Strict Feedback(严格反馈)研究综述
Strict Feedback 严格反馈 - Unlike the classical backstepping strategy, the control issue of nonlinear system in non-strict feedback(NSF) form is more challenging. [1]与经典的反推策略不同，非严格反馈（NSF）形式的非线性系统的控制问题更具挑战性。 [1]
output feedback control 输出反馈控制
In this paper, a novel fuzzy adaptive output-feedback control design scheme is concerned for a class of non-strict feedback switched nonlinear systems. [1] This paper focuses on fuzzy adaptive practical finite-time output feedback control problem for a class of single-input and single-output nonlinear system with time-varying delays in nonstrict feedback form. [2] This paper mainly investigates the problem of event-triggered output feedback control for a class of strict feedback systems that satisfies a prescribed performance. [3] This paper proposes an adaptive fuzzy output feedback control approach based on nonlinear tracking differentiator for a class of strict feedback systems with input saturation, unknown nonlinear functions and unmeasurable states. [4]本文针对一类非严格反馈切换非线性系统，提出了一种新颖的模糊自适应输出反馈控制设计方案。 [1] 本文重点研究了一类非严格反馈形式的时变时滞单输入单输出非线性系统的模糊自适应实际有限时间输出反馈控制问题。 [2] 本文主要研究了一类满足规定性能的严格反馈系统的事件触发输出反馈控制问题。 [3] 针对一类输入饱和、非线性函数未知、状态不可测的严格反馈系统，提出一种基于非线性跟踪微分器的自适应模糊输出反馈控制方法。 [4]
finite time adaptive
This work investigates a finite-time adaptive fuzzy tracking control problem for a class of nonstrict feedback nonlinear systems from a new point of view. [1] The problem of finite time adaptive control for stochastic nonlinear system is studied in this paper, where the system has a non-strict feedback structure. [2] This paper investigates the finite-time adaptive fuzzy control problem for a class of multi-input and multi-output (MIMO) nonlinear nonstrict feedback systems. [3]这项工作从一个新的角度研究了一类非严格反馈非线性系统的有限时间自适应模糊跟踪控制问题。 [1] 本文研究了随机非线性系统的有限时间自适应控制问题，该系统具有非严格的反馈结构。 [2] nan [3]
finite time control 有限时间控制
This article investigates the neural network-based finite-time control issue for a class of nonstrict feedback nonlinear systems, which contain unknown smooth functions, input saturation, and error constraint. [1] The problem of event-triggered neural adaptive fault-tolerant finite-time control is investigated for a class of nonstrict feedback nonlinear systems in the presence of nonaffine nonlinear faults. [2] This paper solves the adaptive fuzzy finite-time control (AFFTC) problem for nonstrict feedback nonlinear systems with state constraints. [3]本文研究了一类包含未知平滑函数、输入饱和和误差约束的非严格反馈非线性系统的基于神经网络的有限时间控制问题。 [1] 研究了一类非严格反馈非线性系统在存在非仿射非线性故障时的事件触发神经自适应容错有限时间控制问题。 [2] nan [3]
fault tolerant control 容错控制
The finite-time consensus fault-tolerant control (FTC) tracking problem is studied for the nonlinear multi-agent systems (MASs) in the nonstrict feedback form. [1] A filter and neural network (NN) based fault tolerant control (FTC) strategy is developed for a family of nonlinear systems expressed in strict feedback form in the event of unknown system dynamics and actuator failures. [2] In this article, an adaptive fuzzy fault-tolerant control problem is investigated for a class of fractional order non-strict feedback nonlinear systems with actuator faults, where the unknown nonlinear functions are approximated by fuzzy logic systems. [3]研究了非严格反馈形式的非线性多智能体系统（MAS）的有限时间一致性容错控制（FTC）跟踪问题。 [1] 为一系列非线性系统开发了一种基于滤波器和神经网络 (NN) 的容错控制 (FTC) 策略，以在未知系统动力学和执行器故障的情况下以严格的反馈形式表示。 [2] nan [3]
finite time tracking 有限时间跟踪
