Sharif Digital Repository

Because of the advances in power electronics, DC-based power systems, have been used in industrial applications such as data centers [. 18], space applications [. 10], aircraft [. 12], offshore wind farms, electric vehicles [. 56], DC home systems [. 5, 20], and high-voltage DC transmission systems. To provide such sensitive loads with more reliability, efficiency, and controllability for future power systems, AC microgrid and more recently DC microgrid and smart-grid technologies have been employed [. 5-9].To obtain stable and optimal operation in DC power systems (microgrids), proper load sharing among different energy units and acceptable voltage regulation across the microgrid is... 

Ultrasonic motors (USM) possess heavy nonlinear, and load dependent characteristics such as dead-zone and saturation reverse effects, which vary with driving conditions. These properties have made the position/velocity control of USM a difficult and challenging task. In this paper, a generalized model predictive (GPC) controller for precise USM position control is suggested. Simulation results indicate improved performance of the motor for both set point tracking and disturbance rejection. Since the motor and the controller both are of type one, the applied saturation would cause in wind up phenomenon. This drawback is removed by implementing the Quadratic GPC controller. © 2004 IEEE  

Three different controllers, i.e., active controller, nonlinear controller, and active sliding mode controller are designed and examined for the synchronization of pairs of three different chaotic systems, i.e., Chen, Lü, and Lorenz. The synchronizing methods are then compared from various point of views including synchronizing error variance, convergence time, control effort, maximum and minimum values of the control signal. Our results indicate that the nonlinear controller synchronizes pairs of the different chaotic systems generally better than two other controllers according to the defined criteria. © 2006 Elsevier B.V. All rights reserved  

The robust fuzzy multimodel control as a potential tool to control the complex systems is presented in this paper. The main idea in multimodel controllers is to identify the best model of system at any instant and apply the appropriate control input to it. Classical multimodel controller works based on switching and tuning, while fuzzy logic is used in construction of fuzzy multimodel controller. The basic control signal for each model is calculated using the sliding mode control and the final control input is inferred as the weighted average of the local control inputs. A new algorithm is proposed in order to use the fuzzy multimodel control for time variant linear systems. To show the... 

Direct yaw moment control (DYMC) is one of the most effective method that improves not only the directional stability of the vehicles but also their road handling and controllability to a great extent. In this method by developing a difference in the longitudinal force (often the braking force) on two sides of the vehicle, an external stabilizing yaw moment is applied to the vehicle. In this study, an optimal control law for DYMC is proposed. The control law is based on the yaw rate, the lateral velocity feedback, and the steering angle feedforward. Simulation results obtained indicate that considerable improvement in the vehicle dynamic behavior can be achieved when the optimal yaw moment... 

In this paper, a new control strategy for optimal attitude tracking control of a multivariable satellite system has been presented. The approach is based on Radial Basis Function Neural Network (RBFNN) and classical PD Controller for its initial stabilization. It is shown how the network can be employed as a multivariable self- organizing and self learning controller in conjunction with a PD controller for attitude control of a satellite. By using four reaction wheels and quaternion for kinematics representation, the attitude dynamics of the satellite has been presented. In contrast to the previous classical approaches, it is shown how this controller can be carried out in an on-line manner... 

PID controllers have been used for many years in industry and if a controller is well tuned, its performance is acceptable for many industrial processes. When the operating point is changed, due to nonlinear behavior of most processes, the controller should be retuned. In this regard, several self-tuning PID controllers are proposed in the literature. In this paper, four such algorithms are compared through simulation and experimental studies. In the simulation study, the effects of factors such as process pole locations, non-minimum phase behavior and model changes on the performance of the schemes are investigated. Simulation and experimental results demonstrate that one of the schemes... 

Control Performance Assessment (CPA) and tuning of PID controllers are studied in this paper. We propose a framework for systematic analysis of the tradeoff between the structural complexity of the controller and its performance. As the measure of the controller performance, an LQG based index is used. The problem is augmented with an additional term which forces sparsity on the complexity of a decentralized PID controller. The desired complexity is controlled via a weighting parameter which determines the cost of each additional element (i.e., P, I, and D terms). The result is a decentralized multivariable PID controller in which the complexity of each loop controller is optimized such that... 

Control Performance Assessment (CPA) and tuning of PID controllers are studied in this paper. We propose a framework for systematic analysis of the tradeoff between the structural complexity of the controller and its performance. As the measure of the controller performance, an LQG based index is used. The problem is augmented with an additional term which forces sparsity on the complexity of a decentralized PID controller. The desired complexity is controlled via a weighting parameter which determines the cost of each additional element (i.e., P, I, and D terms). The result is a decentralized multivariable PID controller in which the complexity of each loop controller is optimized such that... 

