控制增益未知的多变量极值搜索系统神经网络自适应协同控制

针对一类控制增益未知的多变量极值搜索系统,提出了一种神经网络自适应协同控制方法.该方法利用协同控制实现状态变量之间的协同收敛,并确保对系统内部参数扰动和外界干扰具有不变性;以极值搜索控制方法得到的搜寻变量作为输入量,设计多层神经网络逼近状态变量的极值变化率和未知的变量与函数;采用Nussbaum函数解决系统控制增益未知的问题;同时运用自适应参数抵消神经网络逼近误差的影响.稳定性分析证明了系统的状态跟踪误差、输出量与其极值之间的误差、极值搜索变量的跟踪误差以及神经网络各参数的估计误差均指数收敛至原点的一个有界邻域.理论分析与仿真结果验证了该方法的有效性.     

多输入多输出非线性系统的受限滑模控制

本文针对一类具有执行器和状态约束的多输入多输出非线性系统,研究了基于高阶滑模观测器的滑模控制和稳定性分析问题,通过对该系统进行逆变换并考虑其控制输入系数矩阵的对合跨度分布,我们设计了一类高阶滑模观测器用于实现系统的状态估计,其中,采用鲁棒精确微分器分析了所得误差估计系统的收敛性.然后,利用原系统的部分状态变量设计了二阶...     

一种多输入-多输出模糊自适应控制方法的研究

针对多输入-多输出(MIM0)非线性系统基于模糊基函数向量提出了一种新的自适应控制方法.在该方法中,首先将非线性系统线性化,然后利用模糊基函数向量自适应学习系统不确定向量的上界,模糊基函数向量可作为补偿控制器的一个参数.在控制系统的设计过程中可充分保证非线性控制系统的鲁棒性和跟踪误差的渐进收敛性.     

多变量非线性系统的间接模糊输出反馈自适应控制

针对一类多输入多输出非线性不确定系统，提出一种基于观测器的模糊间接自适应控制方法，并基于李亚普诺夫函数方法，导出了输出反馈控制律以及参数的自适应律，证明了整个控制方案不但能保证闭环系统稳定，而且取得了良好的跟踪控制性能。     

一类增长率依赖输出的非线性系统的输出反馈输出跟踪控制

研究一类增长率依赖输出非线性系统的输出反馈输出跟踪控制问题.利用系统结构特点,构造出系统实现输出跟踪时内部状态的渐近轨迹.通过建立状态与渐近轨迹偏差的动态方程,将输出跟踪问题转化为偏差系统的镇定问题,然后通过设计偏差系统的输出反馈镇定控制器给出输出反馈输出跟踪控制器.最后以仿真实例验证本文结论.     

一类随机系统的输出跟踪

采用直接自适应控制律方法解决多输入单输出随机系统的变目标输出跟踪问题,同时主要分析了控制律作用下的该系统的稳定性,并给出了输出跟踪的较弱收敛性条件及仿真实例.     

多输入多输出非线性不确定系统连续高阶滑模控制

针对一类MIMO非线性不确定系统,提出一种新的连续高阶滑模控制算法.引入状态反馈使得系统高阶滑模控制问题等效转换为多变量不确定积分链的有限时间稳定问题,首先针对标称系统设计有限时间到达连续控制律,实现系统状态快速收敛,然后采用多变量非解耦形式超螺旋算法克服系统不确定性,实现鲁棒性,最终使得系统控制作用连续、滑模抖振得以大大抑制.基于二次型Lyapunov函数证明系统的有限时间稳定性.针对三阶不确定系统有限时间稳定和气垫船圆形航迹跟踪问题分别进行了仿真,验证了所提算法的有效性、鲁棒性.     

执行器故障不确定非线性系统最优自适应输出跟踪控制

本文针对一类具有执行器故障的多输入多输出（Multi-input multi-output,MIMO）不确定连续仿射非线性系统,提出了一种最优自适应输出跟踪控制方案.设计了保证系统稳定性的不确定项估计神经网络权值调整算法,仅采用评价网络即可同时获得无限时域代价函数和满足哈密顿-雅可比-贝尔曼（Hamilton-Jacobi-Bellman,HJB）方程的最优控制输入.考虑执行器卡死和部分失效故障,设计最优自适应补偿控制律,所设计的控制律可以实现对参考输出的一致最终有界跟踪.飞行器控制仿真和对比验证表明了本文方法的有效性和优越性.     

