航天器全状态约束输出反馈控制

针对无角速度测量的刚性航天器姿态跟踪问题,提出一种全状态约束输出反馈控制方法.建立修正罗德里格参数描述的系统模型,提出能够适用于约束与非约束情况的改进型障碍李雅普诺夫函数(MBLF),拓展传统对数型障碍李雅普诺夫函数的适用范围.构造二阶辅助系统,将控制输入和饱和输入之间的差作为构造系统的输入,进而产生信号以补偿饱和的影响.设计状态观测器估计未知状态量,并结合反步法设计输出反馈控制律,保证系统全状态约束性能和姿态跟踪精度.通过李雅普诺夫稳定性分析证明姿态观测误差和跟踪误差能够达到一致最终有界.仿真结果验证所提方法的有效性.     

基于神经动态优化的非线性系统近似最优跟踪控制

提出一种输入约束下一类连续时间非线性系统最优跟踪控制问题的近似求解方法.针对有限时间跟踪性能指标下一类单输入单输出非线性系统,利用所提出的最优跟踪控制方法实现目标系统所对应性能指标近似最优.首先将系统的性能指标沿时间泰勒展开,得到一个近似的性能指标;其次,在系统状态可观测条件下,将该问题进一步转化为以控制输入为决策变量的非线性规划问题;再次,利用神经动态优化方法,求解含不等式约束下的近似最优控制问题并给出相应的递归神经网络模块原理图;进而,针对整个闭环系统进行理论分析,证明在一定条件下闭环系统的稳定性;最后,通过两个实例仿真验证所提出方法的有效性.     

约束非线性系统输入到状态稳定经济型模型预测控制

考虑约束非线性系统经济型最优控制问题,提出一种关于经济性能输入到状态稳定的经济型模型预测控制(EMPC)策略.通过离线计算系统的最优经济稳态点,构建关于该稳态点跟踪的稳定最优控制问题.在此基础上,利用稳定最优控制问题的最优值函数和关于经济性能函数的松弛量构造EMPC优化问题的收缩约束,再结合不变集原理和输入到状态稳定性...     

约束自适应反步法及其在飞行控制中的应用

为解决系统含有参数不确定性和(状态)执行器受限条件下的鲁棒自适应控制问题,将SISO系统指令滤波器推广到MIMO系统,提出一种基于指令滤波的自适应块控反步方法。在设计(虚拟)控制律时引入指令滤波器,在克服标准反步法虚拟控制律导数计算膨胀问题的同时,能够施加系统状态和执行器的限制条件,并通过引入扩展跟踪误差,有效解决了约束条件下参数估计过程的稳定性和跟踪误差收敛问题。给出了Lyapunov闭环稳定性证明,并将该方法应用于含有未知气动参数和输入饱和约束的飞行器非线性姿态控制器设计。6自由度飞行仿真表明,该控制器具有良好的指令跟踪能力和较强的鲁棒性。     

具有指定性能和全状态约束的多智能体系统事件触发控制

针对一类非严格反馈的非线性多智能体系统一致性跟踪问题,在考虑全状态约束和指定性能的基础上提出了一种事件触发自适应控制算法.首先,通过设计性能函数,使跟踪误差在规定时间内收敛于指定范围.然后,在反步法中引入Barrier Lyapunov函数使所有状态满足约束条件,结合动态面技术解决传统反步法产生的"计算爆炸"问题,并利用径向基函数神经网络（Radial basis function neural networks,RBF NNs）处理系统中的未知非线性函数.最后基于Lyapunov稳定性理论证明系统中所有信号都是半全局一致最终有界的,跟踪误差收敛于原点的有界邻域内且满足指定性能.仿真结果验证了该控制算法的有效性.     

具有输入及状态未建模动态系统的输出反馈自适应控制

针对一类具有输入及状态未建模动态的非线性系统, 设计K滤波器来估计系统不可量测状态, 基于动态面控制技术并利用径向基函数神经网络的逼近能力, 提出一种输出反馈自适应跟踪控制方案. 利用Nussbaum 函数性质, 有效地解决了高频增益符号未知问题. 在控制器设计中引入规范化信号来约束输入未建模动态, 从而有效地抑制其产生的扰动. 通过理论分析证明了闭环控制系统是半全局一致终结有界的.

     

状态约束下单连杆机械臂输出反馈自适应跟踪控制

研究了一类具有全状态约束且状态不可测的单连杆机械手跟踪控制问题。尽管现有的输出反馈跟踪控制方法可以有效地解决状态不可测情况下的机械手位置跟踪控制问题,但未考虑基于操作安全等因素设定的状态受限。同时,系统状态不可测也为实现状态受限带来了挑战。因此,考虑在系统全状态受限并且仅机械手位置可测情况下的输出反馈跟踪控制器设计问题。首先,构造了一个模糊状态观测器来估计不可测状态;然后,通过融合新的状态变换函数和动态表面控制方法,建立了一种基于观测器的自适应模糊控制策略,并利用李雅普诺夫稳定性理论,证明了位置跟踪误差将收敛到零点附近任意小的邻域之内,且系统中的状态永远不会超越约束条件;最后,通过数值模拟验证了所提方法的可行性。     

具有未知参数的机器人-摄像机系统的自适应动态反馈跟踪控制

研究了不确定非完整移动机器人系统的跟踪问题.首先,基于视觉反馈和状态输入变换,展示了一种非完整移动机器人运动学系统的不确定链式模型.基于反步法思想和跟踪误差系统结构,给出了两个重要的新变换.然后运用李雅普诺夫直接方法和扩展巴巴拉引理设计了自适应控制律和动态反馈鲁棒控制器,以实现理想轨迹的跟踪控制.严格证明了闭环误差系统的渐近收敛性.最后,仿真结果证实了提出的控制策略有效.     

