Sharif Digital Repository

An approximated quadratic programming optimization is proposed to determine a model predictive controller to guarantee end-to-end delay in the DiffServ architecture. The proposed algorithm, called the suboptimal model predictive control scheduler (SMPCS), regulates the service rates of aggregated traffic classes dynamically, such that some constraints on proportional or absolute delay can be guaranteed. This paper investigates SMPCS complexity and its implementation problems in high-speed routers. The main problem of model predictive control (and one which has limited its use to slow processes) is its complexity. Optimization is the most computationally complex part in a model predictive... 

An increasing number of different applications face the challenge of providing end-to-end quality of service (QoS) support such as bandwidth, delay, jitter, and packet loss. In this paper, we have focused on DiffServ architecture to improve its accuracy. We proposed a new algorithm, called Adaptive Model Predictive Control Scheduler (AMPCS), to schedule differentiated buffers in routers, using Adaptive Model Predictive Control as the controller. AMPCS regulates the service rates of aggregated traffic classes dynamically in a way that some constraints on proportional delay or absolute delay can be guaranteed. Our contribution is to apply a model predictive controller to the scheduling problem... 

An approximated quadratic programming algorithm is proposed to determine a model predictive controller, which is applied to the scheduling problem. We name the algorithm Sub-optimal Model Predictive Control Scheduler (SMPCS). The SMPCS prepares a platform to guarantee end to end proportional delay in DiffServ architecture. This paper investigates the complication of SMPCS and its implementation problems in high speed routers. In order to efficiently implement the controller we admit sub-optimal results against reduction in the complexity of the optimizer. Simulation results show that the proposed approximation improves speed of the controller considerably. © Springer-Verlag Berlin Heidelberg... 

In this paper, adaptive model predictive control is applied to schedule differentiated buffers in routers. The proposed algorithm, adaptive model predictive control scheduler (AMPCS), dynamically regulates the service rates of aggregated traffic classes. This algorithm guarantees some required constraints on proportional or absolute delay. The control parameters and the way they are adjusted as well as the problems of implementing the controller at high data rates are investigated. Theoretical analysis and numerical simulations demonstrate stability of AMPCS and its acceptable quality of service differentiations at core routers while maintaining end to end delay constraints. © 2007 Elsevier... 

This paper studies the real-time energy management of large-scale residential households and standalone electric vehicles charging stations using a non-cooperative game based on consensus protocol. We consider a set of aggregators, each equipped with a processor, to minimize its own cost function by having access to the local estimation terms of neighboring aggregators. Since the cost function of each aggregator is affected by strategy of other aggregators through total generation cost, such interaction among competitive agents is modeled as a non-cooperative game. An idea based on model predictive control is utilized to deal with highly random behavior of users. In this paper, a time-of-use... 

Using a non-linear model in model predictive control (MPC) changes the control problem from a convex quadratic programme to a non-convex non-linear problem, which is much more challenging to solve. In this study, we introduce an MPC algorithm for non-linear discrete-time systems. The systems are composed of a linear constant part perturbed by an additive state-dependent non-linear term. The control objective is to design a state-feedback control law that minimises an infinite horizon cost function within the framework of linear matrix inequalities. In particular, it is shown that the solution of the optimisation problem can stabilise the non-linear plants. Three extensions, namely,... 

In this research, two shake table experiments were conducted to study the effects of non-liquefiable crust layer and superstructure mass on the responses of two sets of 2 × 2 pile groups to liquefaction-induced lateral spreading. In this regard, an inclined base layer overlain by a very loose liquefiable layer was constructed in both models; while only in one model, a non-liquefiable crust layer was built. A lumped mass, being representative of a superstructure, was attached to the cap of one pile group in both models. The models were fully instrumented with various sensors, including acceleration, displacement, and pore water pressure transducers. Also, the piles were instrumented with pair... 

Ontology Aligning is an answer to the problem of handling heterogenous information on different domains. After application of some measures, one reaches a set of similarity values. The final goal is to extract mappings. Our contribution is to introduce a new genetic algorithm (GA) based extraction method. The GA, employs a structured based weighting model, named "coincidence based model", as its fitness function. In the first part of the paper, some preliminaries and notations are given and then we introduce the coincidence based weighting. In the second part the paper discusses the details of the devised GA with the evaluation results for a sample dataset  

In this paper an extended approach to the nonlinear DMC algorithm is proposed, which can handle constrained and MIMO systems under some defined conditions. This extension also admits higher control, M, and prediction, P, horizons that are required to increase the performance of the controller in most practical applications. Simulation results of the proposed method in the control of a stirred tank reactor with 2 inputs and 2 outputs nonlinear model are presented to illustrate effectiveness of the method and its justification. © 2003 IEEE  

In this paper, an extended approach to the nonlinear DMC algorithm is proposed, which can handle constrained and MIMO systems under some defined conditions. This extension also admits higher control horizon, M and prediction horizon, P that are required to increase the performance of the controller in the most practical applications. Simulation results of the proposed method in the control of a stirred tank reactor with 2 inputs, 2 outputs nonlinear model and also a power unit nonlinear model with 3 inputs, 3 outputs are presented to illustrate effectiveness of the method and its justification. © 2005 Elsevier Ltd. All rights reserved  

In this paper, the convergence and stability conditions of extended DMC in the control of nonlinear SISO and MIMO systems are investigated. The formulations are based on the ordinary DMC in which, with successive linearization of the nonlinear model and new interpretation of disturbance, the nonlinear extension is deduced. In addition, new convergence and stability criteria are derived for SISO and MIMO systems. These criteria include convergence and stability in the case of longer control (M > 1) and prediction (P > 1) horizons, as well as the finite and infinite sampling time. Finally, the simulation results for a MIMO (3 × 3) model, based on a power unit nonlinear plant, are presented. ©... 

