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In this study, the decentralized model reference adaptive control (DMRAC) problem is tackled for a class of time‐varying delay interconnect systems that comprise unknown system matrices and unknown dead‐zone inputs. Two robust adaptive control methods are proposed for state tracking based on the moderate matching time‐varying delay nonlinear assumptions and the matching between the controlled system and reference model matrices, respectively. The control gain function is explicitly expressed, and it is applied to the adaptive law gains simultaneously. Moreover, a Lyapunov–Krasovskii functional with two integral functions is developed. Besides the properties of the type‐B Nussbaum function, the circumstance where the system parameters are fully unknown is considered. As indicated by the results, all signals in the closed‐loop system are bounded while fulfilling asymptotically tracked control objectives. The simulation example of this study verifies the effectiveness and feasibility of the proposed design method. [ABSTRACT FROM AUTHOR]

This article addresses the problem of adaptive tracking control for stochastic nonlinear systems with asymmetric full state constraints. Different from the traditional log‐type or tan‐type barrier Lyapunov functions (BLFs), a new asymmetric BLF is proposed in this article. Then, a state feedback controller is constructed with backstepping method so that all signals of the closed‐system are bounded and the asymmetric state constraint is well kept all the time. Without changing the structure of the controller, the design and the analysis for constrained and unconstrained systems are unified. Finally, the effectiveness of proposed control strategy has been demonstrated by simulations of numerical example and the single‐link robot arm model. [ABSTRACT FROM AUTHOR]

In this paper, by using bound estimation method, Nussbaum function, K‐filters and higher‐order Lyapunov function, an adaptive output feedback compensation control scheme is proposed for uncertain nonlinear systems with infinite number of actuator failures and unknown control direction. A parametric model with unknown system uncertainties and infinite actuator failures is established, which is different from the existing results. This scheme ensures that closed‐loop signals are globally uniformly bounded. By properly selecting the design parameters, the tracking errors converges to a small neighborhood of the origin. Finally, two simulation examples are given to demonstrate its efficiency of the proposed design scheme. [ABSTRACT FROM AUTHOR]

In this article, we study the reachable set estimation and controller design problems for a class of discrete time‐varying‐delay singularly perturbed systems. First, by constructing a ε‐dependent Lyapunov–Krasovskii functional and using reciprocally convex inequality, delay‐dependent conditions are obtained to ensure the state of the system under zero initial conditions is contained by an ellipsoid for any singularly perturbed parameters below a given threshold. Second, by the method of designing a state‐feedback controller, sufficient conditions that the reachable set of the closed‐loop system can be included in a given ellipsoid are obtained for admissible singularly perturbed parameters. Finally, two examples are given to illustrate the effectiveness of the results. [ABSTRACT FROM AUTHOR]

The adaptive finite‐time event‐triggered quantized control for the nonlinear systems considering uncertain parameters and external disturbances is investigated in this article. First, for the parametric nonlinear systems with external disturbances, an adaptive finite‐time event‐triggered control scheme with input quantization is proposed. The designed controller can ensure the semiglobal finite‐time stability of the closed‐loop system. Then, to deal with the global finite‐time control problem for the parametric nonlinear systems, a novel adaptive quantized event‐triggered control scheme is constructed. Finally, two simulation examples are utilized to illustrate the effectiveness of the adaptive event‐triggered control schemes. [ABSTRACT FROM AUTHOR]

The issue of the reliable exponential H∞ filtering (HF) is revisited for singular Markovian jump time‐delay systems (SMJTSs) accompanied by sensor failures and interval time‐varying delays. By a new mode‐dependent Lyapunov–Krasovskii functional (LKF) containing three augmented nonintegral terms, some mean‐square exponentially admissible (MSEA) conditions satisfying an H∞ performance are derived subject to state decomposition method. On this basis, a novel reliable filter design approach is first proposed for SMJTSs by means of the idea of the state decomposition and recombining. And the filter parameters we want can be obtained. Worth noting that the results presented are not only related to interval time‐varying delay and sensor failure but also to interval delay‐change‐rate. Meanwhile, the sufficient conditions established have less conservatism and lower computational complexity in comparison with the existing results. The effectiveness and superiority of the proposed methods are verified by two numerical examples derived from some existing papers. [ABSTRACT FROM AUTHOR]

Summary: In this article, the adaptive tracking control problem is considered for a class of uncertain nonlinear systems with input delay and saturation. To compensate for the effect of the input delay and saturation, a compensation system is designed. Radial basis function neural networks are directly utilized to approximate the unknown nonlinear functions. With the aid of the backstepping method, novel adaptive neural network tracking controllers are developed, which can guarantee all the signals in the closed‐loop system are semiglobally uniformly ultimately bounded, and the system output can track the desired signal with a small tracking error. In the end, a simulation example is given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Summary: This paper addresses the problem of finite‐time stabilization for a class of low‐order stochastic upper‐triangular nonlinear systems corrupted by unknown control coefficients. Unlike the relevant schemes, the control strategy draws into a dominate gain to cope with the deteriorative effects of both uncertain nonlinearities and unknown control coefficients without using traditional adaptive compensation method. Then, a state feedback controller is constructed by the adding a power integrator method and modified homogeneous domination approach, to ensure the finite‐time stability of the closed‐loop system. Finally, the effectiveness of proposed control strategy has been demonstrated by a simulation example. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates a composite neural dynamic surface control (DSC) method for a class of pure‐feedback nonlinear systems in the case of unknown control gain signs and full‐state constraints. Neural networks are utilized to approximate the compound unknown functions, and the approximation errors of neural networks are applied in the design of updated adaptation laws. Comparing the proposed composite approximation method with the conventional ones, a faster and better approximation performance result can be obtained. Combining the composite neural networks approximation with the DSC technique, an improved composite neural adaptive control approach is designed for the considered nonlinear system. Then, together with the Lyapunov stability theory, all the variables of the closed‐loop system are semiglobal uniformly ultimately bounded. The infringements of full state constraints can be avoided in the case of unknown control gain signs as well as unknown disturbances. Finally, two simulation examples show the effectiveness and feasibility of the proposed results. [ABSTRACT FROM AUTHOR]