基于状态观测器的直接约束鲁棒预测控制

针对多包描述线性离散不确定系统,提出一种在系统状态不可测时的直接约束鲁棒预测控制算法.将控制器与观测器综合设计,利用观测状态直接构造性能指标,通过求解无穷时域性能指标的最小最大优化问题,得到系统的最优状态反馈控制律.采用参数依赖Lyapunov函数,在满足输入和状态约束的情况下保证闭环系统稳定.仿真结果验证了算法的有效性.     

新型指令滤波反步及高超声速飞行器的应用

非线性严反馈系统的控制中,由于迭代和系统的设计过程,反步法成为研究热点之一。然而,由于需要推导虚拟控制的解析导数,传统反步法存在"计算膨胀"问题,当被控对象的系统阶数较高或模型较复杂时,"计算膨胀"问题更为严重,这限制了反步法在实际工程中的应用。因此,提出一类新型的指令滤波反步法,避免传统反步法中"计算膨胀"问题。该方法采用输入状态稳定性(Input-to-State Stability,ISS)和小增益定理保证闭环系统的稳定性,为严反馈系统的控制器设计提供了简洁有效的方式。针对高超声速飞行器巡航段纵向的速度和高度跟踪问题,综合指令滤波反步法和动态逆方法设计有效的状态反馈控制器,最后在数值仿真中验证了所设计的控制器能实现高超声速飞行器在爬升机动中对速度和高度的稳定跟踪。     

Observer-Based Adaptive Fuzzy Tracking Control Using Integral Barrier Lyapunov Functionals for A Nonlinear System With Full State Constraints

A new fuzzy adaptive control method is proposed for a class of strict feedback nonlinear systems with immeasurable states and full constraints. The fuzzy logic system is used to design the approximator, which deals with uncertain and continuous functions in the process of backstepping design. The use of an integral barrier Lyapunov function not only ensures that all states are within the bounds of the constraint, but also mixes the states and errors to directly constrain the state, reducing the conservativeness of the constraint satisfaction condition. Considering that the states in most nonlinear systems are immeasurable, a fuzzy adaptive states observer is constructed to estimate the unknown states. Combined with adaptive backstepping technique, an adaptive fuzzy output feedback control method is proposed. The proposed control method ensures that all signals in the closed-loop system are bounded, and that the tracking error converges to a bounded tight set without violating the full state constraint. The simulation results prove the effectiveness of the proposed control scheme.      

Distributed adaptive output feedback tracking control for a class of uncertain nonlinear multi-agent systems

This paper addresses the distributed output feedback tracking control problem for multi-agent systems with higher order nonlinear non-strict-feedback dynamics and directed communication graphs. The existing works usually design a distributed consensus controller using all the states of each agent, which are often immeasurable, especially in nonlinear systems. In this paper, based only on the relative output between itself and its neighbours, a distributed adaptive consensus control law is proposed for each agent using the backstepping technique and approximation technique of Fourier series (FS) to solve the output feedback tracking control problem of multi-agent systems. The FS structure is taken not only for tracking the unknown nonlinear dynamics but also the unknown derivatives of virtual controllers in the controller design procedure, which can therefore prevent virtual controllers from containing uncertain terms. The projection algorithm is applied to ensure that the estimated parameters remain in some known bounded sets. Lyapunov stability analysis shows that the proposed control law can guarantee that the output of each agent synchronises to the leader with bounded residual errors and that all the signals in the closed-loop system are uniformly ultimately bounded. Simulation results have verified the performance and feasibility of the proposed distributed adaptive control strategy.     

Observer-based adaptive fuzzy backstepping control of uncertain nonlinear pure-feedback systems

In this paper,a new fuzzy adaptive control approach is developed for a class of SISO uncertain pure-feedback nonlinear systems with immeasurable states.Fuzzy logic systems are utilized to approximate the unknown nonlinear functions;and the filtered signals are introduced to circumvent algebraic loop systems encountered in the implementation of the controller,and a fuzzy state adaptive observer is designed to estimate the immeasurable states.By combining the adaptive backstepping technique,an adaptive fuzzy output feedback control scheme is developed.It is proven that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded(SGUUB),and the observer and tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Simulation studies are included to illustrate the efectiveness of the proposed approach.     

