欠驱动水下机器人三维轨迹跟踪有限时间预设性能控制

本文研究了具有不确定动态和未知时变海洋环境扰动的欠驱动水下机器人(AUVs)三维轨迹跟踪有限时间预设性能控制问题,提出新型预设性能函数和误差映射函数,将受预设性能限制的轨迹跟踪误差转变为非受限的变换后误差;构造新的超螺旋(ST)扩张状态观测器,在有限时间内实时估计AUV不确定动态和未知时变海洋环境扰动引起的总扰动;基于...     

Discrete-time extended state observer-based model-free adaptive constrained sliding mode control with modified prescribed performance via CFDL and PFDL

To tackle the trajectory tracking problem and achieve high control accuracy in many actual nonlinear systems with unknown dynamics and input saturation, a novel discrete-time extended state observer-based model-free adaptive constrained sliding mode control with modified prescribed performance is investigated via compact-form dynamic linearization (CFDL) and partial-form dynamic linearization (PFDL). Firstly, the original non-affine system is turned into an affine one comprising an unknown nonlinear term and a linearly parametric term affine to the input via both PFDL and CFDL. Then, a discrete-time extended state observer (DESO) is used to estimate the lumped disturbance containing the unknown nonlinear time-varying term and the term relevant to the estimation error of pseudo partial derivative (PPD) parameter. Furthermore, a modified prescribed performance function is introduced in the model-free adaptive sliding mode control scheme to keep the output tracking error in the prescribed bound without causing any asymmetric offset error in the steady-state. Meanwhile, to suppress the influence of input saturation on the control system, an anti-windup compensator is used. Finally, rigorous theoretical analyses show the robust convergence of the tracking error via the proposed CFDL and PFDL-based methods under external disturbances. Simulations verify the superiority of the modified prescribed performance function, DESO, and anti-windup compensator in the proposed method. Also, the effects of the PFDL-based method and the CFDL-based one are compared during the simulation.     

基于神经网络观测器的船舶轨迹跟踪递归滑模 动态面输出反馈控制

针对三自由度全驱动船舶速度向量不可测问题,考虑船舶模型参数和外部环境扰动均未知的情况,提出一种基于神经网络观测器的船舶轨迹跟踪递归滑模动态面输出反馈控制方法.该方法设计神经网络自适应观测器估计船舶速度向量,且利用神经网络逼近模型参数不确定项,综合考虑船舶位置和速度误差之间关系构造递归滑模面,再采用动态面控制技术设计轨迹跟踪控制律和参数自适应律,并引入低频增益学习方法消除外界扰动导致的高频振荡控制信号.选取李雅普诺夫函数证明了该控制律能够保证轨迹跟踪闭环系统内所有信号的一致最终有界性.最后,基于一艘供给船进行仿真验证,结果表明,船舶轨迹跟踪响应速度快,所设计控制器对系统模型参数摄动及外界扰动具有较强的鲁棒性.     

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.     

Adaptive Sliding Mode Control for Re-entry Attitude of Near Space Hypersonic Vehicle Based on Backstepping Design

Combining sliding mode control method with radial basis function neural network (RBFNN), this paper proposes a robust adaptive control scheme based on backstepping design for re-entry attitude tracking control of near space hypersonic vehicle (NSHV) in the presence of parameter variations and external disturbances. In the attitude angle loop, a robust adaptive virtual control law is designed by using the adaptive method to estimate the unknown upper bound of the compound uncertainties. In the angular velocity loop, an adaptive sliding mode control law is designed to suppress the effect of parameter variations and external disturbances. The main benefit of the sliding mode control is robustness to parameter variations and external disturbances. To further improve the control performance, RBFNNs are introduced to approximate the compound uncertainties in the attitude angle loop and angular velocity loop, respectively. Based on Lyapunov stability theory, the tracking errors are shown to be asymptotically stable. Simulation results show that the proposed control system attains a satisfied control performance and is robust against parameter variations and external disturbances.      

Robust adaptive motion/force tracking control design for uncertain constrained robot manipulators

In the presence of uncertain constraint and robot model, an adaptive controller with robust motion/force tracking performance for constrained robot manipulators is proposed. First, robust motion and force tracking is considered, where a performance criterion containing disturbance and estimated parameter attenuations is presented. Then the proposed controller utilizes an adaptive scheme and an auxiliary control law to deal with the uncertain environmental constraint, disturbances, and robotic modeling uncertainties. After solving a simple linear matrix inequality for gain conditions, the effect from disturbance and estimated parameter errors to motion/force errors is attenuated to an arbitrary prescribed level. Moreover, if the disturbance and estimated parameter errors are square-integrable, then an asymptotic motion tracking is achieved while the force error is as small as the inversion of control gain. Finally, numerical simulation results for a constrained planar robot illustrate the expected performance.     

