ali karimpour - Academia.edu (original) (raw)

Papers by ali karimpour

Research paper thumbnail of Optimal unit commitment using equivalent linear minimum up and down time constraints

Research paper thumbnail of Singular Value Decomposition as a Measure for Control Structure Design in Power Systems

Electric Power Components and Systems, 2004

ABSTRACT In any control system it is important to determine the best system signal to be measured... more ABSTRACT In any control system it is important to determine the best system signal to be measured and the best actuator for the application of a controller. In addition, an important requirement in a multi-machine power system is the selection of the best location for the power system stabilizers. A number of techniques have been proposed to perform this selection. In this paper, a new measure is introduced and a relationship between the new measure and the former ones is presented. The proposed methodology is designed to use the system transfer function. Comparative results illustrate the effectiveness of the proposed technique.

Research paper thumbnail of Relative gain array and singular value decomposition in determination of PSS location

European Transactions on Electrical Power, 2005

In a multi-machine power system, it is important to determine the best location for the applicati... more In a multi-machine power system, it is important to determine the best location for the application of power system stabilizers. A number of techniques have been proposed to perform this selection. In this paper a new selection measure based on relative gain array and singular value decomposition is proposed. A comparison is made between the performance of the new measure and the older methods. The proposed methodology is based on the use of system transfer function. Copyright © 2005 John Wiley & Sons, Ltd.

Research paper thumbnail of Determination of PSS location based on singular value decomposition

International Journal of Electrical Power & Energy Systems, 2005

ABSTRACT In a multi-machine power system, it is important to determine the best location for the ... more ABSTRACT In a multi-machine power system, it is important to determine the best location for the application of power system stabilizers. A technique based on singular value decomposition to identify generators that contribute in each oscillation mode is introduced. Measures based on singular value decomposition for controllability and observability for every mode are described and the selection of the best location for the installation of the PSSs is done according to these measures. The proposed methodology is designed to use the system transfer function. Studies illustrate the effectiveness of the proposed technique.

Research paper thumbnail of Active insulin infusion using fuzzy-based closed-loop control

In this paper a closed-loop control algorithm is developed for blood glucose regulation in type I... more In this paper a closed-loop control algorithm is developed for blood glucose regulation in type I diabetes mellitus patients. The control technique incorporates expert knowledge about treatment of disease by using Mamdani-type fuzzy logic controller to stabilize the blood glucose concentration in normoglycaemic level of 70 mg/dl. Controller performance is assessed in terms of its ability to reject the multiple meal disturbances resulting from food intake, on an averaged nonlinear patient model. Robustness of the controller is tested over a group of patients with model parameter varying considerably from the average model. In addition, proposed controller provides the possibility of more accurate control of blood glucose level in the patient in spite of uncertainty in model and measurement noise. Simulation results show the superiority of the proposed scheme in terms of robustness to uncertainty in comparison with other researches.

Research paper thumbnail of An Automatic Insulin Infusion System based on H-Infinity Control Technique

This paper presents a control algorithm for a type I diabetes mellitus patient under an intensive... more This paper presents a control algorithm for a type I diabetes mellitus patient under an intensive insulin treatment. The control algorithm employs a robust Hinfin controller to regulate the blood glucose level. The control scheme is based on closed-loop feedback strategy to overcome the variability in the glucose-insulin dynamics from patient to patient. Controller performance is assessed in terms of its ability to track a normoglycemic set point (70 mg/dl) in response to multiple meal disturbances resulting from food intake. Simulations results show that resulted controller are robust to 90% parameter variations from mean value on nonlinear patient model. The proposed approach can successfully regulate the blood glucose level and represents more effective results in terms of robustness to uncertainty, in comparison with other existing algorithms.

Research paper thumbnail of Fast and Robust Detection of Epilepsy in Noisy EEG Signals Using Permutation Entropy

Research paper thumbnail of A computational tool for dispatching units in pool-based electricity markets

In this paper a new approach for solving mixed-integer nonlinear programming problems is presente... more In this paper a new approach for solving mixed-integer nonlinear programming problems is presented. The approach is named probabilistic search. The main idea is to search the feasible solution area probabilistically instead of randomly. The presented approach is used to determine the dispatch value of each generator in a pool-based electricity market. In this approach the ON and OFF units are determined using the probabilistic search and the generation value of each unit is determined using the linear programming. A software was developed based on the proposed approach for unit commitment. The software is used in the Iranian electricity power pool now.

Research paper thumbnail of Sufficient conditions for stabilizability of switched linear systems with sub-optimal convergence rate

In this paper, by use of the properties of matrix measure, a set of linear and quadratic conditio... more In this paper, by use of the properties of matrix measure, a set of linear and quadratic conditions is obtained which is sufficient for stabilizability of switched linear systems. These conditions are easily applicable because of their special form. So they are suitable to apply specially for higher order systems with several subsystems. Moreover, different system performances can also be achieved by using an appropriate objective function subject to the proposed conditions. In this way, an optimization problem is also introduced to stabilize the system with sub-optimal convergence rate. Finally a numerical example is used to show the effectiveness of the proposed approach.

