In this paper, we consider the effects of exogenous disturbances on the closed-loop system of the congestion control problem in a network with general structure. This investigation is important since many of data flows in internet network are considered as unmodeled flows. In contrast to previous works, we suppose that both senders and links in the network have dynamics. Each sender updates its sending rate to minimize its own cost function. The network is modeled based on fluid flow approximation with nonlinear dynamics for the links. In this research, we first derive the conditions for the existence of the system equilibrium point taking into account the constraint sets of the problem. Then, we prove input-to-state stability (ISS) of the closed-loop system for the congestion control problem with input and output disturbances in the network links. We further show that the obtain results are valid even when the routing matrix of the network varies. Finally, we verify the theoretical results by simulation on two different multi-link networks.

In this paper, an adaptive fuzzy extended state observer is proposed to estimate the states and external disturbances simultaneously for Single-Input-Single-Output nonlinear affine systems. The observer gains are time-varying and adjusted using an adaptive law. The Takagi-Sugeno fuzzy system is used for modeling that, unlike Mamdani methods, provides a more precise and comprehensive analysis. The proposed adaptive fuzzy observer is designed to relax the limitations of the extended state observers and improve system performance as compared to the classical methods in presence of time-varying disturbances. Moreover, the stability of the proposed method and the convergence of the estimation error are analyzed using the Lyapunov stability Theory. The performance of the proposed method is shown in simulations of control of the inverted pendulum. The simulation results, as compared to the non-adaptive fuzzy observer, show better performance in terms of transient and steady-state responses, control input amplitude, and robustness in presence of measurement noise and external disturbances.

In this paper, a tracking decentralized Adaptive Integral Terminal Sliding Mode control (DAITSMC) technique is proposed for a class of linear interconnected mechanical systems with unknown linear interconnections between subsystems and in the presence of disturbance is considered. In this way, the interconnected system is divided into several subsystems. Then an integral terminal sliding surface is considered for each subsystem. The proposed approach increases the speed of input tracking in a finite time as well as the disturbance attenuation. The effect of unknown linear interconnections between subsystems is considered as uncertainty that is estimated by adaptive rules. The stability of the closed-loop system is guaranteed by a Lyapunov function and selecting the appropriate design parameters. The developed method is applied to two interconnected mechanical systems; the simulation results show that the proposed method (DAITSMC) is efficient for interconnected systems in the presence of disturbance. Comparison of simulation results with several control methods shows that the proposed method (DAITSMC) is efficient for linear interconnected systems in the presence of disturbance and the convergence error becomes zero faster.

The event-triggered approach is a scheduling strategy designed to reduce the frequency of control signal updates over time, aiming to enhance overall system efficiency concerning energy consumption and network bandwidth, while maintaining the stability and performance of the control system. This paper investigates the problem of designing an event-based controller for linear time invariant (LTI) systems in the presence of mismatched external disturbances. It is assumed that certain state variables can be directly measured as outputs. The design of an event trigger sliding mode observer is investigated by incorporating a Luenberger observer to meet the H_∞ performance requirements. A sliding mode controller is designed using the Lyapunov method to ensure that the system trajectories remain within the predefined sliding surface. Furthermore, the tuning parameters of the sliding surface and the state observer are calculated using linear matrix inequality (LMI) to achieve asymptotic stability of the sliding mode dynamics with a prescribed H_∞ index. Finally, a non-zero lower bound for the minimum inter-event interval is determined to prevent Zeno phenomena. Then, two numerical examples are provided to demonstrate the performance of the developed controller. Simulation results indicate that, besides achieving the objective of stabilizing the closed-loop system, the control commands generated by the controller are significantly reduced.

Today, the magnetic levitation system is widely used in various industries. This system is inherently unstable and nonlinear, which is presented by nonlinear equations. On the other hand, the existence of a time delay in these systems also causes system instability or even chaos, which creates additional problems in their control, thus requiring the design of robust and optimal control. In this paper, a robust adaptive intelligent controller based on the backsteppingsliding mode is proposed for the stability and proper tracking of the magnetic levitation system in the presence of time delay, uncertainty, and external disturbances. Due to changes in the equilibrium point, comparative control is used to update the system’ s momentary information and intelligent controller to estimate uncertainties and disturbances and non-linearity of the system. A robust controller is used to asymptomatic stabilize the Maglev system. The Lyapunov stability theory is used to analyze the stability of the magnetic levitation system with the proposed controller. In the end, in order to demonstrate the performance of the proposed controller, numerical simulations have been used in MATLAB software. The simulation results show that good tracking has been performed and the controller is very good against noise and disturbance.

