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.... 

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  

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... 

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... 

A comparison of three common controllers for stabilising a vertical take-off and landing air vehicle is presented. 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. The main problem here is control effectiveness at low flight speeds and transition manoeuvres because of the inherent instability. In the current study, a comprehensive nonlinear model is firstly developed for RMIT, followed by a validation process. Subsequently, linear, adaptive and model predictive controllers are designed in vertical flight. Based on the simulation results, it is shown that the linear... 

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 new model predictive controller is introduced to control a power unit process with three inputs and three outputs. This method is proposed to reduce the complexity of the required computation. In fact, the presented controller ensures achieving an acceptable performance in the presence of noise and disturbances and reduces the volume of calculations to control a complex and nonlinear boilerturbine process. The simulation results indicate that the implementation of the proposed controller requires less computing time while the performance degradation is not more than five percent  

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... 

The objective of this paper is to provide a stochastic framework to optimally avoid collision between a maneuverable spacecraft and a space object or debris. The satellite collision can be caused through a cyber-attack on a satellite by colliding it with a considered strategic satellite. Consequently, it is highly imperative that critical operational space assets be provided with autonomous collision avoidance systems. The collision avoidance methodology proposed in this paper will reduce the collision probability to an acceptable level and protect the satellite against indirect kinetic cyber-attacks initiated by designing optimal collision avoidance maneuvers using a stochastic model... 

This paper is concerned with a distributed model predictive control (DMPC) method that is based on a distributed optimisation method with two-level architecture for communication. Feasibility (constraints satisfaction by the approximated solution), convergence and optimality of this distributed optimisation method are mathematically proved. For an automated irrigation channel, the satisfactory performance of the proposed DMPC method in attenuation of the undesired upstream transient error propagation and amplification phenomenon is illustrated and compared with the performance of another DMPC method that exploits a single-level architecture for communication. It is illustrated that the DMPC... 

In this article, two adaptive model predictive controllers (AMPC) are applied to regulate the blood glucose in type 1 diabetic patients. The first controller is constructed based on a linear model, while the second one is designed by using a nonlinear Hammerstein model. The adaptive version of these control schemes is considered to make them more robust against model mismatches and external disturbances. The least squares method with forgetting factor is used to update the model parameters. For simulation study, two well-known mathematical models namely, Puckett and Hovorka which describe the dynamical behavior of patient's body have been selected. The performances and robustness of the... 

In this study, a new algorithm for explicit model predictive control of linear discrete-time systems subject to linear constraints, disturbances, uncertainties, and actuator faults is developed. The algorithm is based on dynamic programming, constraint rearrangement, multi-parametric programming, and a solution combination procedure. First of all, the dynamic programming is used to recast the problem as a multi-stage optimization problem. Afterwards, the constraints are rearranged in an innovative manner to take into account the worst admissible situation of unknown bounded disturbances, uncertainties, and actuator faults. Then, the explicit solution of the reformulated optimization problem... 

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... 

This paper seeks to provide a probabilistic control framework, named Probabilistic Multiple-Horizon Multiple-Model Predictive Control, for the soft and precise landing on an asteroid. The modified version of the Predictive Path Planning method is also introduced to generate a safe and smooth reference trajectory for landing. The Probabilistic Multiple-Horizon Multiple-Model Predictive Control is carried out in two phases; the offline phase to calculate the difference between models, and the online phase to use a probabilistic approach to track the reference trajectory. The difference of the dynamical models is utilized in the online control method to compensate the accuracy of the... 

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... 

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  

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... 

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...