This paper considers the adaptive fuzzy finite-time tracking control for a class of uncertain stochastic nonlinear non-strict feedback systems with input saturation. [1] This article addresses the finite-time tracking control for multi-input and multi-output (MIMO) nonlinear nonstrict feedback systems with actuator faults and saturations. [2] In this article, a decentralized adaptive finite-time tracking control scheme is proposed for a class of nonstrict feedback large-scale nonlinear interconnected systems with disturbances. [3]本文研究了一类输入饱和的不确定随机非线性非严格反馈系统的自适应模糊有限时间跟踪控制。 [1] 本文讨论了具有执行器故障和饱和的多输入多输出 (MIMO) 非线性非严格反馈系统的有限时间跟踪控制。 [2] nan [3]
event triggered output 事件触发输出
In this paper, the adaptive event-triggered output regulation problem for the parametric strict feedback system is addressed. [1] ABSTRACT In this paper, an adaptive fuzzy event-triggered output feedback control scheme is studied for a class of non-strict feedback systems with tracking error constrained and unknown dead-zone. [2]在本文中，解决了参数严格反馈系统的自适应事件触发输出调节问题。 [1] 摘要 本文针对一类具有跟踪误差约束和未知死区的非严格反馈系统，研究了一种自适应模糊事件触发输出反馈控制方案。 [2]
high order nonlinear 高阶非线性
Thus, we study the finite-time fuzzy adaptive error constraint control problem for stochastic high-order nonlinear nonstrict feedback systems. [1] Since existing results about fixed-time stabilization are only applied to strict feedback systems, this paper investigates the nonsingular fixed-time stabilization of more general high-order nonlinear systems. [2]因此，我们研究了随机高阶非线性非严格反馈系统的有限时间模糊自适应误差约束控制问题。 [1] 由于现有的固定时间镇定结果仅适用于严格的反馈系统，本文研究了更一般的高阶非线性系统的非奇异固定时间镇定。 [2]
adaptive neural network 自适应神经网络
In this paper, an adaptive neural network (NN) constraint control method is studied for a class of uncertain nonlinear nonstrict feedback systems with state constraints. [1] The adaptive neural network asymptotic tracking control issue of nonstrict feedback stochastic nonlinear systems is studied in our article by adopting backstepping algorithm. [2]本文研究了一类具有状态约束的不确定非线性非严格反馈系统的自适应神经网络（NN）约束控制方法。 [1] 本文采用反推算法研究了非严格反馈随机非线性系统的自适应神经网络渐近跟踪控制问题。 [2]
tracking control problem 跟踪控制问题
This paper addresses the adaptive tracking control problem for a class of strict feedback nonlinear systems subject to input saturation and output constraint. [1] The H∞ tracking control problem is investigated for a class of incommensurate fractional order strict feedback nonlinear systems with unknown nonlinear functions and external disturbances in this paper. [2]本文解决了一类受输入饱和和输出约束的严格反馈非线性系统的自适应跟踪控制问题。 [1] 本文研究了一类非线性函数和外部扰动未知的不通约分数阶严格反馈非线性系统的H∞跟踪控制问题。 [2]
nonlinear multi agent 非线性多智能体
Aiming at a class of high-order strict feedback nonlinear multi-agent systems with communication constraints, a novel distributed adaptive back-stepping control method is proposed to cooperatively track the moving targets. [1]针对一类具有通信约束的高阶严格反馈非线性多智能体系统，提出了一种新的分布式自适应反步控制方法来协同跟踪运动目标。 [1]
Order Strict Feedback 订单严格反馈
In this work, a backstepping controller design for fractional-order strict feedback systems is investigated and the neural network control method is used. [1] The H∞ tracking control problem is investigated for a class of incommensurate fractional order strict feedback nonlinear systems with unknown nonlinear functions and external disturbances in this paper. [2] Aiming at a class of high-order strict feedback nonlinear multi-agent systems with communication constraints, a novel distributed adaptive back-stepping control method is proposed to cooperatively track the moving targets. [3] In this paper, the leaderless consensus control of a group of high-order strict feedback nonlinear systems with uncertainties under sensor and actuator attacks is considered. [4] In this paper, adaptive fractional control design is established for uncertain nonlinear fractional order strict feedback form systems with unknown actuator failures. [5]在这项工作中，研究了分数阶严格反馈系统的反步控制器设计，并使用了神经网络控制方法。 [1] 本文研究了一类非线性函数和外部扰动未知的不通约分数阶严格反馈非线性系统的H∞跟踪控制问题。 [2] 针对一类具有通信约束的高阶严格反馈非线性多智能体系统，提出了一种新的分布式自适应反步控制方法来协同跟踪运动目标。 [3] 在本文中，考虑了传感器和执行器攻击下一组具有不确定性的高阶严格反馈非线性系统的无领导一致性控制。 [4] 本文针对具有未知执行器故障的不确定非线性分数阶严格反馈形式系统建立了自适应分数控制设计。 [5]
