Decentralized global stabilization for stochastic high-order feedforward nonlinear systems with time-varying delays

This paper studies the problem of decentralized stabilization for a class of large-scale stochastic high-order time-delay feedforward nonlinear systems. A series of delay-independent state feedback controllers is constructed, which is based on the approach of adding one power integrator. The stochastically global asymptotic stability (GAS) of the closed-loop system under the above-mentioned controllers is proved by Lyapunov–Krasovskii theorem and homogeneous domination approach. A simulation example is given to illustrate the effectiveness of the results of this paper.     

Adaptive neural control of stochastic nonlinear systems with unmodeled dynamics and time-varying state delays

In this paper, a novel adaptive control scheme is investigated based on the backstepping design for a class of stochastic nonlinear systems with unmodeled dynamics and time-varying state delays. The radial basis function neural networks are used to approximate the unknown nonlinear functions obtained by using Ito differential formula and Young?s inequality. The unknown time-varying delays and the unmodeled dynamics are dealt with by constructing appropriate Lyapunov–Krasovskii functions and introducing available dynamic signal. It is proved that all signals in the closed-loop system are bounded in probability and the error signals are semi-globally uniformly ultimately bounded (SGUUB) in mean square or the sense of four-moment. Simulation results illustrate the effectiveness of the proposed design.     

On stabilization for systems with two additive time-varying input delays arising from networked control systems

This paper is concerned with the stability and stabilization for systems with two additive time-varying input delays arising from networked control systems. A new Lyapunov functional is constructed and a tighter upper bound of the derivative of the Lyapunov functional is derived by applying a convex polyhedron method. The resulting stability criteria are of fewer matrix variables and less conservative than some existing ones. Based on the stability criteria, a state feedback controller is designed such that the closed-loop system is asymptotically stable. Numerical examples are given to show the less conservatism of the stability criteria and the effectiveness of the designed method.     

Numerical solutions of optimal control for linear time-varying systems with delays via hybrid functions

By applying hybrid functions of general block-pulse functions and Legendre polynomials, the linear-quadratic problem of linear time-varying systems with delays are transformed into the optimization problem of multivariate functions. The approximate solutions of the optimal control and state as well as the optimal value of the objective functional are derived. The numerical examples illustrate that the algorithms are valid.     

A compensator design technique for control systems with time-varying nonlinear elements

A method is advanced for the design of linear controllers for a class of nonlinear systems. The systems considered in this paper are characterized by the presence of a dominant nonlinearity located in a specified sector. The proposed approach is digital-computer oriented, and design results are presented in parameter planes and parameter space.     

Non-fragile sampled-data stabilization analysis for linear systems with probabilistic time-varying delays

This paper deals with the problem of non-fragile sampled-data stabilization analysis for a class of linear systems with probabilistic time-varying delays via new double integral inequality approach. Based on the auxiliary function-based integral inequality (AFBII) and with the help of some mathematical approaches, a new double integral inequality (NDII) is developed. Then, to demonstrate the merits of the proposed inequality, an appropriate Lyapunov–Krasovskii functional (LKF) is constructed with some augmented delay-dependent terms. By employing integral inequalities, an enhanced stability criterion for the concerned system model is derived in terms of linear matrix inequalities (LMIs). Finally, three benchmark illustrative examples are given to validate the effectiveness and advantages of the proposed results.     

A novel controller design and evaluation for networked control systems with time-variant delays

A new delayed state-variable model for networked control systems is presented, upon which a linear quadratic regulator (LQR) is designed. A method of delays-estimation online is also given. A fuzzy logic with LQR controller is addressed for the difficulty on implementation of LQR in networked control systems (NCSs) with time-variant delays. Simulation results prove that the novel controller can make the system stable and robustly preserve the performance in terms of time-variant delays.     

An improved robust stabilization method for discrete-time fuzzy systems with time-varying delays

This note focuses on the robust stabilization of discrete-time fuzzy uncertain systems with time-varying delays under a delayed nonparallel distributed compensation scheme. The key idea is twofold: first, the linear matrix inequalities (LMI) proposed here are shown to generalize some previous similar results available in recent literature, and second, the design of control parameters is decoupled from the proposed fuzzy-basis dependent Lyapunov–Krasovskii functional (FBDLKF) by means of Finsler?s lemma. Finally, a numerical example is provided to illustrate the effectiveness of this method.     

Approximate controllability of nonlinear stochastic evolution systems with time-varying delays

In this paper, the approximate controllability of nonlinear stochastic evolution time-varying delay systems with preassigned responses is studied. The necessary conditions for controllability results of nonlinear systems are not associated with linear systems. No compactness assumptions are imposed in the main results.     

