Synchronization of time-delay systems with impulsive delay via an average impulsive estimation approach.

We investigated synchronization of dynamic systems with mixed delays and delayed impulses. Using impulsive control method and the average impulsive interval approach, several Lyapunov sufficient conditions were given for ensuring synchronization in terms of impulsive perturbation and impulsive control, respectively. The derived conditions indicated that delays in continuous dynamical systems were flexible under impulsive perturbation and were not strictly dependent on the size of impulsive delays, and they may have a potential impact on synchronization of the considered system. In addition, applying the proposed concepts of average positive impulsive estimation and average impulsive estimation, we integrated the information in impulsive delay into the rate coefficient to eliminate the limitation of having the same threshold at each impulse point, while the impulsive delay maintained the synchronization effect. This was an improvement on the previous results obtained. Finally, we provided two numerical examples to illustrate the validity of our results.

Robust ultimately boundedness control of uncertain delayed systems under time-varying reference and external disturbance.

In the set-point following, the asymptotic property of the stability would disappear in the presence of time-varying references and disturbances. Hence, the boundedness of state variables is an essential issue in the regulation. To this aim, in light of time-varying references and disturbed signals, a robust integral policy is systematically developed to achieve the control aim in the uncertain equations with delay. Utilizing linear matrix inequality, a guideline is suggested for guaranteeing the boundedness of the solutions in uncertain systems with delays. Then, the gains of the control law are computed from a minimization. Although the boundedness is ultimately obtained in the perturbed case, the asymptotic stability would also be deduced for the nominal systems. The findings are numerically evaluated in some simulations. The favorability of the proposed integral method is shown in comparison to the traditional control strategies.

Robust Stabilization of Linear Time-Delay Systems under Denial-of-Service Attacks.

This research examines new methods for stabilizing linear time-delay systems that are subject to denial-of-service (DoS) attacks. The study takes into account the different effects that a DoS attack can have on the system, specifically delay-independent and -dependent behaviour. The traditional proportional-integral-derivative (PID) acts on the error signal, which is the difference between the reference input and the measured output. The approach in this paper uses what we call the PID state feedback strategy, where the controller acts on the state signal. Our proposed strategy uses the Lyapunov-Krasovskii functional (LKF) to develop new linear matrix inequalities (LMIs). The study considers two scenarios where the time delay is either a continuous bounded function or a differentiable and time-varying function that falls within certain bounds. In both cases, new LMIs are derived to find the PID-like state feedback gains that will ensure robust stabilization. The findings are illustrated with numerical examples.

Delay effects on the stability of large ecosystems.

The common intuition among the ecologists of the midtwentieth century was that large ecosystems should be more stable than those with a smaller number of species. This view was challenged by Robert May, who found a stability bound for randomly assembled ecosystems; they become unstable for a sufficiently large number of species. In the present work, we show that May's bound greatly changes when the past population densities of a species affect its own current density. This is a common feature in real systems, where the effects of species' interactions may appear after a time lag rather than instantaneously. The local stability of these models with self-interaction is described by bounds, which we characterize in the parameter space. We find a critical delay curve that separates the region of stability from that of instability, and correspondingly, we identify a critical frequency curve that provides the characteristic frequencies of a system at the instability threshold. Finally, we calculate analytically the distributions of eigenvalues that generalize Wigner's as well as Girko's laws. Interestingly, we find that, for sufficiently large delays, the eigenvalues of a randomly coupled system are complex even when the interactions are symmetric.

DSC-based RBF neural network control for nonlinear time-delay systems with time-varying full state constraints.

The presented control scheme in this paper aims at stabilizing uncertain time-delayed systems requiring all states to change within the preset time-varying constraints. The controller design framework is based on the backstepping method, drastically simplified by the dynamic surface control technique. Meanwhile, the radius basis function neural networks are utilized to deal with the unknown items. To prevent all state variables from violating time-varying predefined regions, we employ the time-varying barrier Lyapunov functions during the backstepping procedure. Moreover, appropriate Lyapunov-Krasovskii functionals are used to cancel the influence of the time-delay terms on the system's stability. Under the presented control laws and Lyapunov analysis, it is proven that constraints on all state variables are not breached, good tracking performance of desired output is achieved, and all signals in the closed-loop systems are bounded. The effectiveness of our control scheme is confirmed by a simulation example.