Uncertain Strict Feedback
The problem of adaptive leaderless consensus control of a class of uncertain strict feedback nonlinear systems with guaranteed transient performance is investigated in this paper. [1] In order to stabilize multiple-input–multiple-output uncertain strict feedback nonlinear systems with time-varying full-state constraints and external disturbances, an adaptive neural dynamic surface control method is investigated in this paper. [2]Parametric Strict Feedback
In this paper, the adaptive event-triggered output regulation problem for the parametric strict feedback system is addressed. [1] Moreover, we avoid transformation to parametric strict feedback form usually needed when using backstepping control as PWM converters are not transformable. [2]在本文中，解决了参数严格反馈系统的自适应事件触发输出调节问题。 [1] nan [2]
Nonlinear Strict Feedback 非线性严格反馈
By using event-triggered technology, consensus control of multi-agent systems (MASs) with nonlinear strict feedback dynamics and directed graph will be investigated in this technical note. [1] Firstly, the line-of-sight (LOS) decoupling principle of strapdown seeker was performed on the traditional integrated guidance and control (IGC) model to deal with the problem of FOV constraint, and then the actuator saturation was employed to build a nonlinear strict feedback state equation with unmatched uncertainties. [2]通过使用事件触发技术，本技术说明将研究具有非线性严格反馈动力学和有向图的多智能体系统 (MAS) 的一致性控制。 [1] 首先在传统的集成制导与控制（IGC）模型上执行捷联导引头的视距（LOS）解耦原理来处理FOV约束问题，然后利用执行器饱和构建非线性严格具有无与伦比的不确定性的反馈状态方程。 [2]
strict feedback form 严格的反馈表
The Inverted-Pendulum system is not in strict feedback form therefore backstepping procedure cannot be directly applied. [1] The nonlinear system with partially unmeasurable states is transformed into the non-strict feedback form, firstly. [2] The finite-time consensus fault-tolerant control (FTC) tracking problem is studied for the nonlinear multi-agent systems (MASs) in the nonstrict feedback form. [3] This paper considers the leader-following consensus for a class of nonlinear switched multi-agent systems (MASs) with non-strict feedback forms and input saturations under unknown switching mechanisms. [4] A filter and neural network (NN) based fault tolerant control (FTC) strategy is developed for a family of nonlinear systems expressed in strict feedback form in the event of unknown system dynamics and actuator failures. [5] The controller was implemented based on the dynamical bicycle model, the model was modified by adding the errors dynamics as state variables and then converting it to the strict feedback form for the backstepping control implementation. [6] Therefore, in this article, a novel adaptive switching dynamic surface control (DSC) strategy is first presented for fractional-order nonlinear systems in the nonstrict feedback form with unknown dead zones and arbitrary switchings. [7] The nonlinear internal dynamics of WMR pose serious challenges to design a suitable controller due to its internal dynamics being not minimum phase and non-strict feedback form structure. [8] Firstly, the AHV dynamic model is transformed into a strict feedback form. [9] The lateral dynamics consist of lateral offset error and yaw error dynamics and can be interpreted as a semi-strict feedback form. [10] In the present study, dynamics is first converted into strict feedback form and then backstepping control scheme is implemented to execute high alpha herbst maneuver under significant lateral center-of- gravity shift. [11] The considered stochastic MASs in nonstrict feedback form is subject to unknown