Stabilization of dynamic-algebraic Boolean control networks via state feedback control

In this paper, we study the state feedback stabilization of dynamic-algebraic Boolean control networks (DABCNs). Using a novel normalization approach, we present necessary and sufficient conditions for the feedback stabilization of DABCNs, and a construction method for the corresponding feedback controllers is proposed. Reduced order feedback stabilization is also studied in this paper. Two examples are given to illustrate the obtained results.     

State feedback corrective control with a self-repair scheme against transient faults

This paper presents corrective control of input/state asynchronous sequential machines (ASMs) against transient faults occurring in both ASM and corrective controller. Since not only the ASM but also the controller undergoes unauthorized state transitions as a result of the fault, the ASM is vulnerable to direct damage by transient faults as well as indirect one propagated from the controller under the fault. We address the existence condition and design procedure for a state feedback corrective controller which achieves self-repair against any transient fault, while diagnosing and overcoming those faults infiltrating into the considered ASM. Hardware experiments on field-programmable gate array (FPGA) are provided to validate the applicability of the proposed methodology.     

Robust control design for delayed periodic piecewise time-varying systems with actuator faults

This paper is mainly focused on the stabilization problem of uncertain delayed periodic piecewise time-varying systems inclusive of disturbances and faults in actuators. More specifically, the considered system is encompassed of periodic dynamics, which exhibits the nature of switched systems with fixed switching sequence and dwell time. The control protocol is configured in the form of both the present and past state information of the addressed system with passive performance. Moreover, the proposed control approach discloses the stabilization issue mainly by resolving the effect of faults in actuator components. Precisely, the desired periodic gain matrices of the developed controller are calculated by way of solving some matrix inequalities which are derived by making use of Lyapunov stability theory and matrix polynomial approach. As a result, the asymptotic stability of the considered system is ensured in conjunction with satisfied disturbance attenuation index. Conclusively, the simulation results of two numerical examples including mass-spring damping system are presented for validating the theoretical result.     

Bifurcation and control of a planktonic ecological system with double delays by delayed feedback control

In this paper, a delayed feedback controller with the delay-dependent coefficient is introduced into a multiple delay phytoplankton-zooplankton system. For uncontrolled system, choosing delays as the bifurcation parameters, we prove that Hopf bifurcation can occur when the delays change and cross some values. Then, the delays are still chosen as the bifurcation parameters to research the dynamic behaviors of the controlled system. Under this control mechanism, the onset of Hopf bifurcation can be delayed by selecting the appropriate control parameters and the stability domain can be extended as feedback gain (the decay rate) decreases (increases), and the influence of the decay rate cannot be ignored. Furthermore, using the crossing curve methods, the stable changes of equilibrium in two delay plane can be obtained. Some numerical simulations are given to verify the correctness and validity of the delayed feedback controller in the bifurcation control.     

Stabilizing unstable periodic orbits in large stability domains with dynamic time-delayed feedback control

Dynamic time-delayed feedback control (DDFC) is applied to stabilize the unstable periodic orbits (UPOs) of chaotic systems in large stability domains. The stability domain is defined as certain areas of the parameter space of the feedback strength, in which the UPOs are stabilized. The control effect of the DDFC with a second-order controller system is investigated by considering two control objectives: to broaden the stability domain of the controlled UPOs and to minimize the modulus of the largest Floquet multiplier, which leads to a multi-objective optimization problem (MOP). The MOP is solved with the genetic algorithm. Case studies indicate that the control effect of the DDFC is significantly better than that of original time-delayed feedback control. The DDFC can stabilize the UPOs in a large stability domain and with a small modulus of the largest Floquet multiplier when the adjustable parameters of the controller system are properly designed.     

Stabilization for multi-group coupled models with dispersal by feedback control based on discrete-time observations in diffusion part

In this paper, we study the almost surely stabilization for a class of unstable multi-group coupled models with dispersal (MGMs, in short) by feedback control design based on discrete-time observations in diffusion part. Specifically, we show that the corresponding stochastically controlled system is almost surely exponentially stable when the stochastic MGM is almost surely exponentially stable within a duration of time. Finally, an example is given to illustrate the obtained theoretical results.     