Research paper thumbnail of Electricity price forecasting using a clustering approach

Research paper thumbnail of A novel adaptive neural sliding mode control for systems with unknown dynamics

In this paper, an adaptive neural sliding mode controller (ANSMC) is proposed as an asymptoticall... more In this paper, an adaptive neural sliding mode controller (ANSMC) is proposed as an asymptotically stable robust controller for a class of Control Affine Nonlinear Systems (CANSs) with unknown dynamics. In the proposed method a Control Affine Radial Basis function Network (CARBFN) is developed for online identification of CANSs. A recursive algorithm based on Extended Kalman Filter (EKF) is used for training of CARBFN to develop an adaptive model for CANSs with unknown and uncertain system dynamics to reduce the uncertainties to low values. Since the CARBFN model learns the system time-varying dynamics online, the ANSMC will compute an efficient control input adaptively. Due to high degree of robustness, the proposed controller can be widely used in real world applications. To demonstrate this efficiency, a robust control system is successfully designed for a chaotic Duffing forced oscillator system in the presence of unknown dynamics as well as the unknown oscillation disturbance which is not available for measurement.

Research paper thumbnail of Optimal Path Planning for Controllability of Switched Linear Systems Using Multilevel Constrained GA

In this paper, optimal switching signal as well as control input is designed for a general switch... more In this paper, optimal switching signal as well as control input is designed for a general switched linear system using multi-level constrained genetic algorithms (MLCGA). Given any two states in the controllable subspace, the proposed approach automatically finds optimal switching signal and control input which steer the system from initial state to final state in a desired feasible time. From optimization perspective, this problem has several linear constraints such as controllability condition and desired dwell time as well as desired final time. Also, the problem is mixed-variable when the switching indices must be integer. The objective function may be nonlinear, multi-modal and non-analytical. Generally the problem must be solved in two levels. At the bottom level, an optimal control input is found for a candidate switching signal and at the top level an optimizer searches for optimal switching signal. To solve this complex problem, we propose Multi-Level Constrained Genetic Algorithms (MLCGA) which can solve this problem efficiently. As it is demonstrated by a simulation example, using the proposed approach an optimal switching signal with desired dwell time as well as optimal control input in the presence of actuator saturation can be efficiently designed.

Research paper thumbnail of Optimal unit commitment using equivalent linear minimum up and down time constraints

Research paper thumbnail of Singular Value Decomposition as a Measure for Control Structure Design in Power Systems

Electric Power Components and Systems, 2004

ABSTRACT In any control system it is important to determine the best system signal to be measured... more ABSTRACT In any control system it is important to determine the best system signal to be measured and the best actuator for the application of a controller. In addition, an important requirement in a multi-machine power system is the selection of the best location for the power system stabilizers. A number of techniques have been proposed to perform this selection. In this paper, a new measure is introduced and a relationship between the new measure and the former ones is presented. The proposed methodology is designed to use the system transfer function. Comparative results illustrate the effectiveness of the proposed technique.

Research paper thumbnail of Relative gain array and singular value decomposition in determination of PSS location

European Transactions on Electrical Power, 2005

In a multi-machine power system, it is important to determine the best location for the applicati... more In a multi-machine power system, it is important to determine the best location for the application of power system stabilizers. A number of techniques have been proposed to perform this selection. In this paper a new selection measure based on relative gain array and singular value decomposition is proposed. A comparison is made between the performance of the new measure and the older methods. The proposed methodology is based on the use of system transfer function. Copyright © 2005 John Wiley & Sons, Ltd.

Research paper thumbnail of Determination of PSS location based on singular value decomposition

International Journal of Electrical Power & Energy Systems, 2005

ABSTRACT In a multi-machine power system, it is important to determine the best location for the ... more ABSTRACT In a multi-machine power system, it is important to determine the best location for the application of power system stabilizers. A technique based on singular value decomposition to identify generators that contribute in each oscillation mode is introduced. Measures based on singular value decomposition for controllability and observability for every mode are described and the selection of the best location for the installation of the PSSs is done according to these measures. The proposed methodology is designed to use the system transfer function. Studies illustrate the effectiveness of the proposed technique.

Research paper thumbnail of Active insulin infusion using fuzzy-based closed-loop control

In this paper a closed-loop control algorithm is developed for blood glucose regulation in type I... more In this paper a closed-loop control algorithm is developed for blood glucose regulation in type I diabetes mellitus patients. The control technique incorporates expert knowledge about treatment of disease by using Mamdani-type fuzzy logic controller to stabilize the blood glucose concentration in normoglycaemic level of 70 mg/dl. Controller performance is assessed in terms of its ability to reject the multiple meal disturbances resulting from food intake, on an averaged nonlinear patient model. Robustness of the controller is tested over a group of patients with model parameter varying considerably from the average model. In addition, proposed controller provides the possibility of more accurate control of blood glucose level in the patient in spite of uncertainty in model and measurement noise. Simulation results show the superiority of the proposed scheme in terms of robustness to uncertainty in comparison with other researches.

