Sharif Digital Repository

In economic design of profiles, parameters of a profile are determined such that the total implementation cost is minimized. These parameters consist of the number of set points, n, the interval between two successive sampling, h, and the parameters of a control chart used for monitoring. In this paper, the Lorenzen-Vance cost function is extended to model the costs associated with implementing profiles. The in-control and the out-of-control average run lengths, ARL0 and ARL1, respectively, are used as two statistical measures to evaluate the statistical performances of the proposed model. A genetic algorithm (GA) is developed for solving both the economic and the economic-statistical... 

In this paper an approach based on system identification is used for fault detection in a nuclear reactor. A continuous-time Extended Kalman Filter (EKF) is presented, which allows the parameters of the nonlinear system to be estimated. Also a fault tolerant control system is designed for the nuclear reactor during power changes operation. The proposed controller is an adaptive critic-based neuro-fuzzy controller. Performance of the controller in terms of transient response and robustness against failures is very good and considerable  

In this paper, two different hybrid intelligent systems are applied to develop practical soft identifiers for modeling the tool-tissue force as well as the resulted maximum local stress in laparoscopic surgery. To conduct the system identification process, a 2D model of an in vivo porcine liver was built for different probing tasks. Based on the simulation, three different geometric features, i.e. maximum deformation angle, maximum deformation depth and width of displacement constraint of the reconstructed shape of the deformed body are extracted. Thereafter, two different fuzzy inference paradigms are proposed for the identification task. The first identifier is an adaptive co-evolutionary... 

Most of industrial applications of statistical process control involve more than one quality characteristics to be monitored. These characteristics are usually correlated, causing challenges for the monitoring methods. These challenges are resolved using multivariate quality control charts that have been widely developed in recent years. Nonetheless, multivariate process monitoring methods encounter a problem when the quality characteristics are of the attribute type and follow nonnormal distributions such as multivariate binomial or multivariate Poisson. Since the data analysis in the latter case is not as easy as the normal case, more complexities are involved to monitor multiattribute... 

This study deals with a generalised version of lead/lag compensators known as fractional-order lead/lag compensators. Exact and simple formulas are found for designing this introduced type of fractional-order compensators in order to provide the required magnitude and phase at a given frequency. Also, the region in the phase-magnitude plane, which is accessible by these compensators, is analytically found. Moreover, numerical examples and experimental results are presented to show the applicability of the achievements of this study in control system design  

This paper presents a robust decentralized proportional-integral (PI) control design as a solution of the load frequency control (LFC) in a multi-area power system. In the proposed methodology, the system robustness margin and transient performance are optimized simultaneously to achieve the optimum PI controller parameters. The Kharitonov's theorem is used to determine the robustness margin, i.e., the maximal uncertainty bounds under which the stable performance of the power system is guaranteed. The integral time square error (ITSE) is applied to quantify the transient performance of the LFC system. In order to tune the PI gains, the control objective function is optimized using the... 

A fractional order PID controller is designed to stabilize fractional delay systems with commensurate orders and multiple commensurate delays, where the time delays in the system may belong to several distinct intervals. Moreover, the controller parameters should belong to given intervals. In order to stabilize the system, the D-subdivision method is employed to choose the stabilizing set of the controller parameters from their available values. Furthermore, the nearest values of the obtained stabilizing set to their mean values are selected as the controller parameters so that a non-fragile controller is concluded. Two numerical examples evaluate the proposed control design method  

The main contribution of this paper is to present a new set of approximate analytical solutions for the parameters of a photovoltaic (PV) five-parameter double-diode model that can be used as initial values for the numerical solutions based on the Newton-Raphson method. The proposed formulations are developed based on only the limited information given by the PV manufacturers, i.e., the open-circuit voltage (V), the short circuit current (I), and the current and voltage at the maximum power point (Im). Compared with the existing techniques that require the entire experimental I-V curve or additional information such as the slope of the I-V curves of the open circuit and the short circuit... 

The design and implementation of linear and nonlinear control methods for a three-pole active magnetic bearing (AMB) is presented in this paper. It is shown that the system has nearly linear dynamics by adding a bias to coil currents. A decentralized PID feedback law and an integral sliding mode controller are proposed and the unknown state variables of the system are estimated by the Kalman filter. The optimal gains of the linear controller are determined by the LQG technique. To evaluate the effectiveness of the proposed controllers, they are implemented on an experimental setup. The experimental results show that the proposed methods can effectively stabilize the three-pole AMB. The... 

Dictionary learning (DL) for sparse representation has been widely investigated during the last decade. A DL algorithm uses a training data set to learn a set of basis functions over which all training signals can be sparsely represented. In practice, training signals may contain a few outlier data, whose structures differ from those of the clean training set. The presence of these unpleasant data may heavily affect the learning performance of a DL algorithm. In this paper we propose a robust-to-outlier formulation of the DL problem. We then present an algorithm for solving the resulting problem. Experimental results on both synthetic data and image denoising demonstrate the promising... 

