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This article considers the event-triggered control for the active seat suspension system with time-varying full-state constraints. Consider that communication resources may be limited, this article proposes a dynamic relative threshold strategy to reduce the communication burden of actuator and controller. Compared with the fixed value as a trigger condition, the dynamically changing thresholds as trigger conditions are more general and universal. The time-varying full-state constraint problem is solved by using the barrier Lyapunov function. In addition, the radial basis function neural networks are employed to approximate the unknown terms. Then, all signals in the resulted system are bounded, and the Zeno behavior can be avoided successfully. Moreover, all the system states satisfy their corresponding constraint condition. Finally, the feasibility and rationality of this method are proved by the simulation analysis of a real example of a seat suspension system.

Purpose The purpose of this study is to provide the full-state mathematical model and devise a nonlinear controller for a balloon-supported unmanned aerial vehicle (BUAV). Design/methodology/approach Newtonian mechanics is used to establish the nonlinear mathematical model of the proposed vehicle assembly which incorporates the dynamics of both balloon and quadrotor UAV. A controllable form of the nine degrees of freedom model is derived. Backstepping control is designed for the proposed model and simulations are performed to assess the tracking performance of the proposed control. Findings The results show that the proposed methodology works well for smooth trajectories in presence of wind gusts. Moreover, the final mathematical model is affine and various nonlinear control techniques can be used in the future for improved system performance. Originality/value Multi-rotor unmanned aerial vehicles (MUAVs) are equipped with controllers but are constrained by smaller flight endurance and payload carrying capability. On the contrary, lighter than air (LTA) aerial vehicles have longer flight times but have poor control performance for outdoor operations. One of the solutions to achieve better flight endurance and payload carrying capability is to augment the LTA balloon to MUAV. The novelty of this research lies in full-order mathematical modeling along with transformation to controllable form for the BUAV assembly.

In this article, the problem of decentralized full-state constrained adaptive tracking control is investigated for interconnected time delay systems with input saturation. The extreme learning machine is applied to approximate the unknown nonlinear function in the design process. By selecting the appropriate Lyapunov–Krasovskii function, the time delay interconnection term could be compensated. A unified barrier function is introduced to ensure that the constraints imposed on all states are not violated. The Nussbaum function is introduced to deal with the problem of input saturation. By applying adaptive backstepping procedures, a novel decentralized full-state constrained adaptive tracking control strategy is proposed for the considered interconnected time delay systems. In terms of Lyapunov stability theory, it is proved that all the signals of the closed-loop systems are semi-global ultimately uniformly bounded and all state variables could be constrained within the time varying asymmetric boundaries. Finally, the effectiveness of the proposed scheme is illustrated by a simulation example of a two-stage chemical reactor.

The paper investigates the global adaptive output regulation problem (ORP) for nonlinear systems with full-state constraints (FSCs). First, in order to avoid the disadvantages of barrier Lyapunov f...

This article studies a tracking control problem for a class of stochastic nonlinear systems with time-varying full-state constraints and asymmetric input saturation. Firstly, the Gauss Error Functi...

This article addresses the issue of adaptive intelligent asymptotic tracking control for a class of stochastic nonlinear systems with unknown control gains and full state constraints. Unli...

In this paper, we study the output regulation problem (ORP) of non-linear systems with full-state constraints (FSC). First, in order to deal with the ORP of non-linear systems with FSC, a radical constraint function is proposed to avoid the drawbacks of the barrier Lyapunov functions (BLF) and the logarithmic constraint functions. Then, a control algorithm is proposed based on neural network control method without using the backstepping method, so that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and the tracking error converge to a small neighbourhood of the origin, and all states of the system can be constrained. Finally, a simulation example illustrates its effectiveness.

Summary In this article, the issue of adaptive finite‐time dynamic surface control (DSC) is discussed for a class of parameterized nonlinear systems with full state constraints. Using the property ...

