Congestion tracking control for uncertain TCP/AQM network based on integral backstepping

This article focuses on the stabilisation problem of fluid-flow delay models of transmission control protocol/active queue management (TCP/AQM) networks by using a proportional-integral (PI) controller as AQM strategy. More precisely, the complete set of PI controllers that exponentially stabilises the corresponding linear time-delay system is derived. Using the particular geometric properties of this set of the controller parameters, the issues of robustness to uncertainty in the network parameters and to perturbation in the controller coefficients are addressed. Then, a methodology to compute a non-fragile PI AQM controller is provided. Finally, exponential estimates for the closed-loop system solutions, allowing to evaluate the performance of the corresponding PI-controlled closed-loop system, are proposed by using a Lyapunov–Krasovskii functional approach. An illustrative example completes the presentation.

In this study, the congestion control problem for multiple transmission control protocol/active queue management (TCP/AQM) networks with user datagram protocol (UDP) flows is investigated. Taking the UDP stream as the unknown interference and the maximum interference is obtained by the minimax theorem. A novel control algorithm is designed for multi‐TCP/AQM networks through backstepping control and command filtered technology. Simulation studies are carried out to verify the effectiveness and feasibility of the proposed method.

Congestion tracking control for multi-router TCP/AQM network based on integral backstepping

Sum-of-squares-based robust H∞ controller design for discrete-time polynomial fuzzy systems

Adaptive terminal synergetic-backstepping technique based machine learning regression algorithm for MPPT control of PV systems under real climatic conditions

Input-queued scheduling algorithms are designed to improve the throughput which use the input and output terminal in the router to obtain the maximum packets. And the length of the input queue is an important target, that can decides the superiority-inferiority about the capability of the input algorithm. With the existing algorithms, the main content about the scheduling algorithm are ensuring the packets’ high priority and low level. But most of these algorithms do not consider the length of queue. In this paper, we consider the change of queue length when the packets enter the input channel at the router, and put forward a shortest queue time-slot adapting algorithm (SQTA algorithm). First of all, SQTA algorithm can base the changes of transmittion time to control the packets’ sending time interval, and this action can make SQTA algorithm match the processing power about the router, and at the same time, this algorithm can reduce the length of the packets queue. Second, SQTA algorithm can control of a phenomenon that the packets may overflow when the length of queue is full, and that also make the packets transmitted more stable in network. The experimental result shows that this scheduling algorithm can control the length of queue effectively and reduce the waiting time with packets queue, It can be shorten the remaining service time, and can improve the network operation obviously.

The paper presents a robust nonlinear output feedback control system for the attitude control of satellites, with unstructured (unmodelled) dynamics in elliptic orbits, using solar radiation pressure. The nonaffine-in-control spacecraft model includes the gravity gradient torque, the control torque produced by two solar flaps, and external time-varying disturbance torque. The objective is to control the pitch angle of the spacecraft using the solar flaps. A robust feedback linearizing control law is derived for the trajectory control of the pitch angle. The controller includes a high-gain observer, which estimates the derivatives of the pitch angle as well as a lumped unstructured nonlinearity including the external disturbance moment in the pitch dynamics for synthesis. In the closed-loop system, the designed output feedback law accomplishes large angle rotational maneuvers. Simulation results are presented which show that in the closed-loop system, precise pitch angle control is accomplished, despite unmodelled nonlinearities and external disturbance torque in the model.KeywordsPitch AngleElliptic OrbitSolar Radiation PressureAttitude Control SystemSolar SailThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The service life and efficiency of proton exchange membrane fuel cells (PEMFCs) are significantly related to the control performance of the air supply system. Therefore, this research develops a novel robust observer-based- [Formula: see text]-variable model-free supertwisting fractional-order sliding mode control ([Formula: see text]-MF-STFOSMC) for complex nonlinear PEMFC air supply system with unmeasurable state variables, model uncertainties, and external disturbance. First, the fifth-order nonlinear PEMFC air supply system model is presented, and the unmeasured state variables are estimated using a nonlinear disturbance observer (NDOB1). Second, the ultra-local model (ULM) algorithm is employed to reconstruct the complex nonlinear PEMFC air supply system, avoiding the need for precise modeling and reducing the controller design difficulty. To estimate and compensate for the uncertain dynamics in the ULM algorithm, another NDOB2 is proposed to realize zero estimation error and finite-time observation. Besides, to achieve optimal control performance with less input chattering, finite-time convergence, and fast response speed, the [Formula: see text]-MF-STFOSMC is designed using super-twisting fractional-order sliding mode control (STFOSMC) algorithm. Furthermore, the stability of [Formula: see text]-MF-STFOSMC via a closed-loop system is verified using the Lyapunov theorem. Finally, the nonlinear PEMFC air supply system model with the proposed controller is realized in MATLAB/Simulink environment, and the simulation results are given to show the superiority and effectiveness of the proposed technique.

