Sharif Digital Repository

Special attention is given to vertical takeoff and landing air vehicles due to their unique capabilities and versatile missions. The main problem here is control effectiveness at low flight speeds and transition maneuvers because of the inherent instability. RMIT is a small sized tail-sitter ducted fan air vehicle with a particular configuration layout, multiple control surfaces, low weight, and high-speed flight capability. In the current study, a comprehensive nonlinear model is firstly developed for RMIT, followed by a validation process. This model consists of all parts including aerodynamic forces and moments, control surfaces term together with the gravity and driving fan forces.... 

The power quality has become a major concern since late 1980's. There has been increasing interest in studying power quality problems, one of which is the existence of the current/voltage harmonics. In order to eliminate these harmonics, different methods have so far been proposed and developed. In this paper, line current harmonics reduction is achieved by using an active filter. More specifically, our aim is to introduce a proper control design method for the current control part of the active filter. To achieve the goal, two different predictive controllers are examined. Due to the existing physical constraints (switching frequency and computational limits) in real applications, a new... 

This paper investigates the control of diesel engines comprising two actuators: exhaust gas recirculation (EGR) valve and variable geometry turbocharger (VGT) to mitigate the exhaust emissions. In contrast to conventional control techniques, multi-model predictive control (MMPC) algorithm is employed for control purposes. With the help of proposed scheme, constraints of the control problem is also considered and nonlinear model to enhance performance is utilized. In doing so, new controller tries to fulfill a compromise between fuel consumption and torque response by regulating air-to-fuel ratio and EGR fraction to decrease pollutants emission especially nitrogen oxides (NOx). The dynamic... 

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... 

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... 

Control of MMA polymerization batch reactor has intensively investigated. The nonlinear and time varying behavior of the system makes its control a challenging task. MPC algorithm is enjoying an increasing application for control of chemical processes. A sequential linearized model based predictive controller based on the DMC algorithm was designed to control the temperature of a batch MMA polymerization reactor. A genetic algorithm (GA) is suggested to optimize the cost function of DMC. The controller performance was studied via simulation. The controller performance in tracking the profile, noise and disturbances rejection is very good  

This paper describes an application of intelligence- based predictive scheme to load-frequency control (LFC) in a two-area interconnected power system. In this investigation, at first, a dynamic model of the present system has to be considered and subsequently an efficient control scheme which is organized based on Takagi-Sugeno-Kang (TSK) fuzzy-based scheme and linear generalized predictive control (LGPC) scheme needs to be developed. In the control scheme proposed, frequency deviation versus load electrical power variation could efficiently be dealt with, at each instant of time. In conclusion, in order to validate the effectiveness of the proposed control scheme, the whole of outcomes are... 

The purpose of this paper is to deal with a novel intelligent predictive control scheme using the multiple models strategy with its application to an industrial tubular heat exchanger system. The main idea of the strategy proposed here is to represent the operating environments of the system, which have a wide range of variation in the span of time by several local explicit linear models. In line with this strategy, the well-known linear generalized predictive control (LGPC) schemes are initially designed corresponding to each one of the linear models of the system. After that, the best model of the system and the LGPC control action are precisely identified, at each instant of time, by an... 

The purpose of the paper presented here is to deal with the well-known linear generalized predictive control (LGPC) scheme based on multiple models strategy for a tubular heat exchanger system. In this control strategy, the operating environments of the system are first represented by multiple explicit linear models. Then the best model of the system is precisely identified by a novel intelligent decision mechanism (IDM), where is organized in association with the fuzzy adaptive Kalman filter and recursive weight generator approaches. As soon as the best model of the system is identified, the corresponding predictive control action is instantly implemented on the system. In order to... 

In this paper, a decentralized model predictive control approach is proposed for discrete linear systems with a high number of inputs and states. The system is decomposed into several interacting subsystems. The interaction among subsystems is modeled as external disturbances. Then, using the concept of robust positively invariant ellipsoids, a robust model predictive control law is obtained for each subsystem solving several linear matrix inequalities. Maintaining the recursive feasibility while considering the attenuation of mutual coupling at each time step and the stability of the overall system are investigated. Moreover, an illustrative simulation example is provided to demonstrate the... 

In this paper, a new strategy for control of tubular heat exchanger system has been presented. The proposed approach is realized using generalized predictive control (GPC) scheme and multiple models method. By using the multiple models approach, different operating environments of the system are first modeled. Then in each instant of time, the best model of the system is identified by a fuzzy decision mechanism. Finally, the best control input is chosen appropriately. For demonstrating the effectiveness of the proposed approach, simulations are done and the results are compared with those obtained using the single model predictive controller approach. The results can verify the validity of... 

Abstract This paper proposes a bumpless transfer method to overcome the problem of switching jumps in a scheduled robust model predictive control approach. A scheduled robust model predictive controller implements a set of local robust model predictive controllers based on an on-line switching strategy. This method could enlarge the domain of attraction efficiently but the transient response might be hampered by spikes appearing at the moment of switching between adjacent local controllers. The proposed algorithm could enhance the transient response by implementing some intermediate controllers augmented to the main control scheme to solve the problem without needing more computation. The... 

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  

In this paper, two online path planning methods are presented for SURENA III humanoid robot by using model predictive control scheme. The methods are general control schemes which can generate the online motions for walking of a humanoid robot. For lowering computational costs a three dimensional linear inverted pendulum model is used instead of the full dynamical model of the robot. The generated trajectories are then used for computing the zero-moment point (ZMP) of the robot and the joint torques. The resulted joint torques of the two methods are compared to torques obtained from Genetic Algorithm (GA) path planning method presented for SURENA III humanoid robot in previous studies. The... 

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... 

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... 

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  

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...