nonlinear functions and stochastic disturbances, which can be solved by exploiting the universal approximation property of radial basis function neural networks. [12] Firstly, the nonlinear and uncertainty state equation with non-strict feedback form for IGC design is derived by using the strap-down decoupling strategy. [13] Aiming at a state space model of the flexible-joint manipulator system with strict feedback form, the H∞ tracking controller of the system is designed based on backstepping method, robust H∞ control theory and Lyapunov stability theory. [14] This paper focuses on fuzzy adaptive practical finite-time output feedback control problem for a class of single-input and single-output nonlinear system with time-varying delays in nonstrict feedback form. [15] This paper investigates the event-based leader-following consensus problem for high-order nonlinear multiagent systems whose dynamics are in strict feedback forms and satisfy Lipschitz condition. [16] The construction applies to Luenberger observers and high-gain observers for plants in strict feedback form. [17] Firstly, an IGC design model is innovatively established in a strict feedback form which selects the normal overload as the system state in replace of the angle of attack so that the system states both are measurable. [18] The controlled system is in a non-strict feedback form. [19] The backstepping technology is employed as the main control framework since the ship course can be modeled in the strict feedback form. [20] Firstly, we transform the longitudinal model of AHV-VGI into the strict feedback form and multiple nonlinear aerodynamic models are built with different elongation distance of translating cowl(EDTC). [21] This paper investigates a finite-time control problem of nonlinear quantized systems with actuator dead-zone in a non-strict feedback form. [22] Each agent is in the strict feedback form with nonlinear functions in drift and diffusion terms and admitting time-varying incremental rates. [23] By introducing appropriate coordinate transform, it is shown that the error dynamics of AUVs can be arranged in the strict feedback form. [24] The radial basis function neural networks are employed to cope with the unknown non-linearities caused by the non-linear non-strict feedback form. [25] In this paper, an observer-based adaptive control problem for a class of high-order switched nonlinear systems in non-strict feedback form with fuzzy dead zone and arbitrary switchings is investigated. [26] Each follower agent is described by a high-order nonlinear dynamics in strict feedback form with input constraints. [27] This paper investigates adaptive fuzzy output feedback fault-tolerant optimal control problem for a class of single-input and single-output nonlinear systems in strict feedback form. [28] First, the Euler-Lagrange model of the general form of UMSs is transformed into block-strict feedback form. [29] Unlike previous results, the studied systems are not necessarily feedback linearizable nor in a strict feedback form. [30] In this paper, adaptive fractional control design is established for uncertain nonlinear fractional order strict feedback form systems with unknown actuator failures. [31] This paper focuses on an output feedback stabilization problem for a class of switched nonlinear systems in non-strict feedback form under asynchronous switching via sampled-data control. [32] Since surface vessel systems are modeled by second-order dynamic in strict feedback form, backstepping is an ideal technique for finishing the tracking task. [33] Firstly, the original six-degree-of-freedom aircraft model is analyzed and simplified, and the model with