Adaptive sensorless robust control of AC drives based on sliding mode control theory

This paper focuses in the design of a new adaptive sensorless robust control to improve the trajectory tracking performance of induction motors. The proposed design employs the so‐called vector (or field oriented) control theory for the induction motor drives, being the designed control law based on an integral sliding‐mode algorithm that overcomes the system uncertainties. This sliding‐mode control law incorporates an adaptive switching gain in order to avoid the need of calculating an upper limit for the system uncertainties. The proposed design also includes a new method in order to estimate the rotor speed. In this method, the rotor speed estimation error is presented as a first‐order simple function based on the difference between the real stator currents and the estimated stator currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. The simulated results show, on the one hand that the proposed controller with the proposed rotor speed estimator provides high‐performance dynamic characteristics, and on the other hand that this scheme is robust with respect to plant parameter variations and external load disturbances. Finally, experimental results show the performance of the proposed control scheme. Copyright © 2006 John Wiley & Sons, Ltd.     

四旋翼飞行器自适应动态面轨迹跟踪控制

针对具有未知外界扰动和系统不确定性集总未知非线性的四旋翼飞行器,提出了一种采用自适应不确定性补偿器的自适应动态面轨迹跟踪方法.通过将四旋翼飞行器系统分解为位置、欧拉角和角速率3个动态子系统,使各子系统虚拟控制器设计能充分考虑欠驱动约束;结合动态面控制技术,通过采用一阶低通滤波器,避免对虚拟控制信号求导;进而设计自适应不确定性补偿器,处理未知外界扰动和系统不确定性,最终确保闭环控制系统的稳定性、跟踪误差一致最终有界和系统所有状态信号有界.仿真研究和实验结果验证了本文提出控制方法的有效性和优越性.     

基于不确定逼近的机械手自适应鲁棒预测控制

针对具有参数不确定性和未知外部干扰的机械手轨迹跟踪问题提出了一种多输入多输出自适应鲁棒预测控制方法. 首先根据机械手模型设计非线性鲁棒预测控制律, 并在控制律中引入监督控制项; 然后利用函数逼近的方法逼近控制律中因模型不确定性以及外部干扰引起的未知项. 理论证明了所设计的控制律能够使机械手无静差跟踪期望的关节角轨迹. 仿真验证了本文设计方法的有效性.     

Synchronization of multiple autonomous underwater vehicles without velocity measurements

In this paper,we investigate the synchronization control of multiple autonomous underwater vehicles (AUVs),considering both state feedback and output feedback cases.Treating multiple AUVs as a graph,we define the tracking error of each AUV with both its own tracking error and the relative position errors with respect to its neighbors taken into account.Lyapunov analysis is used to derive the control law for each AUV.For the output feedback case,a passive filter is used to compensate for the unknown relative velocity errors among AUVs,and an observer is employed to estimate the velocity of the AUV itself.Rigid mathematical proof is provided for the proposed algorithms for both state feedback and output feedback cases.Simulations are provided to demonstrate the effectiveness of the proposed approach.It is shown that,the synchronization error is smaller in the case of considering the relative errors between AUVs than in the case of considering the tracking error of the single AUV only.     

带有未知参数和有界干扰的移动机器人轨迹跟踪控

针对模型参数未知和存在有界干扰的非完整移动机器人的轨迹跟踪控制问题,本文提出了一种鲁棒自适应轨迹跟踪控制器方法.非完整移动机器人的控制难点在于它的运动学系统是欠驱动的.针对这一难点,本文利用横截函数的思想,引入新的辅助控制器,使得非完整移动机器人系统不再是一个欠驱动系统,缩减了控制器设计的难度,进而利用非线性自适应算法和参数映射方法构造李雅谱诺夫函数.通过李雅普诺夫方法设计控制器和参数自适应器,从而使得非完整移动机器人的跟随误差任意小,即可以任意小的误差来跟随任意给定的参考轨迹.仿真结果证明了方法的有效性.     