Consensus tracking control for nonlinear multiagent systems with asymmetric state constraints and input delays

In this paper, the consensus tracking problem is studied for a group of nonlinear heterogeneous multiagent systems with asymmetric state constraints and input delays. Different from the existing works, both input delays and asymmetric state constraints are assumed to be nonuniform and time-varying. By introducing a nonlinear mapping to handle the problem caused by state constraints, not only the feasibility condition is removed, but also the restriction on the constraint boundary functions is relaxed. The time-varying input delays are compensated by developing an auxiliary system. Furthermore, by utilizing the dynamic surface control method, neural network technology and the designed finite-time observer, the distributed adaptive control scheme is developed, which can achieve the synchronization between the followers’ output and the leader without the violation of full-state constraints. Finally, a numerical simulation is provided to verify the effectiveness of the proposed control protocol.     

Contraction-based model predictive control for stochastic nonlinear discrete-time systems with time-varying delays via multi-dimensional Taylor network

For stochastic nonlinear systems with time-varying delays, the existing robust control approaches are unnecessarily conservative in most practical scenarios. Within this context, a mathematically rigorous and computationally tractable tube-based model predictive control scheme is proposed in the framework of contraction theory. A contraction metric is systematically constructed via convex optimization by forming a differential LyapunovKrasovskii function on tangent space. It guarantees the perturbed actual solution trajectories to be contained within a robust positive invariant tube centered along the reference trajectories and results in an explicit exponential bound on the deviation. The application scenarios of the control contraction metric controller are extended from constant delay systems into time-varying delay systems thereby. Compared with the existing robust mechanism for time-delay systems based on min-max optimization formulation with a linear feedback controller, the proposed scheme greatly reduces the design conservativeness and yields a larger region of attraction. A sparse multi-dimensional Taylor network (MTN) is designed to parameterize the family of the geodesic. Compared to conventional NNs and MTN surrogates, sparse MTN features a more concise topology that enhances its computational efficiency conspicuously. Results of the numerical simulations verify the effectiveness of the proposed method.     

Containment control of fractional-order multi-agent systems with time-varying delays

In this paper, containment control problems of networked fractional-order multi-agent systems with time-varying delays are studied. The normalized directed graphs are employed to characterize the communication topologies. Two sampled-data based containment control protocols are proposed, which can overcome the time-varying delays and switching topologies. It is interestingly found that the decays of the closed-loop systems correspond to the Mittag-Leffler function and its approximation, which are the extensions of the exponential function and its approximation, respectively. Based on the algebraic graph theory, the properties of row-stochastic matrix, and the relation between the topologies and the matrices, some conditions for containment control are established. For the fixed topology, a necessary and sufficient condition is obtained; and for the switching topology, a sufficient condition is provided. Finally, the theoretical results are illustrated by several numerical simulations.     

Quantized control of event-triggered networked systems with time-varying delays

The paper is a study of quantized control for stochastic Markov jump systems with interval time-varying delays and bounded system noise under event-triggered mechanism. A new scheme of Lyapunov–Krasovskii functional which contains the quadratic terms and integral terms is presented. Then quadratic convex technology, the theory of stochastic switching system, and logarithmic quantizer are applied to this paper. The design of quantized controller is obtained with those methodologies. Different from previous results, our derivation applies the idea of second-order convex combination. The conservatism of stability criteria for systems is reduced by using this method. A numerical example under different conditions is given to demonstrate the effectiveness and validity of the new design techniques.     

Delay-independent stabilization of linear systems with time-varying delayed state and uncertainties

The problem of robust stabilization for a class of dynamic systems with time-varying state delay as well as parametric and input uncertainties is considered in this paper. Several delay-independent stabilizability criteria and memoryless state feedback controllers are presented to guarantee the asymptotic stability of the closed-loop uncertain time-delay systems. It is shown that if all uncertainties and delay terms are matched, then the mentioned systems can always be stabilized, or can be stabilized with a specified decaying rate.     

A robust low-complexity tracker design with preassigned performance for uncertain high-order nonlinear systems with unknown time-varying delays and high powers

A robust low-complexity design methodology is presented for global tracking of uncertain high-order nonlinear systems with unknown time-varying delays. In contrast to the existing literature, this paper assumes that nonlinear bounding functions of time-delay nonlinearities and high powers of virtual and actual control variables are unknown. Furthermore, a delay-independent tracking scheme using nonlinearly transformed error surfaces is simply designed without the knowledge of nonlinear bounding functions of model nonlinearities, the adaptive technique, and the calculation of repeated time derivatives of certain signals. Thus, the proposed tracker is implemented with low complexity. It is recursively shown that the tracking error is preserved within the predefined bounds of transient and steady-state performance in the Lyapunov sense.     

Delay-dependent exponential stability criteria for neutral systems with interval time-varying delays and nonlinear perturbations

This paper investigates the problem of global exponential stability for neutral systems with interval time varying delays and nonlinear perturbations. It is assumed that the state delay belongs to a given interval, which means that both the lower and upper bounds of the time-varying delay are available. The uncertainties under consideration are norm-bounded. Based on the Lyapunov–Krasovskii stability theory, delay-partitioning technique and lower bounds lemma, less conservative delay-dependent exponential stability criteria are derived in terms of linear matrix inequalities (LMIs) with fewer decision variables than the existing ones. Numerical examples are given to show the effectiveness of the proposed method.