In this paper, a partial tracking error constrained fuzzy output-feedback dynamic surface control (DSC) scheme is proposed for class of uncertain multi-input and multi-output (MIMO) nonlinear systems. The considered MIMO systems contain unknown functions without the requirement their states being available controller design. With help logic identifying systems, adaptive observer established to estimate unmeasured states. By transforming errors into new virtual variables based on DSC...

This paper investigates an adaptive fuzzy tracking control design problem for single-input and single-output uncertain nonstrict feedback nonlinear systems. For the cases of states measurable immeasurable, logic systems are separately adopted to approximate unknown functions or model In unified framework backstepping design, both state observer-based output schemes proposed. The stability closed-loop is proved by using Lyapunov function theory. simulation examples provided confirm...

In this paper, the problem of adaptive fuzzy decentralized optimal control is investigated for a class nonlinear large-scale systems in strict-feedback form. The considered contain unknown functions and unmeasured states. By utilizing logic to approximate cost functions, state observer established estimate design divided into two phases. First, by using backstepping technique, feedforward controller with parameters laws designed, which original controlled system transformed an equivalent...

This paper deals with the problem of adaptive fuzzy output feedback control for a class stochastic nonlinear switched systems. The controlled system in this possesses unmeasured states, completely unknown functions, unmodeled dynamics, and arbitrary switchings. A state observer which does not depend on switching signal is constructed to tackle states. Fuzzy logic systems are employed identify functions. Based common Lyapunov stability theory small-gain theorem, new robust backstepping...

This paper solves the stochastically finite-time control problem for uncertain stochastic nonlinear systems in nontriangular form. The considered controlled plants are different from previous results of systems, which multiple-input and multiple-output (MIMO) with unknown functions consisting all states, disturbance, immeasurable states. Fuzzy logic a state filter used to model estimate respectively. Based on theory Itȏ differential equation, novel stability theorem is first raised. By...

This paper solves the finite-time decentralized control problem for uncertain nonlinear large-scale systems in nonstrict-feedback form. The considered controlled plants are different from previous results of systems, which with unknown functions consisting all states, interactions, and immeasurable states. Fuzzy logic a filter-based state observer utilized to model deal respectively. By combining backstepping recursive design Lyapunov function theory, adaptive fuzzy approach is raised. It...

In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class uncertain switched nonlinear systems in strict-feedback form. The considered contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic are utilized to approximate functions, state observer designed thus states obtained by it. By applying backstepping design principle average dwell time method, an tracking approach developed. It proved that proposed can guarantee all...

This paper solves the finite-time switching control issue for nonstrict-feedback nonlinear switched systems. The controlled plants contain immeasurable states, arbitrarily switchings, and unknown functions which are constructed with whole states. Neural network is used to simulate uncertain systems a filter-based state observer designed estimate states in this paper, respectively. Based on backstepping recursive technique common Lyapunov function method, method presented. Due developed...

This article investigates the problem of neural network (NN)-based adaptive backstepping control design for stochastic nonlinear systems with unmodeled dynamics in finite-time prescribed performance. NNs are used to study uncertain plants, and is tackled by combination changing supply function dynamical signal methods. The outstanding contribution this that based on performance (FTPF), a modified NN strategy proposed, which makes controller simpler. Eventually, using Itô's differential...

This article investigates the problem of finite-time fuzzy adaptive event-triggered control design for stochastic nonlinear nonstrict feedback systems with unmodeled dynamics. The logic are adopted to identify unknown nonlinearities and a state observer is designed estimate unmeasured states. Using backstepping recursive combining it varying threshold condition, novel event-triggered-based algorithm developed, where dynamical signal function employed deal A power form errors used ensure...

This article investigates the problem of neural network (NN)-based adaptive backstepping control design for stochastic nonlinear systems with unmodeled dynamics in finite-time prescribed performance. NNs are used to study uncertain plants, and is tackled by combination changing supply function dynamical signal methods. The outstanding contribution this that based on performance (FTPF), a modified NN strategy proposed, which makes controller simpler. Eventually, using Itô's differential...

In this article, the issue of adaptive control design with full error constraints for multi-input and multi-output nonlinear systems is investigated. By combining filters an back-stepping scheme, a novel dynamic surface (DSC) scheme presented. Different from DSC traditional linear filter, proposed not only solves inherent problem computational complexity explosion, but also enhances property. addition, in order to further enhance tracking performance understructure fixed-time prescribed...