动力定位船轨迹跟踪鲁棒自适应容错控制

本文研究了输入饱和状态下的动力定位船故障容错鲁棒自适应控制问题.该问题以动力定位船轨迹跟踪任务为目标,提出了一种新颖的鲁棒自适应控制器的设计,并且引入了二阶快速非奇异终端滑模和神经网络控制算法保证了控制器在实际任务中的执行效果.首先,介绍了三自由度动力定位船的运动模型包括了运动学模型和动力学模型以及推进器故障模型.然后,设计了二阶快速非奇异终端滑模面,提出了一种针对时变扰动和模型不确定性的鲁棒控制方案,保证系统无抖振现象的前提下实现了系统更快的收敛速度.同时运用被动容错控制思想,确保动力定位船在推进器故障发生时依然能够实现预计的跟踪性能.此外,通过Lyapunov稳定性判据分析,证明了提出的改进自适应滑模控制方法可确保系统在初始状态未知前提下,跟踪误差渐近收敛于零.最后,通过数值仿真实验结果验证了控制律的有效性.     

Dynamical adaptive integral backstepping variable structure controller design for uncertain systems and experimental application

In this study, a dynamical adaptive integral backstepping variable structure control (DAIBVSC) system based on the Lyapunov stability theorem is proposed for the trajectory tracking control of a nonlinear uncertain mechatronic system with disturbances. In this control scheme, no prior knowledge is required on the uncertain parameters and disturbances because it is estimated by two types of dynamical adaptive laws. These adaptive laws are integrated into the dynamical adaptive integral backstepping control and variable structure control (VSC) parts of the DAIBVSC. The dynamical adaptive law in the dynamical adaptive integral backstepping control part updates parametric uncertainties, while the other in the VSC part adapts upper bounds of non‐parametric uncertainties and disturbances. In order to achieve a more robust output tracking and better parameter adaptation, the control system is extended by one integrator and sliding surface is augmented by an integral action. Experimental evaluation of the DAIBVSC is conducted with respect to performance and robustness to parametric uncertainties. Experimental results of the DAIBVSC are compared with those of a traditional VSC. The proposed DAIBVSC exhibits satisfactory output tracking performance, good estimation of the uncertain parameters and can reject disturbances with a chattering free control law. Copyright © 2017 John Wiley & Sons, Ltd.     

High-order sliding-mode observer based output feedback adaptive robust control of a launching platform with backstepping

A kind of launching platform driven by two permanent magnet synchronous motor (PMSM) motors which is used to launch kinetic load to hit the target, always faces strong parameter uncertainties and strong external disturbance such as the air current impulsion, which would degrade their tracking accuracy greatly. In this paper, an adaptive robust nonlinear controller is proposed for high-accuracy motion control of the launching platform, in which the adaption law is designed to estimate the unknown coupling coefficients of torque disturbance and feed-forward cancellation technique is used to compensate the coupling torque disturbance and some other constant disturbances. In addition, a nonlinear robust feedback term is designed to inhibit the influence of the parameter estimation error and the other model uncertainty to stabilise the closed-loop system. Considering that some system states are immeasurable due to cost-reduction, volume/weight limitations and structure restriction or heavy measurement noise is usually associated with the measurements, which may also deteriorate the achievable performance of full-state feedback controllers; a high-order sliding-mode observer is used to estimate the unmeasured system states, and it is synthesised with the adaptive robust controller via feed-forward cancellation method. The intermediary virtual control law and the final control law are derived by integrating the backstepping method. Furthermore, the controller theoretically guarantees a prescribed tracking transient performance and final tracking accuracy while achieving asymptotic tracking performance in the presence of parametric uncertainties only, which is very important for high-accuracy tracking control of launching platform. Extensive comparative experimental results are obtained to verify the high performance nature of the proposed control strategy.     

非完整移动机器人的神经网络鲁棒自适应控制

在非完整移动机器人轨迹跟踪问题中,针对机器人运动学与动力学模型的参数和非参数不确定性,提出了一种混合神经网络鲁棒自适应轨迹跟踪控制器,该控制器由运动学控制器和动力学控制器两部分组成;其中,采用了参数自适应的径向基神经网络对运动学模型的未知部分进行了建模,并采用权值在线调整的单层神经网络和自适应鲁棒控制项构成了动力学控制器;基于Lyapunov方法的设计过程保证了系统的稳定性和收敛性,仿真结果证明了算法的有效性。     

Precision Synchronization Motion Trajectory Tracking Control of Multiple Pneumatic Cylinders