Adaptive neural output feedback tracking control for a class of nonlinear systems

In this paper, an adaptive neural output feedback control scheme based on backstepping technique and dynamic surface control (DSC) approach is developed to solve the tracking control problem for a class of nonlinear systems with unmeasurable states. Firstly, a nonlinear state observer is designed to estimate the unmeasurable states. Secondly, in the controller design process, radial basis function neural networks (RBFNNs) are utilised to approximate the unknown nonlinear functions, and then a novel adaptive neural output feedback tracking control scheme is developed via backstepping technique and DSC approach. It is shown that the proposed controller ensures that all signals of the closed-loop system remain bounded and the tracking error converges to a small neighbourhood around the origin. Finally, two numerical examples and one realistic example are given to illustrate the effectiveness of the proposed design approach.     

基于混合系统模型的非线性系统最大可控不变集求解

针对非线性系统线性化在状态约束下最优鲁棒控制求解问题,提出了一种基于混合系统的分段仿射系统(PWA)建模,通过多次优化迭代的方法求解系统的最大鲁棒控制不变集的方法,并求得不变集内的最优控制器,解决系统的状态约束问题.通过一个非线性系统实例进行建模、仿真,证明了本方法的可行性.     

受限的非仿射非线性系统的自适应控制

针对受限的非仿射非线性系统,结合自抗扰思想提出了非仿射系统的扩张状态观测器(ESO)设计,从而将辅助系统设计技巧拓展到了非仿射系统,然后利用反演和指令滤波器设计了自适应控制器,为受限的不确定非仿射系统提供了新的设计思路.为了补偿受限带来的影响,引入了辅助系统,它的状态被用来补偿跟踪误差.指令滤波器用来处理虚拟控制受限问题,同时获得虚拟控制导数的估计,避免了backstepping中对它的繁琐计算,扩张状态观测器被用来估计系统的未知非仿射非线性项和外部干扰.利用输入状态稳定性(ISS)分析了闭环系统的全局一致有界稳定性.最后仿真结果验证了该设计方案的有效性.     

基于控制参数化的注塑工业过程最优反馈控制方法

本文针对一类典型的注塑工业过程系统, 研究了注塑填充过程中产生的熔体流动速度最优跟踪控制问题, 提出了一种基于控制参数化的计算最优反馈控制器设计方法以实现注塑过程中熔融聚合物流动前沿位移的最优跟 踪控制, 进而达到改善注塑零件性能的高效生产目标. 首先, 面向注塑工艺复杂生产过程建立了动态过程系统数学 模型, 提出了注塑机内部熔融聚合物流动前沿位置的动态最优跟踪控制问题; 其次, 设计了一种多级反馈控制律, 通 过控制参数化方法将控制反馈核进行了参数化表示, 将控制器设计问题转化为一序列最优参数决策问题; 然后, 通 过状态灵敏度方程分析方法, 求解出了目标函数及约束条件关于决策变量参数梯度信息的显式表达式, 并基于所提 供的梯度信息结合序列二次规划算法进行了高效优化迭代求解; 最后, 通过实验仿真验证了本文所提出的最优反 馈控制器设计方法的可行性和有效性.     

Observer-based Adaptive Fuzzy Backstepping Tracking Control of Quadrotor Unmanned Aerial Vehicle Powered by Li-ion Battery

In this paper, an Adaptive Fuzzy Backstepping Control (AFBC) approach with state observer is developed. This approach is used to overcome the problem of trajectory tracking for a Quadrotor Unmanned Aerial Vehicle (QUAV) under wind gust conditions and parametric uncertainties. An adaptive fuzzy controller is directly used to approximate an unknown nonlinear backstepping controller which is based on the exact model of the QUAV. Besides, a state observer is constructed to estimate the states. The stability analysis of the whole system is proved using Lyapunov direct method. Uniformly Ultimately Bounded (UUB) stability of all signals in the closed-loop system is ensured. The proposed control method guarantees the tracking of a desired trajectory, attenuates the effect of external disturbances such as wind gust, and solves the problem of unavailable states for measurement. Extended simulation studies are presented to highlight the efficiency of the proposed AFBC scheme.     

Observer-based backstepping force control of an electrohydraulic actuator

A backstepping approach is used in this paper to design a nonlinear controller for force control of a single-rod electrohydraulic actuator. The control design guarantees the convergence of the tracking error. The implementation of the control design requires system states for feedback, but in this case only the force output is available. To overcome this problem, a PI observer is used to estimate the states of the system. Experimental results have illustrated the success of the observer-based backstepping controller. The results are also compared to those obtained with conventional P and PI controllers. It can be shown that the observer-based backstepping controller has a relatively better tracking performance.     

受限指令预设性能自适应反演控制器设计

针对一类含参数不确定性的输入和状态受限的非线性系统,提出一种受限指令预设性能自适应反演控制器设计方法.采用自适应反演方法,同时考虑输入和状态受限构建受限指令滤波器,以解决“计算膨胀”的问题;引入伪控制减缓方法对误差进行补偿;最后考虑了补偿跟踪误差的瞬态性能.通过Lyapunov理论对所设计的控制器进行稳定性分析,并通过仿真实例验证了所提出方法的正确性和有效性.