无人艇轨迹跟踪的预设性能抗扰控制研究

针对海洋环境干扰下的无人艇轨迹跟踪问题,提出一种预设性能轨迹跟踪抗扰控制方法。首先,该方法通过引入具有约束作用的性能函数设计预设性能反演控制器。同时采用干扰观测器精确补偿外界未知扰动,并引入带σ修正漏项自适应律对海洋环境干扰的界进行估计,实现了无人艇轨迹跟踪抗扰控制,且同时保证其暂态性能和稳态性能。然后根据李雅普诺夫稳...     

精确估计下的多智能体系统漏斗复合控制

针对一类具有时变扰动的非线性多智能体系统, 研究其在有向拓扑下的一致性跟踪问题, 提出一种基于精 确估计的复合自适应预设有限时间(PFT)漏斗控制方法. 首先, 构建一种新的PFT漏斗控制, 使跟踪误差约束在PFT 漏斗边界内. 其次, 采用神经网络(NN)逼近系统的未知非线性, 并利用NN逼近信息设计扰动观测器, 建立基于NN和 扰动观测器的复合估计模型, 将得到的预测误差引入NN权值的复合更新律中, 实现对未知非线性和时变扰动的精 确估计. 然后, 利用动态面技术和误差补偿机制, 在解决传统反步法“计算爆炸”问题的同时, 消除滤波器误差对系 统的影响. 最后, 通过Lyapunov稳定性理论证明闭环系统所有信号均为有界的, 并通过仿真实验验证控制方法的有 效性.     

时变终端滑模自适应有限时间控制算法

为实现非线性系统输出对期望轨迹的有限时间内精确跟踪，提出一种有限时间鲁棒控制算法。通过设计一种无到达过程的时变终端滑模面，在保证有限时间收敛的基础上，消除了传统滑模控制中固有的稳态误差，实现系统输出对期望轨迹的精确跟踪。设计了自适应更新律补偿由参数摄动导致的系统扰动，增强系统对内部未知参数摄动的鲁棒性。对比仿真结果表明：时变终端滑模控制比线性滑模控制的轨迹跟踪时间快41.5%；线性滑模控制器下的轨迹跟踪稳态误差为0.005，时变滑模控制器使轨迹跟踪的稳态误差降为0，实现精确跟踪。     

永磁同步电机有限时间预设性能控制

为实现扰动作用下对永磁同步电机角位置伺服系统的高瞬态和稳态跟踪性能控制,本文提出一种具有预设性能约束的有限时间控制方法.首先,设计扰动观测器实现对负载力矩扰动的估计与补偿.其次,引入有限时间预设性能函数以保证角跟踪误差的动态性能,并通过可逆变换将受不等式约束的角位置跟踪误差转换为等效的无约束误差形式.然后,将有限时间指令滤波反步法应用于控制器设计中,不仅可以避免“微分爆炸”的现象,而且能够保证跟踪误差的有限时间内收敛.最后,通过仿真实验验证了该算法的有效性和对扰动的鲁棒性.     

随机激励下板球系统建模与有限时间全状态预设性能跟踪控制

研究板球系统受到随机激励时的数学建模与轨迹跟踪控制问题. 首次建立了板球系统的随机数学模型, 并 结合backstepping方法、有限时间预设性能函数、全状态约束及新的预设性能推导方法设计了具有未知输入饱和的 随机板球系统实际有限时间全状态预设性能跟踪控制器, 实现了随机激励下板球系统的有限时间预设性能轨迹跟 踪控制. 所设计的控制器保证了系统跟踪误差能够被预先给定的有限时间性能函数约束, 并且能在任意给定的停息 时间内收敛到预先给定的邻域内. 最后通过仿真实验验证了所设计控制器具有更好的控制效果.     

网联车辆有限时间滑模预设性能队列控制

针对含有未知扰动和模型不确定的网联车辆预设性能队列控制问题,本文提出了一种基于改进滑模的有限时间队列控制方法.首先,为满足预设性能,设计了一种新型性能函数,保证了跟踪误差在预设时间内收敛到规定区域.其次,提出了一种改进的滑模队列控制算法,加快了系统收敛速度,实现了有限时间单车稳定及队列稳定,同时,设计了自适应律,有效解决了扰动及模型不确定问题.最后,进行了MATLAB仿真实验,通过6辆网联车的队列控制仿真验证了所提算法的有效性.     