Prescribed-time constrained feedback control for an uncertain twin rotor helicopter

A solution to the problem of AMB control with reduced electrical power losses will be presented in this thesis. The proposed control solution will be founded on the integrator backstepping technique, which decouples the rotor stabilization problem from the bias flux design problem. It further allows for the easy redesign of the control law to compensate for uncertainties in the AMB system. A class of nonlinear controllers will be developed that reduces the AMB power losses in comparison to standard fixed-bias controllers, while containing no control singularity. Control laws will be presented for the standard AMB operating mode where both electromagnets are active at all times, as well as for the “energy-saving” operating mode where only a single electromagnet is active at any given time. The main contribution of this work is the development of a smart bias flux, and function of the rotor position and velocity. General conditions motivated by physical and mathematical properties are developed for the functional form of the bias, ensuring the reduction of power losses and the avoidance control singularities without affecting the closed-loop system stability. Simulation results also illustrate the interesting role the smart bias plays in stabilizing the rotor. Note that while the power loss discussion in this thesis is focused on ohmic losses, the proposed control strategies also help reduce eddy current- and hysteresis-induced losses due to their proportionality to the magnetic flux.

This paper designed a trajectory tracking controller for an underwater vehicle considering model uncertainties and external force disturbances using the Port-Hamiltonian (PH) control theory. Firstly, the mathematical model of the underwater vehicle is established and expressed under the PH framework. However, the hydrodynamic force coefficients inside the mathematical model are hard to obtain accurately without detailed towing tank experiments. To address this, we will propose a parameter observer to estimate the unknown parameters caused by model uncertainties. Meanwhile, the vehicle inevitably suffers from external unknown force disturbances driven by current and wind. So another observer based on passivity theory is proposed to address the unknown fore disturbance. The control law is derived from reshaping kinetic energy and injecting damping terms via the interconnection and damping assignment passivity-based control method. This proposed controller has a physical interpretation. Moreover, it has been proved that the proposed controller can enable vehicles to track the desired trajectory and minimize the tracking errors exponentially. Numerical simulations and comparisons illustrate the stability and effectiveness of the proposed controller to model uncertainties and unknown external disturbances.KeywordsUnmanned underwater vehiclePort-controlled Hamiltonian systemTrajectory tracking control

Finite-time trajectory tracking control for unmanned ground vehicle based on finite-time disturbance observer

Reducing the queue length and queuing delay in the buffer which in turn reduces congestion and latency in the network are of great importance for real-time video services. In this paper, we propose a perceptual quality-aware queue management mechanism to shorten the queue length and waiting time of video traffic in a finite buffer. Our proposed approach prioritizes video layers in a stream in accordance with their hierarchical structure and selectively drops packets from different layers under a target user perceived quality constraint. This in turn reduces network load and latency and increases the capacity to serve more concurrent streams while satisfying users' perceptual quality requirements. We develop a statistical queuing model to express the delay requirements of video layers with an equivalent cross-layer constraint We then formulate the queue management problem as a minimization of queuing delay using a selective packet drop approach under perceptual quality and queue expiry time provisioning. Numerical results show that our proposed approach outperforms the widely deployed random early detection (RED) and tail drop (ID) queue management schemes in terms of reducing queuing delay and queue length in the buffer, while increasing the fraction of perceived quality-satisfied users.

