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In this paper, a high-order nonlinear disturbance observer-based fractional-order sliding mode control (FOSMC) strategy is proposed for DC/DC buck converters in the presence of mismatched disturbances, ensuring the properties of both stability and dynamic performance. Traditional sliding mode control can deal with matched disturbances while achieving desired closed-loop performance, unfortunately it is particularly sensitive to mismatched disturbances. In the proposed control structure, two nonlinear disturbance observers are constructed to estimate both matched and mismatched disturbances in finite time. Then, the estimated variables are used for the fractional-order sliding mode surface design, where a super twisting sliding mode controller is designed to drive the states of the system to track their desired values. Comparing with the traditional SMC, the proposed method not only reduces the sensitivity of the system to mismatched disturbance, but also improves the transient performance of the system. Simulation and experimental results have comprehensively illustrated the feasibility and effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

In this paper, four control strategies for DC-DC buck converters are proposed, compared and analyzed: a single-loop adaptive control strategy (SA), a double-loop adaptive control strategy (DA), a single-loop disturbance observer-based control strategy (SDOB) and a double-loop disturbance observer-based control strategy (DDOB). First, the nominal system without considering the parametric uncertainties of the DC-DC buck converter is built to help develop the SA and DA. The SA is built by adaptive and backstepping control approaches, and the DA is set up by adaptive and sliding mode control approaches. Additionally, a model considering parametric uncertainties is introduced, giving the opportunity to develop the SDOB and DDOB. The SDOB is developed using a designed disturbance observer and backstepping control technique, and the DDOB is synthesized using a designed disturbance observer and sliding mode control method. Finally, the advantages and disadvantages of the four proposed control strategies are compared and analyzed through experiments. [ABSTRACT FROM AUTHOR]

This paper studies an output-based adaptive fault-tolerant control problem for nonlinear systems with nonstrict-feedback form. Neural networks are utilized to identify the unknown nonlinear characteristics in the system. An observer and a general fault model are constructed to estimate the unavailable states and describe the fault, respectively. Adaptive parameters are constructed to overcome the difficulties in the design process for nonstrict-feedback systems. Meanwhile, dynamic surface control technique is introduced to avoid the problem of “explosion of complexity”. Furthermore, based on adaptive backstepping control method, an output-based adaptive neural tracking control strategy is developed for the considered system against actuator fault, which can ensure that all the signals in the resulting closed-loop system are bounded, and the system output signal can be regulated to follow the response of the given reference signal with a small error. Finally, the simulation results are provided to validate the effectiveness of the control strategy proposed in this paper. [ABSTRACT FROM AUTHOR]

This paper is concerned with the exponential stability analysis of genetic regulatory networks (GRNs) with switching parameters and time delays. In this paper, a new integral inequality and an improved reciprocally convex combination inequality are considered. By using the average dwell time approach together with a novel Lyapunov–Krasovskii functional, we derived some conditions to ensure the switched GRNs with switching parameters and time delays are exponentially stable. Finally, we give two numerical examples to clarify that our derived results are effective. [ABSTRACT FROM AUTHOR]

• This paper introduces a type of unusual soft network materials with rotatable structural lattice nodes, which combine mechanical attributes of high stretchability and relatively high strength. • A nonlinear theoretical model is developed to predict the J-shaped stress-strain curves of proposed soft network materials. • The nonlinear responses of stress-strain curves, including the utmost strength and stretchability, can be precisely tuned by key geometric parameters. • This study provides systematic guidelines of the soft network design for achieving targeted mechanical responses required in practical applications. Soft network materials consisting of filamentary horseshoe microstructures represent a class of architected materials of practical interest in flexible, bio-integrated electronics, because they can be tailored to reproduce accurately nonlinear stress−strain responses of biological tissues. The previous studies of these bio-inspired soft network materials focused mostly on the intriguing mechanical responses (e.g., J-shaped stress-strain curves and negative Poisson's ratios) before their fracture, and paid little attention on their utmost strength and stretchability. The development of soft network materials that can offer both a high stretchability (e.g., > 100%) and a relatively high strength (e.g., > 50 MPa) remains challenging. This paper presents the design, mechanics modeling and experimental measurement of a novel type of soft network materials that introduce rotatable structural lattice nodes (either with ring or disk shapes) to offer an enhanced deformability. Based on the analyses of the periodic building-block structure, we develop a nonlinear mechanics model of unusual soft network materials made of elastic constituent materials. Validated by finite element analyses (FEA) and experiments, this theoretical model can well predict the J-shaped stress-strain curves and deformed configurations of unusual soft network materials with a variety of geometric parameters. The results based on the developed model provide insights into the underlying relationship between nonlinear mechanical properties and key geometric parameters. For unusual soft network materials made of metals, an Ashby plot in terms of the strength and the stretchability is presented, highlighting the advantages of developed network materials over the existing network materials and typical soft materials. Moreover, computational models based on representative unit cells with periodic boundary conditions allow precise predictions of the utmost strength and stretchability, which can thereby serve as a reliable design tool. Due to the combined mechanical attributes of high stretchability, relatively high strength, and negative Poisson's ratio, the proposed unusual soft network materials can be used in various device systems of bio-integrated electronics. [ABSTRACT FROM AUTHOR]