strict feedback form is obtained. [34] Kinematics and dynamics of the attitude are in the strict feedback form, which leads the backstepping control strategy serving as the baseline controller. [35] In this study, we consider the stabilization of a class of cascaded nonlinear systems in strict feedback form with unknown dynamics and known relative order. [36] This paper studies the fuzzy adaptive distributed event-based control scheme for a class of uncertain nonlinear multiagent systems in strict feedback form. [37] Moreover, we avoid transformation to parametric strict feedback form usually needed when using backstepping control as PWM converters are not transformable. [38] The considered system is in non-strict feedback form with unknown time-varying delay. [39]倒立摆系统不是严格的反馈形式，因此不能直接应用反推程序。 [1] 首先将具有部分不可测状态的非线性系统转化为非严格反馈形式。 [2] 研究了非严格反馈形式的非线性多智能体系统（MAS）的有限时间一致性容错控制（FTC）跟踪问题。 [3] 本文考虑了在未知切换机制下具有非严格反馈形式和输入饱和的一类非线性切换多智能体系统 (MAS) 的领导者跟随共识。 [4] 为一系列非线性系统开发了一种基于滤波器和神经网络 (NN) 的容错控制 (FTC) 策略，以在未知系统动力学和执行器故障的情况下以严格的反馈形式表示。 [5] 控制器基于动态自行车模型实现，模型通过添加误差动态作为状态变量进行修改，然后将其转换为严格的反馈形式，用于反步控制实现。 [6] 因此，在本文中，首先针对具有未知死区和任意切换的非严格反馈形式的分数阶非线性系统提出了一种新颖的自适应切换动态表面控制（DSC）策略。 [7] WMR的非线性内部动力学对设计合适的控制器提出了严峻的挑战，因为它的内部动力学不是最小相位和非严格的反馈形式结构。 [8] 首先，将 AHV 动态模型转化为严格的反馈形式。 [9] 横向动力学由横向偏移误差和偏航误差动力学组成，可以解释为半严格的反馈形式。 [10] 在本研究中，首先将动力学转换为严格的反馈形式，然后实施反步控制方案以在显着横向重心偏移的情况下执行高阿尔法 Herbst 机动。 [11] 所考虑的非严格反馈形式的随机 MAS 受到未知非线性函数和随机扰动的影响，这可以通过利用径向基函数神经网络的通用逼近特性来解决。 [12] 首先，利用捷联解耦策略推导了用于IGC设计的具有非严格反馈形式的非线性和不确定状态方程。 [13] 针对具有严格反馈形式的柔性关节机械臂系统的状态空间模型，基于反推法、鲁棒H∞控制理论和Lyapunov稳定性理论设计了系统的H∞跟踪控制器。 [14] 本文重点研究了一类非严格反馈形式的时变时滞单输入单输出非线性系统的模糊自适应实际有限时间输出反馈控制问题。 [15] nan [16] nan [17] nan [18] nan [19] nan [20] nan [21] nan [22] nan [23] nan [24] nan [25] nan [26] nan [27] nan [28] nan [29] nan [30] 本文针对具有未知执行器故障的不确定非线性分数阶严格反馈形式系统建立了自适应分数控制设计。 [31] nan [32] nan [33] nan [34] nan [35] nan [36] nan [37] nan [38] nan [39]
strict feedback system 严格的反馈系统
In this paper, the adaptive event-triggered output regulation problem for the parametric strict feedback system is addressed. [1] The backstepping control method is a recursive design procedure that links the choice of a control Lyapunov function with the design of a feedback controller and guarantees global asymptotic stability of strict feedback systems. [2] In this work, a backstepping controller design for fractional-order strict feedback systems is investigated and the neural network control method is used. [3] Considering the strict feedback systems with partial time-varying state constraints, we divide the special systems into constrained subsystems and unconstrained subsystems. [4] Thus, we study the finite-time fuzzy adaptive error constraint control problem for stochastic high-order nonlinear nonstrict feedback systems. [5] State constraints further increase the difficulty of controller design and stability analysis, especially for nonstrict feedback systems. [6] In this paper, an adaptive neural network (NN) constraint control method is studied for a class of uncertain nonlinear nonstrict feedback systems with state constraints. [7] This paper investigates the reinforcement learning control design problem via multi-gradient recursive (MGR) for a general class of strict feedback systems. [8] This paper considers the adaptive fuzzy finite-time tracking control for a class of uncertain stochastic nonlinear non-strict feedback systems with input saturation. [9] This article addresses the finite-time tracking control for multi-input and multi-output (MIMO) nonlinear nonstrict feedback systems with actuator faults and saturations. [10] This article investigates the problem of finite-time fuzzy adaptive event-triggered control design for