Summary In this article, the fuzzy adaptive finite‐time consensus tracking control problem for nonstrict feedback nonlinear multiagent systems with full‐state constraints is studied. The finite‐tim...

Summary This article studies the adaptive fuzzy finite‐time quantized control problem of stochastic nonlinear nonstrict‐feedback systems with full state constraints. During the control design proce...

This paper investigates the issue of finite-time tracking control for multiple-input–multiple-output nonlinear systems subject to uncertainties and full state constraints. To deal with full state constraints directly, integral barrier Lyapunov functionals (iBLF) are introduced. By using finite-time stability theory, an iBLF-based adaptive finite-time neural control scheme is presented. To solve the problem of “explosion of complexity” in the design of traditional backstepping control, a new finite-time convergent differentiator is presented. Through stability analysis, all closed-loop signals are proved to be semi-globally uniformly ultimately bounded, the finite time convergence can be guaranteed, and the state constraints are never violated. Finally, the attitude tracking simulations for an autonomous airship are conducted to verify the effectiveness of the proposed scheme.

This paper investigates the problem of adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics. To stabilize such a system, a dynamic signal is introduced to dominate unmodeled dynamics and an assistant signal is constructed to compensate for the effect of the dead zone. Dynamic surface control is used to solve the “complexity explosion” problem in traditional backstepping design. Two cases of symmetric and asymmetric Barrier Lyapunov functions are discussed respectively in this paper. The proposed Barrier Lyapunov function based on backstepping method can ensure that the output tracking error converges in the small neighborhood of the origin. This control scheme can ensure that semi-globally uniformly ultimately boundedness of all signals in the closed-loop system. Two simulation cases are proposed to verify the effectiveness of the theoretical method.

In this paper, a trajectory tracking control strategy is proposed for multi-legged underwater robot in the presence of input saturation and full-state constraints. An anti-windup compensator is int...

Dynamic identifier is developed for a nonlinear sine-Gordon model. It is shown that the spatially-varying magnitude of the sine-wise external force comes identifiable provided that the model is persistently excited by a nonzero input. The present investigation focuses on the case where the full state information is available for the measurement. Capabilities of the theoretical results obtained are numerically illustrated in the case study of a spatially-invariant plant parameter.

A Luenberger type dynamical observer is proposed for estimation of the full state of a nonautonomous linear parabolic equation, from a finite-dimensional output. The output is given by average-like...

This paper addresses the adaptive finite-time tracking problem for nonlinear sandwich systems with dead-zone nonlinearity and full state constraints. The existence of the non-smooth dead-zone nonli...

This article considers the problem of adaptive neural network control via command filtering for incommensurate fractional-order chaotic permanent magnet synchronous motors with full-state constraints and parameter uncertainties. First, a neural network state observer based on a K-filter is established to reconstruct unmeasured feedback information. Then, the command filtered technology is used to overcome the inherent “explosion of complexity” problem under fractional-order framework. Furthermore, to eliminate the errors generated by filters, an error compensation system is used. Meanwhile, the nonlinear unknown functions are approximated by using neural networks. In addition, the barrier Lyapunov functions are designed to avoid the violation of the state constraints. Finally, the availability of the proposed control algorithm is revealed by numerical simulations.

In this paper, the fuzzy adaptive tracking control problem is studied for a class of nonlinear strict feedback systems with time-varying full state constraints. For the full state constraints probl...

Summary In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time‐delay systems with time‐varying full state constraints and input saturation. To overcome th...

In this study, we consider the problem of designing functional interval observers for a class of singular fractional-order systems. The goal of this work is to design not a full state interval observer for singular fractional-order systems, but to design an observer for state functions of this kind of systems. Conditions for the existence of such functional interval observers are given and an effective algorithm for computing unknown observer matrices is provided in this study. Two numerical examples and simulation results are provided to illustrate the effectiveness of the proposed design method.