Stabilization of differently structured hybrid neutral stochastic systems by delay feedback control under highly nonlinear condition

This paper mainly studies the stabilization of differently structured highly nonlinear hybrid neutral stochastic systems by delay feedback control. Based on the existing works, our new neutral type stochastic system has completely different highly nonlinear structures in switching subspaces, which is more general and applicable. When such a system is given unstable, we focus on studying the asymptotic and exponential stability criteria by designing a feedback control with a time delay for the underlying system. A simulating example is shown to illustrate the feasibility of these results.     

Adaptive leaderless consensus control of a class of strict feedback nonlinear systems with guaranteed transient performance under actuator faults

The problem of adaptive leaderless consensus control of a class of uncertain strict feedback nonlinear systems with guaranteed transient performance is investigated in this paper. The system model is a class of strict feedback nonlinear systems with parametric uncertainty, actuator fault and external disturbance. How to guarantee the transient performance of consensus error is involved. To solve this problem, the consensus is transmitted into stabilization of a new variable. Ultimately the consensus errors will asymptotically converge to zero and faster than a given exponentially converging variable. Finally, simulation results show the effectiveness of proposed control scheme.     

Stabilization of Boolean control networks with stochastic impulses

This paper studies the stabilization problem of Boolean control networks with stochastic impulses, where stochastic impulses model is described as a series of possible regulatory models with corresponding probabilities. The stochastic impulses model makes the research more realistic. The global stabilization problem is trying to drive all states to reach the predefined target with probability 1. A necessary and sufficient condition is presented to judge whether a given system is globally stabilizable. Meanwhile, an algorithm is proposed to stabilize the given system by designing a state feedback controller and different impulses strategies. As an extension, these results are applied to analyze the global stabilization to a fixed state of probability Boolean control networks with stochastic impulses. Finally, two examples are given to demonstrate the effectiveness of the obtained results.     

Stabilization of networked periodic piecewise linear systems under asynchronous switching with packet dropouts

In this paper, the networked stabilization of discrete-time periodic piecewise linear systems under transmission package dropouts is investigated. The transmission package dropouts result in the loss of control input and the asynchronous switching between the subsystems and the associated controllers. Before studying the networked control, the sufficient conditions of exponential stability and stabilization of discrete-time periodic piecewise linear systems are proposed via the constructed dwell-time dependent Lyapunov function with time-varying Lyapunov matrix at first. Then to tackle the bounded time-varying packet dropouts issue of switching signal in the networked control, a continuous unified time-varying Lyapunov function is employed for both the synchronous and asynchronous subintervals of subsystems, the corresponding stabilization conditions are developed. The state-feedback stabilizing controller can be directly designed by solving linear matrix inequalities (LMIs) instead of iterative optimization used in continuous-time periodic piecewise linear systems. The effectiveness of the obtained theoretical results is illustrated by numerical examples.     

Stabilization effect of diffusion in delayed neural networks systems with Dirichlet boundary conditions

In this paper, reaction–diffusion neural networks with unbounded time-varying delays and Dirichlet boundary conditions is studied. A new concept of global μ-stability in the sense of L² norm is introduced, and sufficient conditions are given to guarantee global μ-stability of the equilibrium point. The results obtained not only improve those in the earlier findings, but also show diffusion terms contribute to stabilization of neural networks systems.     

On asymmetric periodic solutions in relay feedback systems

Asymmetric self-excited periodic motions or periodic solutions which are produced by relay feedback systems that have symmetric characteristics are studied in the paper. Two different mechanisms of producing an asymmetric oscillation by a system with symmetric properties are noted and analyzed by the locus of a perturbed relay system (LPRS) method. Bifurcation between the ability to excite symmetric and asymmetric oscillation with variation of system parameters is analyzed. An algorithm of finding asymmetric solutions is proposed.     