stochastic nonlinear nonstrict feedback systems with unmodeled dynamics. [11] In this paper a strict feedback system with time-varying full-state constraints is studied. [12] ABSTRACT In this paper, an adaptive fuzzy event-triggered output feedback control scheme is studied for a class of non-strict feedback systems with tracking error constrained and unknown dead-zone. [13] This article investigates the adaptive fuzzy control algorithm for a class of large-scale switched fractional-order nonlinear nonstrict feedback systems. [14] Since existing results about fixed-time stabilization are only applied to strict feedback systems, this paper investigates the nonsingular fixed-time stabilization of more general high-order nonlinear systems. [15] This paper mainly investigates the problem of event-triggered output feedback control for a class of strict feedback systems that satisfies a prescribed performance. [16] This paper proposes an adaptive fuzzy output feedback control approach based on nonlinear tracking differentiator for a class of strict feedback systems with input saturation, unknown nonlinear functions and unmeasurable states. [17] This paper investigates an observer-based neuro-adaptive prescribed performance control scheme for nonstrict feedback systems with consideration of unmeasurable states and expected output tracking performance constraint. [18] In this paper, an adaptive neural network controller is designed for non-strict feedback systems with full-state constraints. [19] We consider two classes of controllers for illustration of our ideas (i) a model reference NN adaptive controller for linear systems with matched uncertainty (ii) backstepping NN controller for strict feedback systems. [20] In the meanwhile, the proposed control scheme can be directly extended to a class of nonstrict feedback systems. [21] In this paper, we investigate the tracking control problem for a class of strict feedback systems with pregiven performance specifications as well as full-state constraints. [22] In this paper, the authors aim to address such a problem by considering controlling strict feedback systems with unknown actuator aging. [23] This paper investigates the finite-time adaptive fuzzy control problem for a class of multi-input and multi-output (MIMO) nonlinear nonstrict feedback systems. [24] ABSTRACT The distributed consensus output tracking problem is dealt with for a class of nonlinear semi-strict feedback systems in the presence of mismatched nonlinear uncertainties, external disturbances and uncertain nonlinear virtual control coefficients of the subsystems. [25] First of all, the considered plant is transferred into a strict feedback system on account of the implicit function theorem and mean value theorem. [26]在本文中，解决了参数严格反馈系统的自适应事件触发输出调节问题。 [1] 反推控制方法是一种递归设计过程，它将控制 Lyapunov 函数的选择与反馈控制器的设计联系起来，并保证严格反馈系统的全局渐近稳定性。 [2] 在这项工作中，研究了分数阶严格反馈系统的反步控制器设计，并使用了神经网络控制方法。 [3] 考虑到具有部分时变状态约束的严格反馈系统，我们将特殊系统分为有约束子系统和无约束子系统。 [4] 因此，我们研究了随机高阶非线性非严格反馈系统的有限时间模糊自适应误差约束控制问题。 [5] 状态约束进一步增加了控制器设计和稳定性分析的难度，尤其是对于非严格反馈系统。 [6] 本文研究了一类具有状态约束的不确定非线性非严格反馈系统的自适应神经网络（NN）约束控制方法。 [7] 本文通过多梯度递归 (MGR) 研究了针对一般类严格反馈系统的强化学习控制设计问题。 [8] 本文研究了一类输入饱和的不确定随机非线性非严格反馈系统的自适应模糊有限时间跟踪控制。 [9] 本文讨论了具有执行器故障和饱和的多输入多输出 (MIMO) 非线性非严格反馈系统的有限时间跟踪控制。 [10] 本文研究了具有未建模动力学的随机非线性非严格反馈系统的有限时间模糊自适应事件触发控制设计问题。 [11] 本文研究了具有时变全状态约束的严格反馈系统。 [12] 摘要 本文针对一类具有跟踪误差约束和未知死区的非严格反馈系统，研究了一种自适应模糊事件触发输出反馈控制方案。 [13] 本文研究了一类大规模切换分数阶非线性非严格反馈系统的自适应模糊控制算法。 [14] 由于现有的固定时间镇定结果仅适用于严格的反馈系统，本文研究了更一般的高阶非线性系统的非奇异固定时间镇定。 [15] 本文主要研究了一类满足规定性能的严格反馈系统的事件触发输出反馈控制问题。 [16] 针对一类输入饱和、非线性函数未知、状态不可测的严格反馈系统，提出一种基于非线性跟踪微分器的自适应模糊输出反馈控制方法。 [17] nan [18] nan [19] nan [20] nan [21] nan [22] nan [23] nan [24] nan [25] nan [26]