An alternative design approach for Fractional Order Internal Model Controllers for time delay systems.

INTRODUCTION: Fractional Order Internal Model Control (FO-IMC) extends the capabilities of the classical IMC approach into the generalized domain of fractional calculus. When dealing with processes that exhibit time delays, implementation of such controllers in a classical feedback loop requires the approximation of the fractional order terms, as well as of the corresponding time delays. OBJECTIVES: The present study proposes an alternative design procedure of FO-IMC controllers based on a novel approximation method of the process time delay, proving the efficiency of the proposed method and its suitability for time delay systems. METHODS: The generalized IMC control laws are obtained analytically, based on a novel approximation of time delay, the Non-Rational Transfer Function approach. RESULTS: Several numerical examples are chosen to illustrate the efficiency of the proposed approach. In addition, a vertical take-off and landing unit exhibiting second order plus time delay dynamics is chosen to experimentally validate the proposed control strategy. The obtained results are used to compare the proposed tuning strategy with a popular FO-IMC tuning approach, based on the Taylor series approximation of the time delay. CONCLUSION: All the chosen examples, both numerical and experimental ones, validate the proposed method. The overall closed loop results obtained with the proposed approach demonstrate an improved performance compared to the existing method. Ultimately, the purpose of the paper to provide an alternative design strategy that extends the existing FO-IMC control field is reached.

Effect of asymmetric deformation dynamics in amoeboid organism on its search ability.

We investigate the effect of asymmetric deformation dynamics in an amoeboid organism on its search ability using a model amoeba. The model represents the behaviours of the amoeboid organism and its search ability is evaluated by searching for the solution to a Boolean satisfiability problem (SAT). We found that the efficiency of the search is significantly improved by implementing asymmetric delays in response to the feedback signals that increase and decrease the variable under appropriate errors. The results indicate that the model could search around the variable vector space by means of the appropriate combination of the inherent local search in the model and the error-induced global search. The results also show that the asymmetric response delays bias the variable to the values that can satisfy the SAT. We also demonstrate that an analog electronic system implementing the amoeba model with asymmetric dynamics possesses the search characteristics of the model.

Delay-induced resonance suppresses damping-induced unpredictability.

Combined effects of the damping and forcing in the underdamped time-delayed Duffing oscillator are considered in this paper. We analyse the generation of a certain damping-induced unpredictability due to the gradual suppression of interwell oscillations. We find the minimal amount of the forcing amplitude and the right forcing frequency to revert the effect of the dissipation, so that the interwell oscillations can be restored, for different time delay values. This is achieved by using the delay-induced resonance, in which the time delay replaces one of the two periodic forcings present in the vibrational resonance. A discussion in terms of the time delay of the critical values of the forcing for which the delay-induced resonance can tame the dissipation effect is finally carried out. This article is part of the theme issue 'Vibrational and stochastic resonance in driven nonlinear systems (part 1)'.

H∞ controller and observer synthesis with delay and nonlinear perturbation of double diabetes systems.

Patient having type 1 diabetes mellitus (having insulin resistance experience) cannot be treated solely by treatment procedure of type 1 patient nor does treatment employed for type 2 diabetes work for such patient. This type of diabetes patient needs a specific insulin injection procedure. For continuous insulin injection, the patient has to be classified as a different group from type 1 and type 2 patient. The patients experiencing both type 1 and 2 are called double diabetes mellitus (DDM) patient. Dynamic behavior of the patient was presented in delay differential equation (DDE). Based on the developed DDE of DDM model, controllers and observers fulfilling H∞ norm bound are designed for this specific group of diabetes mellitus patient. Also, a nominal controller and a nominal observer are synthesized to check the proposed controller's ability for disturbance rejection, which is the glucose intake. The performance of the designed controller and observer is evaluated for a population of simulated patients. It shows that controller and observer are able to regulate and estimate, respectively, glycaemic for population of double diabetes patients.