一种快速有限时间收敛的轨迹跟踪引导律EI北大核心CSCD

针对参考轨迹曲率变化大导致前视距离(LAD)调整不及时,使得无人船(USV)轨迹跟踪误差收敛慢的问题,本文利用轨迹跟踪几何关系,建立位置跟踪误差动态系统,引入曲率参数设计一种新型的时变前视距离(NTLAD),提出一种快速有限时间收敛的轨迹跟踪引导律(FFTC-GL),包括期望艏向引导律和期望巡航速度引导律研究,以快速准确跟踪大范围曲率的轨迹.首先,构造NTLAD的稳定约束条件,结合图解法求解NTLAD函数,实现法向误差快速有限时间收敛,并且引入曲率参数,快速准确地跟踪不同曲率的轨迹.其次,基于切向误差的有限时间技术,设计快速有限时间速度引导律,实现切向误差动态系统的有限时间稳定.最后,通过对比有限时间上确界,表明引导律对位置跟踪误差收敛的快速性.轨迹跟踪仿真表明FFTC-GL能够在有限时间内跟踪参考轨迹,保证曲线拐点位置跟踪误差快速收敛.     

控制方向未知的不确定系统预设性能自适应神经网络反演控制

对一类控制方向未知的不确定严格反馈非线性系统的预设性能自适应神经网络反演控制问题进行了研究.系统中含有时变非匹配不确定项且控制方向未知.首先,提出了一种新的误差转化方法,放宽了对初始误差已知的限制;随后,利用径向基函数(radial basis function,RBF)神经网络及跟踪微分器分别实现了对未知函数和虚拟控制量导数的逼近,并综合运用Nussbaum函数和反演控制技术设计了控制器.所设计的控制器能保证系统内所有信号有界且输出误差满足预设的瞬态和稳态性能要求.最后的仿真研究验证了控制器设计方法的有效性.     

基于有限时间预设性能的高超声速飞行器反演控制

针对存在参数不确定以及外界干扰的高超声速飞行器跟踪性能问题,提出一种基于有限时间预设性能的反演控制方案.首先,为便于控制器设计,将高超声速飞行器模型划分为速度和高度子系统,针对子系统分别设计预设性能控制器以提高系统的瞬态和稳态性能;然后,通过设计一种有限时间性能函数,使得跟踪误差能够在预设时间内收敛至稳态值;接着,考虑到反演设计中虚拟指令导数难以获取以及干扰项对系统的影响,基于干扰观测器提出一种扰动估计方法,目的是在取得良好的观测扰动效果的同时,使得控制器设计流程简化、复杂度降低;最后,基于Lyapunov稳定理论证明系统的跟踪误差最终一致有界,并通过仿真验证该方法的有效性.     

基于时变障碍李雅普诺夫函数的变体无人机有限时间控制

针对复杂扰动下可执行多种任务的复合式变体无人机, 提出了一种基于浸入与不变(Immersion and invariance, I&I)理论和隐含系统状态受限条件的复合时变障碍Lyapunov函数(Composite time-varying barrierLyapunov function, CTV-BLF)的控制方案. 设计了一种基于浸入与不变理论的扰动观测器, 构建了一种基于监督因子的有限时间动态尺度因子(Finite-time dynamic scaling factor, FT-DSF)调节器. 在此基础上, 设计了一种基于复合时变障碍Lyapunov函数和动态滑模面的控制器, 保证系统状态始终在约束条件之内. 通过衍生定理证明轨迹跟踪误差是有限时间稳定的. 最终仿真结果验证了所提方案的有效性.     

Robust adaptive trajectory tracking control of underactuated autonomous underwater vehicles with prescribed performance

In this paper, a novel robust adaptive trajectory tracking control scheme with prescribed performance is developed for underactuated autonomous underwater vehicles (AUVs) subject to unknown dynamic parameters and disturbances. A simple error mapping function is proposed in order to guarantee that the trajectory tracking error satisfies the prescribed performance. A novel additional control based on Nussbaum function is proposed to handle the underactuation of AUVs. The compounded uncertain item caused by the unknown dynamic parameters and disturbances is transformed into a linear parametric form with only single unknown parameter called virtual parameter. On the basis of the above, a novel robust adaptive trajectory tracking control law is developed using dynamic surface control technique, where the adaptive law online provides the estimation of the virtual parameter. Strict stability analysis indicates that the designed control law ensures uniform ultimate boundedness of the AUV trajectory tracking closed‐loop control system with prescribed tracking performance. Simulation results on an AUV in two different disturbance cases with dynamic parameter perturbation verify the effectiveness of our adaptive trajectory tracking control scheme.     