Stabilization of periodic orbits of discrete-time dynamical systems using the Prediction-Based Control: New control law and practical aspects

This paper tackles in the stabilization of periodic orbits of nonlinear discrete-time dynamical systems with chaotic sets. The problem is approximated locally to the stabilization of linear time-periodic systems and the theory of modern control is applied to the Prediction-Based Control, resulting in a new control law. This control law sets all the Floquet multipliers of the stabilized orbit to zero, resulting in fast convergence of trajectories in its vicinity. Another important characteristic of the control law is that no previous knowledge about the periodic orbit is required for stabilization. Using numerical simulations, this control law was analysed and compared to an optimal Delayed Feedback Control evidencing its advantages in theoretical and practical aspects.     

Stabilization for time-delay nonlinear systems with unknown time-varying control coefficients

A control scheme based on dynamic gains is proposed for the time-varying nonlinear time-delay systems with unknown control coefficients. A class of Nussbaum functions are introduced to deal with the problem of unknown control directions. Dynamic gains technique and Lyapunov–Krasovskii functional are developed to handle the time delays in nonlinear system. It is shown that the system state is regulated to origin asymptotically, and the boundedness of all closed-loop signals is guaranteed. Simulation results are provided to demonstrate the effectiveness of the proposed methodology.     

Event-triggered delayed impulsive control for nonlinear systems with applications

In this paper, we investigate the Lyapunov stability for general nonlinear systems by means of the event-triggered impulsive control (ETIC), in which the delayed impulses are greatly taken into account. On the basis of impulsive control theory, a set of Lyapunov-based sufficient conditions for uniform stability and asymptotic stability of the addressed system are obtained in the framework of event triggering, under which Zeno behavior is excluded. It is shown that our results depend on the event-triggering mechanism (ETM) and the time delays. Then the mentioned results are applied to synchronization of chaotic systems and moreover, a kind of impulsive controllers is designed in form of linear matrix inequality (LMI), where the delayed impulsive control can be activated only when events happen. In the end, to illustrate the validity of the mentioned theoretical results, we present a numerical example.     

Output feedback control of an uncertain input-delayed nonlinear system with bounded control commands

This study focused on controlling a class of nonlinear systems with actuation time delays. We proposed a novel output-feedback controller in which the magnitude of the input commands is saturated and can be adjusted by varying control parameters. In this design, a predictor term is used to compensate for delays in the input, and auxiliary systems are exploited to provide a priori bounded control commands and account for the lack of full-state information. The stability analysis results revealed that uniformly ultimately bounded tracking is guaranteed despite modeling uncertainties and additive time-varying disturbances in the system dynamics. The performance of the controller was evaluated through simulation.     

Adaptive output feedback neural network control of uncertain non-affine systems with unknown control direction

This paper deals with the problem of adaptive output feedback neural network controller design for a SISO non-affine nonlinear system. Since in practice all system states are not available in output measurement, an observer is designed to estimate these states. In comparison with the existing approaches, the current method does not require any information about the sign of control gain. In order to handle the unknown sign of the control direction, the Nussbaum-type function is utilized. In order to approximate the unknown nonlinear function, neural network is firstly exploited, and then to compensate the approximation error and external disturbance a robustifying term is employed. The proposed controller is designed based on strict-positive-real (SPR) Lyapunov stability theory to ensure the asymptotic stability of the closed-loop system. Finally, two simulation studies are presented to demonstrate the effectiveness of the developed scheme.     

Design of observer-based feedback control for time-delay systems with application to automotive powertrain control

A new approach for observer-based feedback control of time-delay systems is developed. Time-delays in systems lead to characteristic equations of infinite dimension, making the systems difficult to control with classical control methods. In this paper, a recently developed approach, based on the Lambert W function, is used to address this difficulty by designing an observer-based state feedback controller via assignment of eigenvalues. The designed observer provides estimation of the state, which converges asymptotically to the actual state, and is then used for state feedback control. The feedback controller and the observer take simple linear forms and, thus, are easy to implement when compared to nonlinear methods. This new approach is applied, for illustration, to the control of a diesel engine to achieve improvement in fuel efficiency and reduction in emissions. The simulation results show excellent closed-loop performance.