This paper deals with the synchronized motion trajectory tracking control problem of multiple pneumatic cylinders. An adaptive robust synchronization controller is developed by incorporating the cross‐coupling technology into the integrated direct/indirect adaptive robust control (DIARC) architecture. The position synchronization error and the trajectory tracking error of each cylinder are combined to construct the so‐called coupled position error. The proposed adaptive robust synchronization controller is designed with the feedback of this coupled position error and is composed of two parts: an on‐line parameter estimation algorithm and a robust control law. The former is employed to obtain accurate estimates of model parameters for reducing the extent of parametric uncertainties, while the latter is utilized to attenuate the effects of parameter estimation errors, unmodelled dynamics, and external disturbances. Theoretically, both the position synchronization and trajectory tracking errors will achieve asymptotic convergence simultaneously. Moreover, the effectiveness of the proposed controller is verified by the extensive experimental results performed on a two‐cylinder pneumatic system.     

不确定性系统的自适应鲁棒跟踪控制

针对存在未知干扰和未建模动态等不确定性的系统的自适应鲁棒跟踪控制问题进行了 探讨.首选将l1优化控制器的有限拍设计方法结合给出了最优鲁棒稳态跟踪控制器的设计方法． 然后利用集员辨识的思想,将名义模型的参数和未建模动态及干扰的大小作为未知参数,提出了 一种递推参数估计方法.最后将上述研究结果结合起来提出了一种自适应鲁棒跟踪控制策略,证 明了自适应算法的全局收敛性并给出了鲁棒跟踪性能指标的一下较紧的上界.与现有的结果相 比,本文提出的自适应控制具有非保守的鲁棒稳定性,具有渐近最优的鲁棒跟踪性能.     

基于RBF神经网络的作业型AUV自适应终端滑模控制方法及实验研究

研究了作业型AUV （自主水下机器人）的轨迹跟踪控制问题.实际作业中,水下机械手展开作业过程将引起AUV动力学性能变化,进而影响AUV轨迹跟踪控制;并且水流环境干扰亦将影响AUV轨迹跟踪控制.针对上述AUV轨迹跟踪控制问题,提出一种基于RBF （径向基函数）神经网络的AUV自适应终端滑模运动控制方法.该方法在李亚普诺夫稳定性理论框架下,采用RBF网络对机械手展开引起的AUV动力学性能变化和水流环境干扰进行在线逼近,并结合自适应终端滑模控制器对神经网络权值和AUV控制参数进行自适应在线调节.通过李亚普诺夫稳定性理论,证明AUV系统轨迹跟踪误差一致稳定有界.针对滑模控制项引起的控制量抖振问题,提出一种变滑模增益的饱和连续函数滑模抖振降低方法,以降低滑模控制量抖振.通过AUV实验样机的艏向和垂向的轨迹跟踪实验,验证了本文AUV系统控制方法和滑模降抖振方法的有效性.     

Robust time‐varying formation control for multiple underwater vehicles subject to nonlinearities and uncertainties

This paper addresses the robust formation control problem for multiple autonomous underwater vehicles (AUVs) to achieve the desired formation trajectory and time‐varying formation pattern and to align the vehicle attitudes. The dynamics of each AUV system involves parameter variations, nonlinear dynamics, and external disturbances. A robust distributed formation control protocol is developed based on the graph theory and the robust compensation theory. It is proven that the tracking errors of the global uncertain system can converge into a given neighborhood of the origin in a finite time. Simulation results substantiate the effectiveness of the developed formation control method for multiple AUVs subject to nonlinearities and uncertainties.     

Adaptive synchronisation of unknown nonlinear networked systems with prescribed performance

This paper proposes an adaptive tracking control with prescribed performance function for distributive cooperative control of highly nonlinear multi-agent systems. The use of such approach confines the tracking error within a large predefined set to a predefined smaller set. The key idea is to transform the constrained system into unconstrained one through the transformation of the output error. Agents’ dynamics are assumed unknown, and the controller is developed for a strongly connected structured network. The proposed controller allows all agents to follow the trajectory of the leader node, while satisfying the necessary dynamic requirements. The proposed approach guarantees uniform ultimate boundedness for the transformed error as well as a bounded adaptive estimate of the unknown parameters and dynamics. Simulations include two examples to validate the robustness and smoothness of the proposed controller against highly nonlinear heterogeneous multi-agent system with uncertain time-variant parameters and external disturbances.