The practicality of robust model predictive control of systems with model uncertainties depends on the time consumed for solving a defined optimization problem. This paper presents a method for the computational complexity reduction in a robust model predictive control. First a scaled state vector is defined such that the objective function contours in the defined optimization problem become vertical or horizontal ellipses or circles, and then the control input is determined at each sampling time as a state feedback that minimizes the infinite horizon objective function by solving some linear matrix inequalities. The simulation results show that the number of iterations to solve the problem... 

Optimal control of large-scale uncertain dynamic systems with time delays in states is considered in this paper. For this purpose, a two-level strategy is proposed to decompose the large-scale system into several interconnected subsystems at the first level. Then optimal control inputs are obtained by minimization of convex performance indices in presence of uncertainties, in the form of states and interactions feedback. The solution is achieved by bounded data uncertainty problems, where the uncertainties are only needed to be bounded and it is not required to satisfy the so-called 'matching conditions'. At the second level, a simple substitution-type interaction prediction method is used... 

In this paper, we have developed a production planning and marketing model in unreliable flexible manufacturing systems with inconstant demand rate that its rate depends on the level of advertisement on that product. The proposed model is more realistic and useful from a practical point of view. The flexible manufacturing system is composed of two machines that produce a single product. Markovian models frequently have been used in modeling a wide variety of real-world systems under uncertainties. Therefore, in this paper, the inventory balance equation is represented by a continuous-time model with Markov jump process to take into account machines breakdown. The objective is to minimize the... 

The objective of this paper is to expand the concept of hybrid modeling and control in power electronics area. A new precise and non-averaged model of a DC-DC boost converter is developed on the basis of Mixed Logical Dynamical (MLD) systems, and the approach is extended by a new version of such systems which is called as Extended Mixed Logical Dynamical (EMLD) systems in this paper. A Model Predictive Controller (MPC) based on the Mixed Integer Quadratic Programming (MIQP) is designed for the MLD and EMLD models of the DC-DC boost converter considering all possible dynamics in Continuous and Discontinuous Conduction Modes of operations (CCM-DCM). The simulation results show the satisfactory... 

In this paper, modified genetic algorithm has been used as a simultaneous optimizer of recurrent neural network to improve identification and modeling of aircraft nonlinear dynamics. Weighted connections, network architecture, and learning rules are features that play important roles in the quality of neural networks training and their generalizability in order to model nonlinear systems. Therefore, the main focus of this paper is to apply appropriate evolutionary methods in order to simultaneously optimize the parameters of neural networks for the improvement identification and modeling of aircraft nonlinear dynamics. To validate this study, the results have been compared with the recorded... 

Exoskeletons are robotic devices which are used in power augmentation and rehabilitation robotics. The exoskeleton control system is one of the most challenging issues in humanrobot interaction systems. Although the rehabilitation robotic control methods are well studied, little research has been conducted on power augmenting control methods. This paper presents a novel idea in control system of exoskeletons for load carrying and power augmentation. Here, the desired linear velocity of the exoskeleton in interaction points are taken to be proportional to interaction force at the corresponding location. The introduced control method is merely based on kinematic model and thus easy to... 

This paper presents closed loop simulation of a CMOS-MEMS force sensor for biomedical applications employing an optimal proportional-integral-derivative controller. Since the dynamic behavior of the sensor under investigation is nonlinear the iterative feedback tuning approach was proposed for optimal gains tuning of the proposed controller. Simulation results presented in this research illustrate that the proposed controller suppresses the undesired in-plane vibration induced by environment or gripper 40 times faster than the nonlinear controller proposed in the literature. To suppress the maximum input disturbance the maximum voltage was approximately 18 V which was less than the pull-in... 

A methodology is developed for the design of optimum viscous fluid passive energy dissipation systems using pole assignment active control algorithm. In this method, the procedure to assign the new structural poles is slightly modified such that the resulting structural properties (i.e., the optimum locations of system poles) can be achieved merely by modification of structural stiffness and addition of a passive control system. A combination of stiffness reduction and increase of damping is utilized to reduce both acceleration and displacement response. It is shown that the control systems designed using this method provide structural performances slightly better than or close to those of... 

This paper deals with irrational transfer functions having monotonic nondecreasing step responses. Firstly, some results on the monotonicity of step responses in irrational transfer functions describing fractional- or distributed-order systems are presented. Then, some conditions guaranteeing the existence of monotonic nondecreasing step responses in more general forms of irrational transfer functions are found. Various examples are brought to show the usefulness of the obtained results in time response analysis of fractional/distributed-order systems. The achievements of the paper can be used in the design of control systems having monotonic step responses  

The electric power steering (EPS) system was developed and the steer-by-wire (SBW) system achieves the purposes of EPS. The advantages of SBW are packaging flexibility, advanced vehicle control system, and superior performance. No mechanical linkage exists between the steering gear and steering column in the SBW system. The steering wheel and front-wheel steering can be controlled independently. The SBW system consists of two motors controlled by an electronic control unit (ECU). One motor is in the steering wheel and develops the steering feel of the driver and the other motor is in the steering linkage and improves vehicle maneuverability and stability. Moreover, the active front steering...