This article investigates the event-triggered predefined time output feedback control design problem for nonlinear interconnected systems with nonstrict structures. Compared existing schemes, most significant contribution of this is that system stability can be preset directly. Fuzzy logic (FLSs) and FLSs-based state observer deal unknown dynamics unmeasured states. Combining dynamic surface technology mechanism based on switching threshold strategy, an decentralized method proposed, in...

This paper studies the predefined-time adaptive control problem for a class of strict-feedback nonlinear systems with parametric uncertainties and disturbances. A new practical predefined time stable (PPTS) criterion is first presented as theoretical basis design, then command filter designed. Based on established PPTS backstepping design technique, based scheme developed. The proposed method can guarantee system to be tracking error converges small neighborhood around zero. Moreover, it...

This paper studies adaptive fuzzy output feedback tracking control problem for nonstrict-feedback switched nonlinear systems. The systems under consideration contain unknown nonlinearities, unmeasured states, and deadzones. Fuzzy logic are utilized to approximate the a state observer is designed, thus, immeasurable states estimated via it. In framework of observer-based control, by using certainty equivalence deadzone inverse, novel design method with parameters adaptation laws developed....

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown functions. The logic are introduced to learn dynamics cost functions, respectively, state estimator is developed. By applying backstepping recursive algorithm, feedforward controller established. using scheme, considered system changed into an equivalent affine system. Subsequently, scheme constructed. whole...

Due to the particularity of fractional-order derivative definition, control design is more complicated and difficult than integer-order design, it has practical significance. Therefore, in this article, a novel adaptive switching dynamic surface (DSC) strategy first presented for nonlinear systems nonstrict feedback form with unknown dead zones arbitrary switchings. In order avoid problem computational complexity continuously obtain fractional derivatives virtual control, DSC technique...

This paper discusses the adaptive fuzzy partial tracking errors constrained control problem for a class of uncertain stochastic nonlinear systems. The concerned systems contain unknown functions, unmeasured state variables, and switching signal with average dwell time. logic are first used to approximate switched observer is developed estimating states. By introducing performance function error transformation into backstepping dynamic surface design, new observer-based design approach...

In this article, the high-order nonlinear system is commonly studied in an underactuated weakly coupled mechanical system, control design difficult from tractional for systems. Thus, we study finite-time fuzzy adaptive error constraint problem stochastic nonstrict feedback Fuzzy logic systems are utilized to identify unknown dynamics, a new transfer variable used achieve prescribed performance. Based on adding power integrator technique and backstepping recursive control, novel performance...

In this article, the problem of stochastically finite time stabilization for an uncertain single-input and single-output stochastic system in presence input quantization is studied. The broad learning (BLS) first applied to identify with unknown dynamics. unmeasured states can be solved by establishing a novel BLS-based state observer. Combining theorem Ito formula, new design method proposed, which reduce difficulty designing controllers traditional methods. A quantized control presented...

This article addresses the issue of fuzzy adaptive prescribed performance control (PPC) design for nonstrict feedback multiple input output (MIMO) nonlinear systems in finite time. Unknown functions are handled via fuzzy-logic (FLSs). By combining backstepping algorithm and filters, a novel dynamic surface (DSC) method is proposed, which can not only avoid computational complexity but also improve contrast to traditional DSC methods. Furthermore, make tracking errors have time, new Lyapunov...

This article studies the nonsingular fixed-time control problem of multiple-input multiple-output (MIMO) nonlinear systems with unmeasured states for first time. A state observer is designed to solve that system cannot be measured. Due existence unknown dynamics, neural networks (NNs) are introduced approximate them. Then, through combination adaptive backstepping recursive technology and adding power integration technology, a output feedback algorithm proposed, which introduces filter avoid...

This article studies the fuzzy adaptive finite-time consensus control problem for high-order nonlinear multiagent systems with unknown dynamics. In design,fuzzy logic (FLSs) are adopted to approximate dynamics, and under frameworks of backstepping recursive design stability theory, an method is developed. To save communication resources reduce numbers controller execution times, a dynamic event-triggered mechanism relative threshold established. Subsequently, event-triggered-based scheme...

This paper addresses the challenge of adaptive fuzzy event-triggered bipartite consensus control for a class nonlinear multi-agent systems (MASs) with full-state asymmetric constraints, incorporating both cooperative and adversarial communication between agents. To ensure tracking performance in presence MASs are augmented an enhanced function. Fuzzy logic (FLSs) employed to handle unfamiliar nonlinearities effectively. reduce burden enhance transient performance, strategy is introduced,...