This paper focuses on the dynamic output feedback (DOF) controller design problem for discrete-time switched genetic regulatory networks (GRNs) with time-varying delays. Firstly, based on the average dwell time method and piecewise Lyapunov–Krasovskii functional, the exponential stability criteria are derived by utilizing a new summation inequality, an extended reciprocally convex matrix inequality and the extension of the property of quadratic convex function. Then, sufficient conditions for a desired DOF controller are obtained such that the resulting closed-loop system is exponentially stable. Moreover, the explicit expressions of all desired controllers are given. Finally, numerical example is provided to verify the effectiveness of the proposed design techniques. [ABSTRACT FROM AUTHOR]

Abstract The paper studies the problem of event-triggered H 2 / H ∞ model predictive control (MPC) for nonlinear networked control systems (NCSs) with bandwidth limitation and packet loss. The nonlinear system is described by the interval type-2 Takagi-Sugeno (IT-2 T-S) fuzzy model. To reduce the communication bandwidth utilization, an event-triggered communication scheme is presented to determine the transmission of the latest sampled state. The unreliable networks with packet loss are described by stochastic variables which satisfy Bernoulli binomial distribution. This paper aims at designing a fuzzy predictive controller to make the resulting closed-loop system stochastically stable with H 2 / H ∞ performance satisfied. An online optimization MPC problem is formulated to optimize a H 2 performance index while the H ∞ performance index is prescribed. We provide a numerical example to illustrate the validity of the presented technique. [ABSTRACT FROM AUTHOR]

The attitude synchronization problem of multiple spacecraft is investigated in this paper. A simple cooperative control law, which can render spacecraft formation synchronized to a time-varying reference trajectory globally in the presence of model uncertainties, external disturbances and input saturation, is proposed. The globally asymptotic stability of the controller in the presence of model uncertainties and external disturbances is proven rigorously through a three-step proof technique. The controller can be used in orbit without modification due to its low computational complexity. Then, the proposed controller is extended to solve the consensus problem for multiple inertial agents with double-integrator dynamics. Finally, Numerical simulations are included to demonstrate the effectiveness of the developed controller. [ABSTRACT FROM AUTHOR]

• Both the sliding variables of linear and integral-type are designed depending on the singular matrix of the singular MJS, based on which the uniformly bounded stochastic stability of resulting sliding motions are analyzed. • Interval type-2 FNN-based dynamic SMC laws are proposed depending on the system mode, which can achieve practical sliding modes of the sliding variables and directly estimate the unknown function. • The dynamic SMC variables are designed to simultaneously act as the inputs of the presented interval type-2 FNN, of which the approximation error bound can also be estimated by our designed adaptive laws. • Moreover, some sufficient conditions are developed for the determination of the parameters of the sliding variables and control laws. This paper is concerned with the problems of dynamic practical-sliding-mode control (SMC) and estimation of unknown functions for singular Markovian jump systems (MJSs) with system perturbations, by using an ellipsoidal-type interval type-2 fuzzy neural networks (FNNs). For the interval type-2 FNN, both the system states and control inputs are utilized as its inputs. Then, by using respectively the linear and the integral sliding variables depending on both the system state and control input, the design of novel interval type-2 FNN-integrated intelligent dynamic practical SMCs to achieve practical sliding modes in finite time is presented. The resulting practical sliding motions are proved to be semi-global practical finite-time stochastic stable based on the Lyapunov function. Furthermore, by exploring some adaptive laws based on the interval type-2 FNN, the unknown function can be approximated, and even the bound of the approximation errors of the interval type-2 FNN can be estimated, under the system perturbation. Finally, an application example is introduced to illustrate the validity of the presented intelligent dynamic practical SMC techniques. [ABSTRACT FROM AUTHOR]

For the typical uncertain nonlinear systems subjected to controller gain variation and disturbances, an integrated adaptive robust controller, called integral sliding-mode finite-time controller with an integrated extended state observer (ISFC-IESO), is proposed. The designed controller mainly consists of an integrated ESO (IESO) unit and an integral sliding-mode control (ISMC) unit. The IESO unit is composed of improved linear and nonlinear ESOs which are designed to automatically switch each other, with the aim of enhancing disturbance estimation capability. Moreover, the ISMC unit produces an integral sliding-mode control law (SMCL) based on the newly designed integral sliding-mode surface function (SMSF) and sliding-mode reaching law (SMRL). The integral SMSF is developed based on the n -th estimated state and a designed convergence function of tracking error to suppress the influence of the disturbance estimation error. On this basis, SMRL is further presented by combining integral SMSF with a specially designed variable boundary layer thickness saturation function, for the purpose of eliminating chattering and enhancing robustness. Finally, fourteen control methods are compared to illustrate the effectiveness and superiority of the proposed ISFC-IESO. [ABSTRACT FROM AUTHOR]

Abstract: The problem of delay-dependent robust stability for neutral control systems with time-varying delay and time-varying structured uncertainties is investigated. An improved linear matrix inequality-based delay-dependent stability test is introduced to ensure a large upper bound for time-delay. A new class of Lyapunov–Krasovskii functionals combined with the descriptor model transformation and the decomposition technique of coefficient matrix is constructed to derive some novel delay-dependent stability criteria. Finally, numerical examples are given to demonstrate the derived condition are much less conservative than those given in the literature. [Copyright &y& Elsevier]