Predictive control of unstable time delay series cascade processes with measurement noise.

In this paper, generalized predictive control strategy is applied for unstable time delay series cascade processes. The control structure consists of a secondary loop with a secondary controller designed based on simple internal model control (IMC) method and the primary loop consists of a set-point achievement controller and is designed using synthesis method. Further, a generalized predictor consisting of two filters that deals with time delay, disturbance rejection and noise rejection capabilities is also designed in the primary loop. The filters are designed to ensure internal stability as well. For the predictor, only one tuning parameter is involved, which can be tuned in such a way that a trade-off is attained between disturbances attenuation and performance under uncertainties. In this work, various examples of cascade processes with unstable dynamics and time delay are considered for simulation. Results obtained from simulation reveals that with the suggested predictive control scheme, enhanced closed loop control performances are obtained for both nominal and perturbed conditions both in the presence and absence of measurement noise. The comparison is also verified quantitatively with the literature methods using integral absolute error (IAE) and total variation (TV) measures.

Fast consensus in a large-scale multi-agent system with directed graphs using time-delayed measurements.

This article is on fast-consensus reaching in a class of multi-agent systems (MAS). We present an analytical approach to tune controllers for the agents based on the premise that delayed measurements in the controller can be preferable to standard controllers relying only on current measurements. Controller tuning in this setting is however challenging due to the presence of delays. To tackle this problem, we propose an analytic geometry approach. The key contribution is that the tuning can be implemented for complex eigenvalues of the arising graph Laplacian of the network, complementing the current state of the art, which is limited to real eigenvalues. Results, therefore, extend our knowledge beyond symmetric graphs and enable the study of the MAS under directed graphs. This article is part of the theme issue 'Nonlinear dynamics of delay systems'.

Finite frequency range iterative learning fault-tolerant control for discrete time-delay uncertain systems with actuator faults.

The subject area considered is discrete linear time delay systems operating repetitively on a finite time interval with actuator faults, where the system resets at the end of each operation. Regulation of the dynamics is by iterative learning control and performance goals imposed over finite frequency intervals for the case of uncertainty in the dynamic model. To derive the results, the generalized Kalman-Yakubovich-Popov lemma is used. A simulation based case study is also given to demonstrate the applicability of the new results.

Tuning of a dead-time compensator focusing on industrial processes.

This paper proposes tuning rules for the Simplified Dead-Time Compensator (SDTC), which is intended to deal with stable, unstable and integrative dead-time processes. The main contribution is the proposal of new guidelines for the tuning of the robustness filter. The new set of rules allow for the use of lower order filters which are able to simultaneously account for closed-loop robustness and noise attenuation. Through illustrative examples, it is shown that the proposed approach provides enhanced disturbance rejection and noise attenuation in the control of industrial processes when compared with other recently published works. Furthermore, the internal temperature of an in-house thermal chamber is controlled to evaluate the applicability of the strategy on real processes.

Finite-time decentralized adaptive neural constrained control for interconnected nonlinear time-delay systems with dynamics couplings among subsystems.

The problem of finite-time decentralized neural adaptive constrained control is studied for large-scale nonlinear time-delay systems in the non-affine form. The main features of the considered system are that 1) unknown unmatched time-delay interactions are considered, 2) the couplings among the nested subsystems are involved in uncertain nonlinear systems, 3) based on finite-time stability approach, asymmetric saturation actuators and output constraints are studied in large-scale systems. First, the smooth asymmetric saturation nonlinearity and barrier Lyapunov functions are used to achieve the input and output constraints. Second, the appropriately designed Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. Note that, due to unknown time-delay interactions and the couplings among subsystems, the controller design is more meaningful and challenging. At last, based on finite-time stability theory and Lyapunov stability theory, a decentralized adaptive controller is proposed, which decreases the number of learning parameters. It is shown that the designed controller can ensure that all closed-loop signals are bounded and the tracking error converges to a small neighborhood of the origin. The simulation studies are presented to show the effectiveness of the proposed method.