This letter introduces a consensus-based generalized multi-population aggregative game coordination approach with application to electric vehicles charging under transmission line constraints. The algorithm enables agents to seek an equilibrium solution while considering the limited infrastructure capacities that impose coupling constraints among the users. The Nash-seeking algorithm consists of two interrelated iterations. In the upper layer, population coordinators collaborate for a distributed estimation of the coupling aggregate term in the agents' cost function and the associated Lagrange multiplier of the coupling constraint, transmitting the latest updated values to their population's... 

In an original impulsive synchronization only instantaneous errors are used to determine the impulsive inputs. To improve the synchronization performance, addition of an integral term of the errors is proposed here. In comparison with the original form, the proposed modification increases the impulse distances which leads to reduction in the control cost as the most important characteristic of the impulsive synchronization technique. It can also decrease the error magnitude in the presence of noise. Sufficient conditions are presented through four theorems for different situations (nominal, uncertain, noisy, and noisy uncertain cases) under which stability of the error dynamics is... 

In this paper the impulsive synchronization of general continuous chaotic and hyperchaotic systems is investigated. The robust stability of the synchronization method is examined in the presence of uncertainties both on linear and nonlinear parts of the system dynamics and the channel noise. Conditions on the impulse distances are derived for different cases. Numerical simulations are presented to show the effectiveness of the method. © 2007 Elsevier B.V. All rights reserved  

The impulsive synchronization has been employed to synchronize two different hyperchaotic (chaotic) systems. Conditions on impulse distances are given in order to obtain stable synchronization in the nominal case and robust stability in the case that we experience uncertainties in the systems dynamic and/or measurement noise. Under the given conditions, it is guaranteed that the error dynamics is asymptotically stable for the nominal case and convergent to a predetermined level for uncertain and/or noisy circumstances. Computer simulations are provided to assess results of the given theorems in the paper. © 2006 Elsevier Ltd. All rights reserved  

In this Letter the impulsive synchronization of the Chen's hyperchaotic systems is discussed. Some new and sufficient conditions on varying impulsive distance are established in order to guarantee the synchronizabillity of the systems using the synchronization method. In particular, some simple conditions are derived in synchronizing the systems by equal impulsive distances. Two illustrative examples are provided to show the feasibility and the effectiveness of the proposed method. The boundaries of the stable regions are also estimated. © 2006 Elsevier B.V. All rights reserved  

Destructive damages to deep foundations due to liquefaction-induced lateral spreading during or after major earthquakes in gently sloping or level grounds with a free end have been observed in many earthquakes. The pile foundations supporting structures located in or near the ports and harbors, and also bridge piers, are the most vulnerable structures in this respect, as have been observed in various events in earthquake-prone areas all around the world for decades. Many physical and numerical modeling studies have been carried out to study and understand the insight into different aspects of this phenomenon. In this regard, 1g shake table and Ng centrifuge tests using both rigid and laminar... 

To deal with strong nonlinearity in nonlinear systems, a new method called cascade multiple-model predictive controller based on gap metric and stability margin, is proposed. The gap metric is utilized to describe the nonlinear system by a linear model bank. It is possible to select nominal local models from the linear model bank by an algorithm based on the gap metric and stability margin to avoid the redundancy of the local controllers. By scheduling proportional controller for each nominal local model, the robust stability is guaranteed whereas there will be no guarantee for the desired performance. Then, by designing a model predictive controller in the cascade structure, the closed loop... 

The aim of this study is to reduce the computational load in model predictive control of multi-input nonlinear systems. First, the nonlinear system which has a high number of states and inputs is decomposed into several subsystems by solving a linear integer programming problem offline. Then, the model of each subsystem is revised by considering the effect of coupling and interactions of other subsystems. Next, the robust model predictive technique based on linear matrix inequalities is employed to compute control signal for each subsystem. An industrial chemical reaction example is used to illustrate the effectiveness of the proposed method. © 2017 IEEE  

Adaptive Model Predictive Transmission Control Protocol (AMP-TCP) as a new TCP delay-based congestion control algorithm is introduced. Both aspects of design and implementation of the algorithm are described using simulations on the ns-2 network simulator. The design stage is composed of two steps. First, a recursive system identification approach is proposed to capture the network delay dynamics from TCP source view. Second, the proposed modeling is employed to develop an adaptive model predictive TCP congestion control strategy in the absence of any explicit congestion notification. The characteristics and performance of AMP-TCP are investigated using several network simulations. Finally a...