The model-based controllers need a mathematical model of the system, whereas the data-driven controllers operate based on measuring the input-output data. Nowadays, considering complexity of the industrial systems and unavailability of an accurate mathematical model of the system, scientists try to reduce dependency of the controllers on the mathematical model. In this paper, an adaptive sliding-mode data-driven controller for a class of unknown multi-input multi-output nonlinear discrete-time systems is proposed. Because the chattering phenomenon is the main challenge of the sliding-mode controllers, an adaptive sliding-mode controller is used to solve this problem. In addition, to solve the dependencies of the controller on the mathematical model, the proposed adaptive sliding-mode controller is combined with a data-driven controller. Next, the new adaptive laws for the switching gain and the Pseudo Jacobian Matrix (PJM) are calculated. In addition, the closed-loop stability based on the Lyapunov theory is investigated. To show performance of the controller, the proposed method is applied to a three-tank system. The proposed controller has some advantages in comparison with similar methods in references, such as reducing the conservatism and complexity in the controller design and simplifying the closed-loop stability analysis. The simulated results show that the proposed method better tracks the reference signals and improves rejection of the external disturbances. Furthermore, the chattering phenomenon is considerably reduced.

Background and Objective: Several studies have reported significant disturbances in vertical posture during various standing and walking conditions, but there is little evidence about the behavior of related muscles in dynamic conditions such as external perturbation, so this study was done to investigate and to compare the delay in response of upper trapezius and sternocleidomastoid muscles as two superficial muscles in the neck area, in posterior-anterior perturbation among patients with chronic neck pain and healthy subjects.Materials and Methods: This study was a case-control study with simple nonprobable sampling.32 subjects (16 healthy subjects and 16 patients with chronic neck pain) participated the study. Data collection was done using questionnaire and test performance .The equipments included dynamometer, chronometer and surface kinesiology electromyography .Dropping the weight equal to 10% of total body weight, performed using electrical magnet, followed by pulling of the trunk inducing perturbation was performed.Results: There were significant statistical differences in response onset of upper trapezius(p=0.032) and sternocleidomastoid(p=0.012) muscles between two groups.This meant the response onset in patients was longer than healthy subjects.Conclusion: Pain can change the onset of response of trapezius and sternocleidomastoid muscles and possibly decrease muscle activity in deep muscles and change the pattern of muscle activation and possibly it can increase the risk of injury in patients with chronic neck pain.

This paper proposes a novel hybrid control framework by combing enhanced extended state observer with trajectory linearization control for air vehicle acceleration tracking problems. First, based on the tracking error dynamics derived by Taylor expansion for the original nonlinear system along the desired trajectory, a feedback linearization-based control law is designed to stabilize a linear time-varying system. To reduce the controller performance sensitivity to uncertainties, with partial model information, an enhanced extended state observer is constructed to estimate the tracking error vector, as well as the uncertainties in an integrated manner. The closed-loop stability of the system under the proposed compound scheme is established. Both numerical simulation studies and an application example of air vehicle acceleration autopilot design demonstrate the feasibility and efficacy of the proposed method.

In this paper, the finite time control of 2nd order multi-agent systems (MASs) consisting of a leader and a number of followers under external disturbance is discussed. The communication graph of agents is considered non-directional and the distance between them is considered constant. The goal is to design a robust adaptive sliding mode controller which, by estimating the upper and lower limits of the disturbance, not only ensures the finite time stability of the system, but also does not increase the tracking error range between the agents. For this purpose, a new slip surface is defined, which becomes zero under the considered controller, both of the above goals are met. The second Lyapunov theorem is used to prove the stability of the system and an unbounded radial Lyapunov function is presented in terms of the new slip surface and estimation errors. Based on the communication structure of the factors, the necessary control and adaptive rules will be obtained to make the derivative of the Lyapunov function negative. The results are presented in the form of a theorem with proof. In order to validate this method, two scenarios with different movements of the leader are examined. It is shown that the mentioned system is finite time stable under the presented control method and the tracking error between the agents reaches zero.