## What is/are Strict Feedback Form?

Strict Feedback Form - In this paper, the adaptive prescribed performance tracking control of nonlinear asymmetric input saturated systems in strict-feedback form is addressed under the consideration of model uncertainties and external disturbances.^{[1]}This article investigates the issue of neuro-fuzzy-based adaptive dynamic surface control (DSC) for uncertain fractional-order (FO) nonlinear systems in strict-feedback form where input constraint is considered in the systems.

^{[2]}In this article, an observer-based fuzzy adaptive inverse optimal output feedback control problem is studied for a class of nonlinear systems in strict-feedback form.

^{[3]}This paper solves the fault-tolerant control (FTC) problem of uncertain nonlinear systems in nonstrict-feedback form.

^{[4]}The difficulty of control design is to use the state observer to estimate unmeasurable states for nonstrict-feedback form in the fixed-time convergence setting.

^{[5]}In our proposed design procedure, the structural feature of Gaussian functions is utilized to conquer the obstruction of nonstrict-feedback form.

^{[6]}Specifically, by utilizing coordinate transformation and Euler approximation, the discrete strict-feedback form is obtained, and the backstepping technique can be applied.

^{[7]}This paper examines the adaptive control of high-order nonlinear systems with strict-feedback form.

^{[8]}Moreover, the attitude dynamics are in the strict-feedback form; thus the incremental backstepping sliding mode control is applied.

^{[9]}Moreover, the attitude dynamics are in the strict-feedback form; thus the incremental backstepping sliding mode control is applied.

^{[10]}The dynamics of each following agent is unknown, obeying a strict-feedback form.

^{[11]}In this paper, the dynamic event-triggered tracking control issue is studied for a class of unknown stochastic nonlinear systems with strict-feedback form.

^{[12]}The method is capable of dealing with nonlinear stochastic systems in strict-feedback form with any unknown dynamics.

^{[13]}In this article, a robust adaptive learning control strategy for uncertain single-input–single-output systems in strict-feedback form and controllability canonical form (CCF) is studied.

^{[14]}Combining neural networks technology, graph theory, fast finite-time control theory and backstepping recursive design scheme, the uncertainties and non-strict-feedback form are considered to propose a distributed adaptive FTC protocol which can guarantee tracking error reaching a region in finite time.

^{[15]}This paper investigates the distributed containment maneuvering problem for uncertain nonlinear multiagent systems in multiple-input multiple-output (MIMO) strict-feedback form.

^{[16]}This paper is concerned with the problem of adaptive event-triggered tracking control for a class of uncertain stochastic nonlinear systems in strict-feedback form.

^{[17]}This paper addresses the fixed-time adaptive fuzzy control problem for a class of uncertain non-linear systems in non-strict-feedback form.

^{[18]}The considered dynamics are accompanied by the uncertain strict-feedback form, actuator faults and unknown disturbances.

^{[19]}The radial basis function (RBF) NNs are used to deal with the algebraic loop problem from the nonstrict-feedback formation based on the approximation structure.

^{[20]}By transforming the plant to the pseudo-strict-feedback form that has affine appearance of state variables to be used as the virtual controls, it circumvents the implicit algebraic control equation arising from applying the traditional backstepping method and avoids the introduction of dynamics for virtual controls as Zhang et al.

^{[21]}New control procedures for finite-time stabilization of discrete-time nonlinear systems in the strict-feedback form are proposed.

^{[22]}The approach is more general than methods based on feedback linearization or backstepping as it does not require invertibility or the system be in strict-feedback form.

^{[23]}Initially, the traditional backstepping controller is designed for a generalized nonlinear plant in strict-feedback form that is subsequently extended to the ETC.

^{[24]}Each agent is considered in a non-affine nonstrict-feedback form under input saturation and output constraint which contains unknown dynamics and external disturbances.

^{[25]}In this article, an adaptive fuzzy output-feedback tracking control scheme is proposed for a class of single-input and single-output uncertain switched nonlinear systems in nonstrict-feedback form with prescribed performance and arbitrary switching.

^{[26]}In this paper, the tracking control problem is researched for nonlinear systems in the presence of the uncertain smooth functions, the strict-feedback form, input delay and input dead-zone.

^{[27]}In this article, the problem of robust tracking control is investigated for a class of discrete-time switched nonlinear uncertain system in strict-feedback form, and a novel robust neural tracking control scheme through backstepping technique is proposed for the first time.

^{[28]}This paper proposes a novel distributed optimal backstepping control method for a class of nonlinear multi-agent systems in strict-feedback form with output constraints.

^{[29]}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.

^{[30]}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.

^{[31]}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.

^{[32]}Firstly, velocity and altitude subsystems in the strict feedback formulations are obtained by decomposing the longitudinal dynamics of flexible air-breathing hypersonic vehicle, while uncertainties with regard to flexible effects, aerodynamic parameter uncertainties, modeling errors, and external disturbances are formed as the lumped disturbances which are excellently estimated by the proposed adaptive neural network disturbance observer with the adaptive regulation laws of weight matrices.

^{[33]}The construction applies to Luenberger observers and high-gain observers for plants in strict feedback form.

^{[34]}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.

^{[35]}The controlled system is in a non-strict feedback form.

^{[36]}The backstepping technology is employed as the main control framework since the ship course can be modeled in the strict feedback form.

^{[37]}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).

^{[38]}This paper investigates a finite-time control problem of nonlinear quantized systems with actuator dead-zone in a non-strict feedback form.

^{[39]}Each agent is in the strict feedback form with nonlinear functions in drift and diffusion terms and admitting time-varying incremental rates.

^{[40]}By introducing appropriate coordinate transform, it is shown that the error dynamics of AUVs can be arranged in the strict feedback form.

^{[41]}The radial basis function neural networks are employed to cope with the unknown non-linearities caused by the non-linear non-strict feedback form.

^{[42]}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.

^{[43]}Each follower agent is described by a high-order nonlinear dynamics in strict feedback form with input constraints.

^{[44]}Firstly, the dynamic model of GSP is transformed into a strict feedback formulation by designed FD to facilitate the backstepping control system.

^{[45]}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.

^{[46]}First, the Euler-Lagrange model of the general form of UMSs is transformed into block-strict feedback form.

^{[47]}Unlike previous results, the studied systems are not necessarily feedback linearizable nor in a strict feedback form.

^{[48]}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.

^{[49]}Since surface vessel systems are modeled by second-order dynamic in strict feedback form, backstepping is an ideal technique for finishing the tracking task.

^{[50]}

## single input single

In this paper, the adaptive fuzzy backstepping control problem is considered for a class of single-input single-output (SISO) unknown uncertain nonaffine nonlinear systems in strict-feedback form.^{[1]}In this work, the fuzzy adaptive output feedback control is investigated for single-input single-output (SISO) uncertain nonlinear systems in strict-feedback form.

^{[2]}The current paper addresses the fuzzy adaptive tracking control via output feedback for single-input single-output (SISO) nonlinear systems in strict-feedback form.

^{[3]}

## adaptive backstepping control

This article addresses an adaptive backstepping control design for uncertain fractional-order nonlinear systems in the strict-feedback form subject to unknown input quantization, unknown state-depe.^{[1]}

## nonlinear time delay

This article presents a solution to event-triggered stabilization of a class of nonlinear time-delay systems in the strict-feedback form.^{[1]}