-Tolerant Cooperative Control(FTCC)of multiple unmanned aerial vehicles(multi-UAVs).To facilitate the analyses of FTCC methods for multi-UAVs.the formation control strategies under fault-free flight conditions of multi-UAVs are first summarized and analyzed,including the leader-following,behavior-based,virtual structure,collision avoidance,algebraic graph-based,and close formation control methods,which are viewed as the cooperative control methods for multi-UAVs at the pre-fault stage.Then,by considering the various faults encountered by the multi-UAVs,the state-of-the-art developments on individual,leader-following,and distributed FTCC schemes for multi-UAVs are reviewed in detail.Finally,conclusions and challenging issues towards future developments are presented.

Active Disturbance Rejection Controller Based Heading Control of Underwater Flight Vehicles

The total disturbance estimated by the extended state observer(ESO)in active disturbance rejection controller(ADRC)is affected greatly by measurement noise when the control step is small in heading control of underwater flight vehicles(UFVs).In order to prevent rudder from high-frequency chattering caused by measurement noise,a tracking-differentiator(TD)is integrated to the ESO to develop an improved ADRC scheme.The improved ADRC suppresses the impact of sensor noise.Both the results of simulations and tank tests show the effectiveness of improved ADRC based heading control.

A hybrid tracking control strategy for an unmanned underwater vehicle aided with bioinspired neural dynamics

Tracking control has been a vital research topic in robotics.This paper presents a novel hybrid control strategy for an unmanned underwater vehicle(UUV)based on a bio-inspired neural dynamics model.An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods.Then,a novel sliding mode control is proposed,which is capable of providing smooth and continuous torque commands free from chattering.In comparative studies,the proposed combined hybrid control strategy has ensured control signal smoothness,which is critical in real‐world applications,especially for a UUV that needs to operate in complex underwater environments.

Adaptive Attitude Control for Multi-MUAV Systems With Output Dead-Zone and Actuator Fault

Many mechanical parts of multi-rotor unmanned aerial vehicle(MUAV)can easily produce non-smooth phenomenon and the external disturbance that affects the stability of MUAV.For multi-MUAV attitude systems that experience output dead-zone,external disturbance and actuator fault,a leader-following consensus anti-disturbance and fault-tolerant control(FTC)scheme is proposed in this paper.In the design process,the effect of unknown nonlinearity in multi-MUAV systems is addressed using neural networks(NNs).In order to balance out the effects of external disturbance and actuator fault,a disturbance observer is designed to compensate for the aforementioned negative impacts.The Nussbaum function is used to address the problem of output dead-zone.The designed fault-tolerant controller guarantees that the output signals of all followers and leader are synchronized by the backstepping technique.Finally,the effectiveness of the control scheme is verified by simulation experiments.

基于自抗扰方法的无人机控制律设计

针对多平台、多任务的无人机飞行控制律的快速开发问题,提出一种基于自抗扰方法的无人机控制律架构,设计了可复用的扩展状态观测器及微分跟踪器,研究对比了其在3种具有较大差异的无人机平台中的应用,使7 000 kg的超音速UAV_A获得了更优的敏捷性结果,在60 kg的缩比UAV_B完成了5.8g的半滚倒转大过载机动飞行试验,基于10 kg的平直翼UAV_C实现了12架机紧编队的精确轨迹控制飞行试验。仿真及试飞结果表明:所提自抗扰控制结构响应快速、控制精度高、鲁棒性强,能够较好地适应多类无人机、面向多种任务场景的控制需求,且不需调参就能够获得较好的控制效果,为飞行控制算法设计提供了新的技术途径。

水下无人航行器高速航行下的运动特性及仿真控制研究

水下无人航行器具有水下活动范围大、机动性好优点,主要用于大范围地形地貌勘探,水下高速长航程航行时,水下航行器运动特性和姿态控制是研究重点。本文建立水下航行器垂直面航行运动模型,分析高速航行下的运动特性。为保证高速航行高效稳定,提出PID方法控制纵倾和滑模方法控制深度的组合控制策略。通过仿真试验,开展高速航行运动仿真研究。研究结果表明,在高速航行下,水下航行器会产生一定纵倾,且随着航速增加,纵倾影响会越大,高速状态放大了水下航行器外形上下轻微不对称的特性,诱导产生的垂向水动力及力矩增大,进而引起纵倾;在高速航行条件下,水下航行器能稳定保持定深度长距离航行,控制策略具有很好的适用性。