Control input energy efficiency is an important issue which should be considered in designing any control system. Due to the importance of this subject, in the present paper fractional order control systems are studied in the viewpoint of control input energy efficiency. In this study, the divergent terms of the control input energy function of fractional order control systems are obtained. It is shown that these terms have a significant role in the amount of the energy injected to the plant by the controller. Finally, two examples are provided to demonstrate the usefulness of the presented results in the paper  

A nonlinear predictive model controller was designed to control the temperature of a batch polymerization of methyl methacrylate. Using the mechanistic model of the polymerization, a state space model was derived and converted to transfer function model. The coefficients of the transfer function were calculated along the selected temperature trajectory by sequential linearization. 140 operation points were resulted. Model validation showed model ability in process dynamic description. Consequently, DMC algorithm was applied and one objective function was optimized. Results of control loop simulation shows a high precision ability of this algorithm in comparison to classic methods  

A fuzzy controller has been suggested for attitude control of magnetic actuated satellites in order to calculate the desired mechanical torque based on the attitude error including error in the angles and their rates. The problem of selecting proper magnetic dipole based on the known desired mechanical torque has been investigated, two different methods for the purpose has been suggested and the performance of the attained fuzzy magnetic attitude controllers has been shown under two different simulated conditions. © 2009 IEEE  

Most multivariate quality control procedures evaluate the in-control or out-of-control condition based upon an overall statistic, like Hotelling's T2. Although T2 is optimal for finding a general shift in mean vectors, it is not optimal for shifts that occur for some subset of variables. This introduces a persistent problem in multivariate control charts, namely the interpretation of a signal that often discourages practitioners in applying them. In this paper, we propose an artificial neural network based model to diagnose faults in out-of-control conditions and to help identify aberrant variables when Shewhart-type multivariate control charts based on Hotelling's T2 are used. The results... 

This paper proposes a scheme for computing the stable regions from which the parameters of fractional-order proportional-integral (PI) and proportional-derivative (PD) controllers can be selected. In particular, a previously investigated method for plotting the stability regions of PI λ and PDμ controllers is extended to their integer-order approximations. Next, the two stability regions are compared and their overlapping sections, referred to as the implementable stability region, are derived. In order for the final closed-loop system to be stable, the designer must choose the controller parameters from the overlapping section of the two stability regions. Simulation results for two example... 

In this paper, two fractional-order linear controllers are proposed to stabilize unstable equilibrium points of a chaotic fractional-order system. The first controller is based on the dynamic output feedback control idea and requires detectability of the linearized model of the fractional-order system on the equilibrium point. The second controller is a dynamic state feedback controller and requires observability of the linearized model. In both considered cases, the stabilizability of the model is assumed. The number of inner states in the second controller is one and therefore its structure is much simpler than the first controller. To illustrate the applicability, these controllers are... 

During the milling process, self-excited vibration or chatter adversely affects tool life, surface quality and productivity rate. In this paper, nonlinear cutting forces of milling process are considered as a function of chip thickness with a complete third order polynomial (instead of the common linear dependency). An optimal control strategy is developed for chatter suppression of the system described through nonlinear delay differential equations. Counterbalance forces exerted by actuators in x and y directions are the control inputs. For optimal control problem, an appropriate performance index is defined such that the regenerative chatter is suppressed while control efforts are... 

This study presents a comprehensive control framework to ensure desired loading margin (LM) while minimising the corresponding control cost. The proposed framework is divided into corrective control (CC) and preventive control (PC) subproblems. The CC subproblem deals with the condition that a power system encounters voltage instability as a result of severe contingencies. This control is merely devised to restore system stability. The PC subproblem is brought up when the system operates in a stable region but its LM is insufficient. In this manner, the system-operating point is changed such that the desired LM is achieved. One of the features of the proposed methodology is to consider... 

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 discusses a novel and detailed approach for dynamic modeling and control design of a coupled hydraulic dynamometer/turbine-engine system. This study presents a comprehensive model to reveal the coupling effects and an adaptive multiobjective controller to ensure a safe and reliable operation. A fuzzy-based strategy is employed to dynamically adjust the controller gains to keep the state variables and power loading within the desirable operational limits. This approach uses the dynamometer inlet, outlet, and trim valves as well as the turbine fuel flow rate and bleed valve in order to control the system performance during the engine testing process. The proposed fuzzy control... 

Rhythmic activities such as swimming stroke in the human body are learnable through conscious trainings. Inspiringly, the main objective of this study is to develop a control framework to reproduce the described functionality in the imitating robots. To do so, a two layer supervisory controller is proposed. The high-level controller, which acts as the conscious controller during trainings, is a supervisory dynamic-based controller and uses all system sensory data to generate stable rhythmic movements. On the other hand, the low-level controller in this structure is a distributed trajectory-based controller network. Each node in this network is an oscillatory dynamical system which has the...