Sharif Digital Repository

Predictive functional controller originally developed based on a first order reference model. In this paper the related equation of the predictive functional control is derived for an arbitrary reference model and then a simple approach to tune different parameters of the controller is examined by applying the controller on a benchmark problem. Finally, the robustness of the design is improved using the so called Youla parameterization approach. © 2005 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, 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  

Representing nonlinear systems by linear models along with structured or unstructured uncertainties and applying robust control strategies could reduce the computational complexity in comparison with implementing the nonlinear model predictive controllers. In this paper design of robust model predictive controllers which are based on special classes of nonlinear systems representations called Wiener and Hammerstein are presented. The proposed algorithms approximate the nonlinear systems by uncertain linear models and reduce online the computational demands in the control implementation. The advantages of the proposed approaches are illustrated by two examples  

This paper proposes a multi-unit building model, in which the parameters are obtained via an online identification process. The identification process is carried out on-the-fly so it can update the best model of the building units. A model predictive controller (MPC) is also employed that uses the prediction of the building model, as well as the weather forecast data and acts on the heating boiler in an optimal fashion. In addition, since the controller is designed for a multi-unit building, it is crucial to estimate the amount of the delay that takes the hot flow to reach the units. This paper presents a very simple method for the delay identification based on unscented kalman filter. For... 

In this paper, a new effective and computationally reduced method for congestion control in high speed dynamic computer networks is introduced. The controller is designed using the well-known predictive functional control (PFC) scheme and an ARMarkov model representation that considers the system delay explicitly. Use of the multi-step-ahead predictive ARMarkov model structure within the PFC results in a simple algebraic control law that does not require recursive model output computation in the so-called prediction horizon performed in the other Model Predictive Controllers (MPC). This combination not only reduces the required computational load, but the accumulative error due to the model... 

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... 

Presented in this paper are a method, named the Dynamic Rule Prediction (DRP), which predicts the behavior of a system and its application in designing a controller. The aim of the study is to overcome some of the limitations and shortcoming of the other modeling methods. The effectiveness of this method is verified. The controller based on DRP possesses two main features. It can control the system without any prior knowledge of the controlled plant. It is, also, superior as its high-speed prediction. This paper focuses on the robot manipulator controllers and applications of this approach in it  

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  

This paper develops methodology and technique tor the design, analysis, and impie mentation of an adaptive generalized predictive controller (AGPC) for Active Queue Management in TCP Networks. The TCP/AQM dynamic is modeled experimentally as a second-order system with a time delay where its parameters are estimated using the standard gradient algorithm. Based on this model, an AGPC is designed to gain the set-point tracking and robustness. AGPC, as a queue-based control mechanism, responds quickly to traffic changes, thus allowing for high utilization and small loss. We illustrate our results using ns-2 simulations and demonstrate the practical impact of adaptive model reference control on... 

Controlling inverters with LC output filters in order to achieve a high quality desired output voltage or current is a challenging problem in power electronics. The LC filter and the binary nature of switch state variables increase the difficulty of achieving a single comprehensive model for the system. In this paper, a hybrid model is presented for a three-phase inverter with an LC output filter and a three-phase RL load. Then, the Model Predictive Control (MPC) algorithm is applied to the model and a geometrical approximate method is used to fit the answers to the binary values. Simulation results for a sample system verify the usability of the method and the quality of the answers  

A predictive functional controller based on ARMarkov model structure has been designed to control welding current and arc voltage in a GMAW process. The closed loop system performance is investigated through computer simulations and is compared by those achieved from implementing two commonly used controllers i.e. PI and feedback linearization based PID. The local stability of the closed loop system is analyzed in the presence of uncertainties in the linearized model of the process as well as the control parameters. Finally it is shown that the proposed controller performs like a PI controller along with a pre-filter compensator  

Experimental permeability and diffusivity values for CO2 and CH4 through imidazolium-based ionic liquid 1-hexyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([hmim][Tf2N]) were determined in the temperature range of 300-320K using temperature correction factor defined in our previous study. According to literature, experimental values of permeability and diffusivity obtained in this study for CO2 in [hmim][Tf2N], showed good agreement with predictive models reported by other researchers. In addition, experimental values of permeability and diffusivity for CH4 in [hmim][Tf2N] as a function of pressure have been reported in this study. Considering the results of present study and... 