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method.

Robust observer-based passive control for uncertain singular time-delay systems subject to actuator saturation.

This paper investigates the problem of robust observer-based passive control for uncertain singular time-delay system subject to actuator saturation. A polytopic approach is used to describe the saturation behavior. First, by constructing Lyapunov-Krasovskii functional, a less conservative sufficient condition is obtained which guarantees that the closed-loop system is regular, impulse free, stable and robust strictly passive. Then, with this condition, the design method of state feedback controller and the observer are given by solving linear matrix inequalities. In addition, a domain of attraction in which the admissible initial states are ensured to converge asymptotically to the origin is solved as a convex optimization problem. Finally, some simulations are provided to demonstrate the effectiveness and superiority of the proposed method.

Robust observer-based absolute stabilization for Lur'e singularly perturbed systems with state delay.

This paper is concerned with the problem of robust observer-based absolute stabilization for Lur'e singularly perturbed time-delay systems. The aim is to design a suitable observer-based feedback control law such that the resulting closed-loop system is absolutely stable. First, a full-order state observer is constructed. Based on the linear matrix inequality (LMI) technique, a delay-dependent sufficient condition is presented such that the observer error system is absolutely stable. Then, for observer-based feedback control, by introducing some slack matrices, a sufficient condition for input-to-state stability (ISS) of the closed-loop system with regard to the observer error is presented. Thus, the absolute stabilization of the closed-loop system can be guaranteed based on the ISS property. In addition, the criteria presented are both independent of the small parameter and the upper bound for the absolute stability can be obtained in a workable algorithm. Finally, two numerical examples are provided to illustrate the effectiveness of the developed methods.

Closed-loop firing rate regulation of two interacting excitatory and inhibitory neural populations of the basal ganglia.

This paper develops a new closed-loop firing rate regulation strategy for a population of neurons in the subthalamic nucleus, derived using a model-based analysis of the basal ganglia. The system is described using a firing rate model, in order to analyse the generation of beta-band oscillations. On this system, a proportional regulation of the firing rate reduces the gain of the subthalamo-pallidal loop in the parkinsonian case, thus impeding pathological oscillation generation. A filter with a well-chosen frequency is added to this proportional scheme, in order to avoid a potential instability of the feedback loop due to actuation and measurement delays. Our main result is a set of conditions on the parameters of the stimulation strategy that guarantee both its stability and a prescribed delay margin. A discussion on the applicability of the proposed method and a complete set of mathematical proofs is included.

Improved delay-range-dependent stability analysis of a time-delay system with norm bounded uncertainty.

This paper presents improved robust delay-range-dependent stability analysis of an uncertain linear time-delay system following two different existing approaches - (i) non-delay partitioning (NDP) and (ii) delay partitioning (DP). The derived criterion (for both the approaches) proposes judicious use of integral inequality to approximate the uncertain limits of integration arising out of the time-derivative of Lyapunov-Krasovskii (LK) functionals to obtain less conservative results. Further, the present work compares both the approaches in terms of relative merits as well as highlights tradeoff for achieving higher delay bound and (or) reducing number of decision variables without losing conservatism in delay bound results. The analysis and discussion presented in the paper are validated by considering relevant numerical examples.

Velocity control of servo systems using an integral retarded algorithm.

This paper presents a design technique for the delay-based controller called Integral Retarded (IR), and its applications to velocity control of servo systems. Using spectral analysis, the technique yields a tuning strategy for the IR by assigning a triple real dominant root for the closed-loop system. This result ultimately guarantees a desired exponential decay rate σ(d) while achieving the IR tuning as explicit function of σ(d) and system parameters. The intentional introduction of delay allows using noisy velocity measurements without additional filtering. The structure of the controller is also able to avoid velocity measurements by using instead position information. The IR is compared to a classical PI, both tested in a laboratory prototype.