基于扩张状态观测器的里程计定位补偿无人车轨迹跟踪控制

无人车的轨迹跟踪精度与车载传感器密切相关,应用图像、基站定位等方法容易受到实际中存在的各种干扰的影响导致传感器数据出现误差甚至丢失,进而影响无人车的轨迹跟踪精度。鉴于此本文以差速驱动型无人车为研究对象,提出了一种仅依赖轮式里程计的无人车轨迹跟踪控制方法,同时通过扩张状态观测器来估计总扰动的方式解决里程计在复杂工况下受干扰产生读数偏移以及长时间运行产生的累计误差等问题。本文首先对里程计的定位过程进行了分析,通过对里程计建立扩张状态观测器准确测量影响定位的干扰,并且针对里程计的偏差,采取扰动补偿措施以提升定位精度。随后对车辆的轨迹跟踪动态误差进行了深入研究,并设计了相应的误差方程,以制定轨迹跟踪控制策略。在实际弯曲道路测试中,车辆可以稳定在0.21 m的跟踪误差范围内,验证了本文所提方法的可行性和有效性。

差动转向无人车轨迹跟踪和车身姿态控制研究

针对分布式驱动无人车转向时车身在离心力作用下外倾,引起内侧车轮载荷减小,严重时会导致差动转向失效乃至车辆侧翻等问题,提出了一种差动转向无人车的轨迹跟踪和车身姿态控制方法;该控制方法可通过差动转向实现无人车轨迹跟踪,同时通过主动悬架实现转向时车身主动内倾来保证差动转向有效性,提高了无人车的操纵稳定性。建立考虑侧倾因素的车辆模型及参考模型,通过分数阶单点预瞄驾驶员模型得到了参考模型跟踪期望路径所需的参考前轮转角;基于此,设计了H_(∞)鲁棒控制器,通过控制差动转向无人车的横摆角速度和车身内倾角,分别跟踪参考模型提供的参考值,得到了所需的差动力矩及左右侧主动悬架控制力。研究结果表明:所设计的分数阶单点预瞄驾驶员模型和H_(∞)鲁棒控制器能有效保证差动转向无人车实现轨迹跟踪,同时实现了车身姿态控制。

无人机自抗扰控制的调相补偿改进设计与抑扰实现

为解决非线性自抗扰控制应用中无人机位姿跟踪控制响应相位滞后的问题,利用非线性函数的滤波特性与相位补偿机理完成调相补偿器设计,解决了跟踪微分器实际滤波与相位跟踪之间的矛盾,进而提出调相补偿改进后的自抗扰控制(Phase Compensation ADRC,PCADRC),将其应用于四旋翼无人机飞控作业中的姿态与轨迹跟踪。通过由空中避障圆角矩和锥形螺旋组成的复合轨迹跟踪分析PCADRC应用的飞航控制性能优势,并设计无人机轨迹跟踪抗扰实验,对自抗扰控制的调相补偿改进效果进行验证。仿真与实验结果表明,对于平面或空间、平缓或陡变不同性质的轨迹,PCADRC能在确保抑扰性能前提下提高位姿跟踪的准确性、时效性与鲁棒性,能更好满足其稳健的飞控需求。

水下运载器动力学仿真以及串级控制器参数优化

为了让水下运载器能够更好完成潜射无人机的跨介质机动,基于回转体结构以及ROV(Remote Operated Vehicle)驱动模式设计一种具有动力的潜射无人机水下运载器。根据该运载器的外形结构和驱动模式特点,对其进行动力学建模并设计一种串级控制器控制该运载器的六自由度运动参数,利用Matlab/Simulink进行仿真验证,最后利用Isight优化软件对该运载器的串级控制器参数进行优化,分别利用自适应DOE优化算法和Evol优化算法进行优化计算,经过优化后的串级控制器在六自由度上的轨迹跟踪效果均有提升,其中Evol优化算法优化效果更好,计算成本更小。

基于NLADRC的水下飞行器姿态控制算法

针对水下飞行器系统模型中非线性强、并且在水下运动的过程中常遇到各种干扰的问题,提出一种抗扰性较强的非线性自抗扰姿态控制算法。根据刚体动力学理论,得到水下飞行器的三自由度俯仰运动模型,并详细阐述自抗扰控制器的结构及各个组成部分,确定参数整定的原则。仿真表明本算法可以通过单一改变观测器和控制器带宽大小而完成对姿态跟踪控制的调整,与传统PID控制和最优控制相比,非线性自抗扰控制器喷管摆角变化幅度和超调量更小、过渡时间更短,在有脉冲力矩干扰情况下,控制效果更好,为后面水下飞行器的进一步实验提供理论依据。

基于改进自抗扰控制的AUV回收姿态控制研究

针对自主水下潜航器(AUV)在近距离水下回收过程中对接姿态稳定控制的需求,在建立AUV空间运动数学模型的基础上,设计一款姿态跟踪的自抗扰控制器(ADRC),并对干扰补偿通道进行平滑低通滤波优化。通过对系统总扰动进行实时估计和补偿,实现对姿态误差的控制调整。以常值、阶跃扰动、高频正弦扰动3种波形作为预设姿态值,在Matlab/Simulink中进行仿真对比实验。结果表明,相较于传统PID控制器,该控制系统具有较快的响应速度,同时能够有效抑制外界扰动,可用于AUV回收姿态控制。