Summary: This paper gives a first try to the finite‐time control for nonlinear systems with unknown parametric uncertainty and external disturbances. The serious uncertainties generated by unknown parameters are compensated by skillfully using an adaptive control technique. Exact knowledge of the upper bounds of the disturbances is removed by employing a disturbance observer–based control method. Then, based on the disturbance observer–based control, backstepping technique, finite‐time adaptive control, and Lyapunov stability theory, a composite adaptive state‐feedback controller is strictly designed and analyzed, which guarantees the closed‐loop system to be practically finite‐time stable. Finally, both the practical and numerical examples are presented and compared to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Summary: Second‐order sliding mode (SOSM) control is used to keep exactly a constraint σ of the second relative degree or to avoid chattering phenomenon. Yet, the traditional SOSM controllers are designed based upon the assumption that the uncertainties or their derivatives are bounded by positive constants. In this paper, a global SOSM controller is designed for a general class of single‐input–single‐output nonlinear systems with uncertainties bounded by positive functions. Moreover, a variable‐gain robust exact differentiator is developed such that the SOSM controllers with finite‐time convergence can also be implemented even when the derivative of the constraint σ is unavailable. Simulation results are given to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the flocking problem for multiple unicycle systems in the presence of heterogenous input disturbances under directed topologies. Adaptive compensators are employed to eliminate the effect of disturbances. Based on the constructed potential functions, a class of novel distributed dynamic control algorithms are designed to implement flocking with connectivity preservation and collision avoidance with strongly connected directed graphs. It is noted that the proposed controller has released the constraints for connectivity preservation by only maintaining a minimum strongly connected directed graph in the initial topology. With the proposed methodology, the initial graph is allowed to contain those edges at boundary distances. Two illustrative examples are presented to demonstrate the effectiveness of the actuator involved in this paper. [ABSTRACT FROM AUTHOR]

This paper studies the finite-time tracking control of nonholonomic systems in chained form with parameter uncertainties, unknown output gains, and mismatched uncertainties. To achieve the finite-time tracking control of uncertain nonholonomic systems, we propose 2 types of controllers by state and output feedback, respectively. Both of the proposed 2 types of controllers can achieve the finite-time output tracking control of the nonholonomic systems even in the presence of mismatched uncertainties and/or unknown gains. The effectiveness of our proposed controllers are illustrated with simulation examples. [ABSTRACT FROM AUTHOR]

This paper investigates the finite-time control problem for a class of stochastic nonlinear systems with stochastic integral input-to-state stablility (SiISS) inverse dynamics. Motivated by finite-time stochastic input-to-state stability and the concept of SiISS using Lyapunov functions, a novel finite-time SiISS using Lyapunov functions is introduced firstly. Then, by adopting this novel finite-time SiISS small-gain arguments, using the backstepping technique and stochastic finite-time stability theory, a systematic design and analysis algorithm is proposed. Given the control laws that guarantee global stability in probability or asymptotic stability in probability, our design algorithm presents a state-feedback controller that can ensure the solution of the closed-loop system to be finite-time stable in probability. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control scheme. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY This paper is concerned with the stability of sampled-data systems with state quantization. A new piecewise differentiable Lyapunov functional is first constructed by fully utilizing information about sampling instants. This functional has two features: one is that it is of the second order in time t and of every term being dependent on time t explicitly and the other is that it is discontinuous and is only required to be definite positive at sampling instants. Then, on the basis of this piecewise differentiable Lyapunov functional, a sampling-interval-dependent exponential stability criterion is derived by applying the technique of a convex quadratic function with respect to the time t to check the negative definiteness for the derivative of the piecewise differentiable Lyapunov functional. In the case of no quantization, a new sampling-interval-dependent stability criterion is also obtained. It is shown that the new stability criterion is less conservative than some existing one in the literature. Finally, two examples are given to illustrate the effectiveness of the stability criterion. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, an adaptive backstepping tracking control scheme is proposed for a class of nonlinear state time-varying delay systems, which are subject to parametric uncertainties and external disturbances. The bounds of the time delays and their derivatives are assumed to be unknown. Tuning functions method is exploited to construct the control law and adaptive laws. Unknown time-varying delays are compensated by using appropriate Lyapunov-Krasovskii functional. It is shown that the proposed controller can guarantee the boundedness of all the closed-loop signals. The tracking performance can be adjusted by choosing suitable design parameters. At the end, a simulation example is provided to illustrate the effectiveness of the design procedure. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]