Research paper thumbnail of An Automatic Insulin Infusion System based on H-Infinity Control Technique

This paper presents a control algorithm for a type I diabetes mellitus patient under an intensive... more This paper presents a control algorithm for a type I diabetes mellitus patient under an intensive insulin treatment. The control algorithm employs a robust Hinfin controller to regulate the blood glucose level. The control scheme is based on closed-loop feedback strategy to overcome the variability in the glucose-insulin dynamics from patient to patient. Controller performance is assessed in terms of its ability to track a normoglycemic set point (70 mg/dl) in response to multiple meal disturbances resulting from food intake. Simulations results show that resulted controller are robust to 90% parameter variations from mean value on nonlinear patient model. The proposed approach can successfully regulate the blood glucose level and represents more effective results in terms of robustness to uncertainty, in comparison with other existing algorithms.

Research paper thumbnail of Fast and Robust Detection of Epilepsy in Noisy EEG Signals Using Permutation Entropy

Research paper thumbnail of A computational tool for dispatching units in pool-based electricity markets

In this paper a new approach for solving mixed-integer nonlinear programming problems is presente... more In this paper a new approach for solving mixed-integer nonlinear programming problems is presented. The approach is named probabilistic search. The main idea is to search the feasible solution area probabilistically instead of randomly. The presented approach is used to determine the dispatch value of each generator in a pool-based electricity market. In this approach the ON and OFF units are determined using the probabilistic search and the generation value of each unit is determined using the linear programming. A software was developed based on the proposed approach for unit commitment. The software is used in the Iranian electricity power pool now.

Research paper thumbnail of Sufficient conditions for stabilizability of switched linear systems with sub-optimal convergence rate

In this paper, by use of the properties of matrix measure, a set of linear and quadratic conditio... more In this paper, by use of the properties of matrix measure, a set of linear and quadratic conditions is obtained which is sufficient for stabilizability of switched linear systems. These conditions are easily applicable because of their special form. So they are suitable to apply specially for higher order systems with several subsystems. Moreover, different system performances can also be achieved by using an appropriate objective function subject to the proposed conditions. In this way, an optimization problem is also introduced to stabilize the system with sub-optimal convergence rate. Finally a numerical example is used to show the effectiveness of the proposed approach.

Research paper thumbnail of Electricity price forecasting using a clustering approach

Research paper thumbnail of A novel adaptive neural sliding mode control for systems with unknown dynamics

In this paper, an adaptive neural sliding mode controller (ANSMC) is proposed as an asymptoticall... more In this paper, an adaptive neural sliding mode controller (ANSMC) is proposed as an asymptotically stable robust controller for a class of Control Affine Nonlinear Systems (CANSs) with unknown dynamics. In the proposed method a Control Affine Radial Basis function Network (CARBFN) is developed for online identification of CANSs. A recursive algorithm based on Extended Kalman Filter (EKF) is used for training of CARBFN to develop an adaptive model for CANSs with unknown and uncertain system dynamics to reduce the uncertainties to low values. Since the CARBFN model learns the system time-varying dynamics online, the ANSMC will compute an efficient control input adaptively. Due to high degree of robustness, the proposed controller can be widely used in real world applications. To demonstrate this efficiency, a robust control system is successfully designed for a chaotic Duffing forced oscillator system in the presence of unknown dynamics as well as the unknown oscillation disturbance which is not available for measurement.

Research paper thumbnail of Optimal Path Planning for Controllability of Switched Linear Systems Using Multilevel Constrained GA

In this paper, optimal switching signal as well as control input is designed for a general switch... more In this paper, optimal switching signal as well as control input is designed for a general switched linear system using multi-level constrained genetic algorithms (MLCGA). Given any two states in the controllable subspace, the proposed approach automatically finds optimal switching signal and control input which steer the system from initial state to final state in a desired feasible time. From optimization perspective, this problem has several linear constraints such as controllability condition and desired dwell time as well as desired final time. Also, the problem is mixed-variable when the switching indices must be integer. The objective function may be nonlinear, multi-modal and non-analytical. Generally the problem must be solved in two levels. At the bottom level, an optimal control input is found for a candidate switching signal and at the top level an optimizer searches for optimal switching signal. To solve this complex problem, we propose Multi-Level Constrained Genetic Algorithms (MLCGA) which can solve this problem efficiently. As it is demonstrated by a simulation example, using the proposed approach an optimal switching signal with desired dwell time as well as optimal control input in the presence of actuator saturation can be efficiently designed.