执行器有故障的多输入单输出系统的自适应输出反馈控制

对一类控制增益符号未知且执行器有故障的输出反馈多输入单输出非线性系统,提出了一种后推容错控制方案.该方案在系统状态不可量测的情况下,利用Nussbaum函数处理符号未知的常数增益,并通过构造K-滤波器来估计了系统不可量测的状态.在容错控制器设计过程中,引入变能量函数来处理利用虚拟控制律所无法抵消的部分.与现有研宄成果相比,放宽了未知增益需要上下界均为已知的假设条件.最后,通过选取合适的李雅普诺夫函数,证明了闭环系统所有信号半全局一致终结有界,且跟踪误差收敛到原点的一个小邻域内.仿真结果表明了所提控制方法的有效性.     

输出饱和多智能体系统的迭代学习趋同跟踪控制

针对带有输出饱和的多智能体系统有限时间趋同跟踪控制问题,提出了一种分布式迭代学习控制算法.首先假设多智能体系统具有固定拓扑结构,且仅有部分智能体可获取到期望轨迹信息.基于输出约束条件构造一致性跟踪误差,在此基础上设计了P型迭代学习控制率.然后采用压缩映射方法给出了一个算法收敛的充分条件,并在理论上证明了跟踪误差的收敛性.最后,将理论结果推广至具有随机切换拓扑结构的多智能体系统中.仿真结果验证了所提出算法的有效性.     

Constrained multivariable extremum-seeking for online fuel-efficiency optimization of Diesel engines

This work presents a new method for online fuel-efficiency optimization of Diesel engines, using constrained extremum-seeking. A two-input optimization problem, which is suitable for extremum-seeking, is integrated into a tracking control system. As a result, both air-path and fuel-path actuators are used for tracking and extremum-seeking. A key element of the proposed method is a cost function based on real-time BSFC estimation. Moreover, an existing constrained extremum-seeking method is extended to multiple output constraints. Experiments on a Euro-VI heavy-duty Diesel engine demonstrate the constraint handling, robustness with respect to real-world disturbances, and the fuel saving potential of the control design.     

An adaptive algorithm for control of combustion instability

We propose an adaptive algorithm for control of combustion instability suitable for reduction of acoustic pressure oscillations in gas turbine engines, and main burners and augmentors of jet engines over a large range of operating conditions, and supply an experimental demonstration of oscillation attenuation, the first for a large industrial-scale gas turbine combustor. The algorithm consists of an Extended Kalman Filter based frequency tracking observer to determine the in-phase component, the quadrature component, and the magnitude of the acoustic mode of interest, and a phase shifting controller actuating fuel-flow, with the controller phase tuned using extremum-seeking. The paper also identifies a closed-loop model with phase-shifting control of combustion instability from experimental data; supplies stability analysis of the adaptive scheme based upon the identified model, and stable extremum-seeking designs used in experiments.     

Discrete-time extremum-seeking for Wiener–Hammerstein plants

This paper presents a new formulation of extremum-seeking control for discrete-time Wiener–Hammerstein plants. A novel method of analysis using Linear Parameter-Varying (LPV) system theory demonstrates semi-global stability of the control scheme. Assuming only limited plant knowledge, the stability result ensures convergence of the plant output in steady state to a point in an arbitrarily small neighbourhood of the extremum, for appropriately chosen controller parameters. The behaviour of the control scheme is analysed on a simple simulated system, prior to being implemented on an internal combustion engine. Experiments demonstrate how the scheme is able to maximise engine output torque in the presence of an uncertain fuel composition by modifying the spark timing.     

无人机全电式自主刹车系统滑模极值搜索控制

常规主动刹车系统采用在线辨识跑道特征的算法,但仍需依赖摩擦模型先验知识,难以应对复杂跑道工况.为克服上述问题,提出一种滑模极值搜索控制策略并应用于无人机全电式自主刹车系统.考虑电动作动机构非线性特性,建立系统的状态空间模型并合理简化为严格反馈形式,采用超扭曲算法估计结合系数的梯度,结合反馈线性化控制律得到刹车压力参考值,证明此控制作用下可实现对未知最优滑移率的渐近跟踪.采用反演控制的思想设计无抖振滑模控制器实现对参考刹车压力的跟踪.利用Lyapunov方法获得系统的渐近稳定性条件并分析控制参数对系统的影响.半实物仿真试验结果表明控制策略的有效性.     