The rapid growth of the food and beverage sector, especially in bustling urban environments, requires ongoing improvements in operational effectiveness to keep up with the rising demand and client standards. This study examines the queue management system at the Hasanudin branch of Bebeke Om Aris, a renowned restaurant in Bandung, Indonesia, that specializes in duck and chicken cuisine. The restaurant's operational performance is significantly impacted by extended waiting times experienced during busy periods. The objective of this research is to to develop and evaluate strategies for diminishing waiting times and enhancing overall efficiency through a quantitative methodology. This study was driven by the observed inefficiencies in the current queue management system, characterized by huge waits and longer waiting periods, especially on weekends. These inefficiencies not only impede the delivery of services but also provide a possible threat to the restaurant's competitive standing in the market. The main goal of this study is to determine and recommend effective strategies for optimizing queue management in order to achieve a maximum waiting time of 5 minutes during the busiest hours, as specified by the restaurant's management. During a four-week period, a structured observation method was used to collect primary data on customer arrivals, queue lengths, and waiting times. The observation notably targeted Saturday evenings, which are known for having the highest client inflow. The gathered data was subsequently employed to generate simulation models using Arena software, which assessed different scenarios, such as the integration of self-service kiosks, the adoption of QR code ordering systems, and the augmentation of cashier counters. The queuing theory was employed to examine these scenarios and assess important performance measures, including average waiting time, queue length, and system utilization rates. The investigation demonstrated that the integration of self-service kiosks and QR code ordering systems can effectively decrease waiting times and enhance operational efficiency. The self-service kiosks enable customers to autonomously place orders, thereby decreasing the burden on cashiers and expediting the ordering procedure. Similarly, the implementation of the QR code system simplifies the procedure by allowing customers to place orders and make payments directly from their smartphones, thereby reducing congestion at the cashier. The simulation results demonstrated a significant reduction in both mean waiting times and queue lengths, thereby successfully attaining the intended performance goals. This study's findings enhance the subject of operational management by showcasing how queuing theory and simulation tools may be practically applied to optimize service delivery in the food service industry. The suggested solutions give a scalable approach that can be customized for other comparable environments, providing a foundation for restaurants seeking to improve their service efficiency and customer satisfaction. Subsequent studies could investigate the enduring impacts of these interventions on customer behavior and business performance, as well as their suitability in various categories of food service enterprises

We explore the relationship between a yield stress fluid flow in a Hele-Shaw cell with irregular walls, and a non-Darcy 2D porous medium flow with limiting pressure gradient. The continuum (Hele-Shaw) flow is a much-studied simplification of a cementing displacement flow model, solved via a variational formulation that leads to a convex streamfunction minimization problem. Our interest is with the analogy between the discretization used for the numerical solution and network flows that model the associated porous media flow, i.e. via the pore-throat approach. A staggered mesh, with pressure nodes at the cell corners and streamfunction nodes at the cell center is used for the continuum problem, which naturally separates into a network representation comprising primal and dual graphs, linking streamfunction and pressure nodes, respectively. We show explicitly how the continuum model defines a network model and vice versa. We develop the variational form of the network flow, including an appropriate (discrete) streamfunction minimization and a discrete version of the principle of virtual work. Two network models are explored, based on different interpretations of the minimization problem. The network flow results are compared with analogous computed continuum flow results in 3 specific geometries. We find that our network model I, which is the most natural interpretation of the continuum model as a network flow using our discretization, generally under-predicts flow rates. This is problematic from the perspective of considering the network flow as an approximation to the porous media or Hele-Shaw flow. Network model II rectifies this situation, via a pressure interpolation method. In our examples we find that the network II flow converges to the continuum flow as the mesh and network are refined. This is not the usual comparison made, as in many pore-throat models the network is fixed according to the underlying pore-space geometry. Despite the differences, both network models have their own advantages and disadvantages. Network model I offers a more natural way of modelling the flow and is easier to apply, for example to complex meshes, e.g. unstructured triangular. Network model II gives the more accurate physical representation of the Hele-Shaw flow. Lastly, we have developed approximate algebraic relationships for the total flow rate as a function of the total applied pressure gradient, both close to the critical onset pressure and for large pressure gradients. These correlations align well with previous findings for Bingham fluid flows in porous media. • Hele-Shaw cell – porous media analogy derived for Herschel-Bulkley fluids. • Discrete pore-throat network models derived. • Discrete principle of virtual work. • Convergence as network is refined. • Improved network model that gives convergence.