基于自适应滑模的欠驱动无人艇轨迹跟踪控制算法

针对欠驱动水面无人艇在航行过程中存在的海洋环境干扰、数学模型参数不确定、执行器故障等问题,提出了一种基于扰动观测器与神经网络技术的自适应滑模轨迹跟踪策略。在无人艇三自由度模型的基础上,结合视线制导率,提出了一种新的轨迹跟踪制导策略。采用自适应滑模控制技术设计了欠驱动无人艇轨迹跟踪控制器,有效地抑制了执行器衰减故障对无人艇控制系统的影响;同时运用了非线性扰动观测器和自适应径向基函数神经网络分别对无人艇受到的外界干扰和模型参数不确定性进行补偿和拟合,提高了控制系统的抗干扰能力。基于Lyapunov定理证明了所设计的控制系统的稳定性,并在MATLAB中进行了仿真测试。仿真结果表明,所提出的轨迹跟踪控制算法可以在较为复杂的环境下实现对欠驱动无人艇的精准控制;相较于对比算法,位置的平均跟踪误差减小了80%以上,具备较高的稳定性和鲁棒性。     

Transverse function control with prescribed performance guarantees for underactuated marine surface vehicles

This paper studies the problem of stabilizing reference trajectories (also called as the trajectory tracking problem) for underactuated marine vehicles under predefined tracking error constraints. The boundary functions of the predefined constraints are asymmetric and time‐varying. The time‐varying boundary functions allow us to quantify prescribed performance of tracking errors on both transient and steady‐state stages. To overcome difficulties raised by underactuation and nonzero off‐diagonal terms in the system matrices, we develop a novel transverse function control approach to introduce an additional control input in backstepping procedure. This approach provides practical stabilization of any smooth reference trajectory, whether this trajectory is feasible or not. By practical stabilization, we mean that the tracking errors of vehicle position and orientation converge to a small neighborhood of zero. With the introduction of an error transformation function, we construct an inverse‐hyperbolic‐tangent‐like barrier Lyapunov function to show practical stability of the closed‐loop systems with prescribed transient and steady‐state performances. To deal with unmodeled dynamic uncertainties and external disturbances, we employ neural network (NN) approximators to estimate uncertain dynamics and present disturbance observers to estimate unknown disturbances. Subsequently, we develop adaptive control, based on NN approximators and disturbance estimates, that guarantees the prescribed performance of tracking errors during the transient stage of on‐line NN weight adaptations and disturbance estimates. Simulation results show the performance of the proposed tracking control.     

基于扩张观测器的欠驱动船舶轨迹跟踪低频学习自适应动态面输出反馈控制

针对速度不可测的三自由度欠驱动船舶轨迹跟踪控制问题,考虑船舶存在模型参数不确定项以及外界环境干扰未知情况,提出一种基于扩张观测器的欠驱动船舶轨迹跟踪低频学习自适应动态面输出反馈控制策略.该策略构造扩张观测器估计船舶速度向量,利用神经网络算法逼近模型参数不确定项,然后采用动态面控制技术避免对虚拟控制律直接求导,简化控制律计算过程,并引入低频增益学习技术消除外界扰动导致控制信号产生高频振荡,最后选取李雅普诺夫函数证明该控制律能够保证船舶跟踪闭环系统中所有误差信号一致最终有界.仿真结果表明,本文所设计控制器对船舶模型参数不确定项及外界环境干扰具有较强的鲁棒性,能够实现对船舶轨迹的有效跟踪.     

基于模糊不确定观测器的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的四旋翼飞行器,提出了一种基于模糊不确定观测器（Fuzzy uncertainty observer,FUO）的自适应动态面轨迹跟踪控制方法.通过将四旋翼飞行器系统分解为位置、姿态角和角速率三个动态子系统,使得各子系统虚拟控制器能够充分考虑欠驱动约束;采用一阶低通滤波器重构虚拟控制信号及其一阶导数,实现四旋翼跟踪控制设计的迭代解耦;设计了一种模糊不确定观测器,用以估计和补偿未知外界扰动与系统不确定性,从而确保闭环系统的稳定性和跟踪误差与其他系统信号的一致有界性.仿真研究验证了所提出的控制方法的有效性和优越性.     