Global output-feedback extremum seeking for a class of nonlinear dynamic systems with arbitrary relative degree

ABSTRACT

An output-feedback sliding-mode-based extremum-seeking controller was recently introduced for linear uncertain systems by using periodic switching functions. Nonlinear systems were also considered but restricted to relative degree one plants as well as the former linear case. Here, generalisation is achieved to include more general dynamics with arbitrary relative degree, thanks to the introduction of a high-gain adaptive observer with updated gain. Global stability properties of the closed-loop system with convergence to a controlled neighbourhood of the desired maximum point are also rigorously proved. Simulation and experimental results illustrate the performance of the proposed extremum-seeking control algorithm.     

具有输入输出约束的无人直升机预设性能安全跟踪控制

针对无人直升机姿态与高度系统存在未知外部干扰、输入饱和、姿态与高度约束等问题, 本文提出一种具 有输入输出约束的预设性能安全跟踪控制方法. 首先, 针对无人直升机的姿态与高度约束, 通过设计一类边界保护 算法, 构建了新的安全期望跟踪信号. 为了保证系统对于安全期望跟踪信号的跟踪性能, 将预设性能函数与边界保 护算法进行结合, 并对跟踪误差进行转换. 针对系统的输入饱和现象, 使用Sigmoid函数进行逼近; 同时, 针对饱和函 数的逼近误差与未知外部干扰构成的复合干扰, 采用参数自适应方法对其上界进行逼近. 然后, 结合反步控制方法 设计了安全跟踪控制器, 并通过Lyapunov稳定性理论证明了闭环系统所有信号的收敛性, 保证了无人直升机的安全 跟踪性能. 最终, 通过数值仿真验证了所提控制方法的有效性.     

Novel MPC‐Based Fault Tolerant Tracking Control Against Sensor Faults

The problem of active fault‐tolerant tracking control with control input and system output constraints is studied for a class of discrete‐time systems subject to sensor faults. A time‐varying fault‐tolerant observer is first developed to estimate the real system state from the faulty sensor output and control input signals. Then by using the estimated state at each time step, a model predictive control (MPC)‐based fault‐tolerant tracking control scheme is presented to guarantee the desired tracking performance and the given input and output constraints on the faulty system. In comparison with many existing fault‐tolerant MPC methods, its main contribution is that the proposed state estimator is designed by the simple and online numerical computation to tolerate the possible sensor faults, so that the regular MPC algorithm without fault information can be adopted for the online calculation of fault‐tolerant control signal. The potential recursive infeasibility and computational complexity due to the faults are avoided in the scheme. Additionally, the closed‐loop stability of the post‐fault system is discussed. Simulative results of an electric throttle control system verify the effectiveness of the proposed method.     

Model Free Adaptive Control for a Class of Nonlinear Systems Using Quantized Information

This paper considers the stability of model free adaptive control systems with quantized information. Two quantized model free adaptive control (QMFAC) algorithms are proposed by using different signal quantization schemes, and here the logarithmic quantizer is introduced to decode these signals with a number of quantization levels. By using the sector bound method, the stability conditions of proposed QMFAC algorithms can be given and the effect of quantization error for such systems can also be discussed. It is shown that the tracking error under the QMFAC algorithm with system output quantized signal is proved to converge to a bound, and the bound depending on quantization density and desired trajectory. Thus, the tracking error under the QMFAC algorithm with tracking error quantized signal converges to zero. Two illustrative examples are given to validate the theoretical results.     

一类非线性系统模糊自适应固定时间量化反馈控制

研究了一类严格反馈不确定非线性系统的模糊自适应实际固定时间量化反馈控制问题. 基于李雅普诺夫有限时间稳定理论、自适应模糊控制理论及反演控制算法, 提出了一种非线性系统模糊自适应实际固定时间量化反馈跟踪控制方案. 所设计的控制方案能够保证闭环系统的输出跟踪误差在固定时间内收敛于原点的一个充分小邻域内, 且闭环系统内所有信号均有界. 最后, 数值示例验证了设计方案的有效性.