The Proton Exchange Membrane Fuel Cell (PEMFC) control system has an important effect on operation of cell. Traditional controllers couldn't lead to acceptable responses because of time- change, long- hysteresis, uncertainty, strong- coupling and nonlinear characteristics of PEMFCs, so an intelligent or adaptive controller is needed. In this paper a neural network predictive controller have been designed to control the voltage of at the presence of fluctuations of temperature. The results of implementation of this designed NN Predictive controller on a dynamic electrochemical model of a small size 5 KW, PEM fuel cell have been simulated by MATLAB/SIMULINK  

High center of mass vehicles are likely to rollover in extreme maneuvers. Available works present control strategies to prevent rollover. In these works, however, other important parameters such as path trajectory tracking are not a main concern. In this paper conflicts between rollover prevention and trajectory tracking is investigated. Model predictive control (MPC) is adopted to predict and avoid rollover while tracking desired trajectory. For this regard a model based future error estimation is introduced. The control framework predicts both rollover and trajectory error simultaneously. It avoids rollover while tries to track the trajectory. Simulation results for two controllers with... 

Electric Vehicles (EVs) will be used rampantly in future transportation system. Although the uncontrolled charging of these EVs will be threatening for the stability of the grid, a compatible energy trading policy may provide beneficial services to the grid as well as preserving the sustainability of the system. In this paper, by taking advantage of block rate tariff, a wholesale pricing policy is introduced. A multi-objective approach is utilized to address the cost reduction and load leveling services concurrently. Due to the high computational complexity of a centralized problem, a game theoretic approach is exerted in order to design decentralized controllers for EVs. Moreover, an MPC... 

In this paper, a hierarchical predictive controller is designed in order to solve the tracking problem of a moving ground target by a quad-rotor in an unknown and uneven environment. This controller has internal and external predictive controller levels. In the lower layer of the controller, a constrained predictive controller is designed that is capable of rejecting perturbations and quickly tracking the reference path, and in the outer loop, a model predictive controller is designed to optimally detect the moving ground target where, the sub-cost functions were defined so that the quad-rotor would be able to track the moving ground target even if it was temporarily out of sight of the... 

The Extended dynamic matrix control (EDMC) has been proved to extend the existing version of the linear model predictive control to control nonlinear systems. In this method, the control input is determined based on the linear model approximation of the system that is updated during each sampling interval. In this paper, by using this method, a new control scheme for quasi-resonant converters is described. This control offers an excellent transient response and a good tracking. © 2008 IEEE  

In this paper, a novel generalized predictive control (GPC) strategy using multiple models approach has been presented. The proposed strategy is realized based on the Takagi-Sugeno-Kang (TSK) fuzzy-based modeling for control of a tubular heat exchanger system. In this strategy, different operating environments of the system with varying parameters are first identified. Then for each environment, a linear model and its corresponding fuzzy predictive controller are designed. For demonstrating the effectiveness of the proposed approach, simulations are done and the results are compared with those obtained using the single model predictive control approach. The results can verify the validity of... 

Nonlinearity caused by actuator constraint plays a destructive role in the overall performance of a control system. A model predictive controller can handle the problem by implementing a constrained optimization algorithm. Due to the iterative nature of the solution, however, this requires high computation power. In the present work we propose a new method to approach the problem by separating the constraint handling from the predictive control job. The input constraint effects are dealt with in a newly defined component called a predictive directional compensator, which works based on the directionality and predictive concepts. Through implementation of the proposed method, the... 

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...