Investigations on the Hybrid Tracking Control of an Underactuated Autonomous Underwater Robot

The problem of trajectory tracking control of an underactuated autonomous underwater robot (AUR) in a three-dimensional (3-D) space is investigated in this paper. The control of an underactuated robot is different from fully actuated robots in many aspects. In particular, these robot systems do not satisfy Brockett's necessary condition for feedback stabilization and no continuous time-invariant state feedback control law exists that makes a specified equilibrium of the closed-loop system asymptotically stable. The uncertainty of hydrodynamic parameters, along with the coupled, nonlinear dynamics of the underwater robot, also makes the navigation and tracking control a difficult task. The proposed hybrid control law is developed by combining sliding mode control (SMC) and classical proportional–integral–derivative (PID) control methods to reduce the tracking errors arising out of disturbances, as well as variations in vehicle parameters like buoyancy. Here, a trajectory planner computes the body-fixed linear and angular velocities, as well as vehicle orientations corresponding to a given 3-D inertial trajectory, which yields a feasible 6-d.o.f. trajectory. This trajectory is used to compute the control signals for the three available controllable inputs by the hybrid controller. A supervisory controller is used to switch between the SMC and PID control as per a predefined switching law. The switching function parameters are optimized using Taguchi design techniques. The effectiveness and performance of the proposed controller is investigated by comparing numerically with classical SMC and traditional linear control systems in the presence of disturbances. Numerical simulations using the full set of nonlinear equations of motion show that the controller does quite well in dealing with the plant nonlinearity and parameter uncertainties for trajectory tracking. The proposed controller response shows less tracking error without the usually present control chattering. Some practical features of this control law are also discussed.     

基于非线性迭代滑模的欠驱动UUV三维航迹跟踪控制

为实现欠驱动无人水下航行器(Unmanned underwater vehicle, UUV)在未知海流干扰作用下的三维航迹跟踪控制, 提出一种基于工程解耦思想设计的非线性迭代滑模航迹跟踪控制器. 基于虚拟向导的方法,建立UUV空间航迹跟踪误差方程;采用迭代方法设计非线性滑模控制器, 无需对UUV模型参数不确定部分和海流干扰进行估计,避免了舵的抖振现象以及减小了稳态误差与超调问题. 仿真实验表明,设计的控制器对欠驱动UUV系统的模型参数摄动及海流干扰变化不敏感、 且设计参数易于调节,可以实现三维航迹的精确跟踪.     

基于一阶不确定项估计律的机械臂鲁棒控制研究

针对多自由度机械臂控制系统的模型参数误差、关节摩擦力以及外部输入扰动等不确定项,设计了一类一阶误差估计律;结合基于机构动力学名义模型的输入输出反馈线性化控制算法,对六自由度刚性机械臂的时变轨迹跟踪控制进行了研究,理论上证明了设计的鲁棒控制器是全局渐进稳定的.仿真结果表明该控制策略对系统的各类不确定项具有很好的鲁棒性,能够实现高精度的轨迹跟踪控制.     

Event-triggered-based finite-time cooperative path following control for underactuated multiple marine surface vehicles

This paper develops an event-triggered-based finite-time cooperative path following (CPF) control scheme for underactuated marine surface vehicles (MSVs) with model parameter uncertainties and unknown ocean disturbances. First, a finite-time extended state observer (FTESO) is proposed, in which the FTESO can estimate the velocities and compound disturbances in finite time. Then, the finite-time LOS guidance law based on velocity estimation values is designed to obtain the desired surge velocity and the desired yaw rate. In order to realize the cooperative control of multiple paths in finite time, the cooperative control law for the path variable is designed. In addition, the relative threshold event-triggered control (ETC) mechanism is incorporated into the formation control algorithm, and an event-triggered-based finite-time CPF controller is designed, which not only effectively reduces the update frequency of controller and the mechanical loss of actuator but also improves the control performance of system. Furthermore, by using homogeneous method, Lyapunov theory, and finite-time stability theory, it is proved that under the proposed finite-time CPF control scheme, the formation errors can converge to a small neighborhood around origin in finite time. Finally, numerical simulation results illustrate the effectiveness of the proposed control scheme.     

Active DIsturbance Rejection Control of Surface Vessels Using Composite Error Updated Extended State Observer

In this paper, a composite‐errors‐based active disturbance rejection control law is proposed for surface vessels with exogeneous disturbances. The low‐frequency disturbances from wind, wave and ocean currents are estimated by a novel composite‐errors‐based extended state observer (ESO). Since the composite errors are composed of trajectory tracking errors and estimation errors, the disturbance rejection control is feedforward‐feedback composite control. The advantages of feedforward control and feedback control are exploited to reject system disturbances. Compared with conventional ESO‐based active disturbance rejection control, smaller estimation errors and smaller tracking errors can be achieved by the proposed disturbance compensation control. The effectiveness and superiority of the designed control law are illustrated by theoretical analysis and simulation results.