Sharif Digital Repository

In this paper a combination of Kalman filter and feedback linearization methods is used to present a controller-identifier system for synchronizing two different chaotic systems. The drive system has some unknown parameters which are supposed to have linear form within its dynamic equation. An identifier based on Kalman filter approach is designed to estimate the unknown parameters of the drive system, and simultaneously a feedback linearizing controller is used to synchronize the chaotic behavior of the response system with the drive chaotic system. The method proposed in this paper is applied to the Lure' and the Genesio dynamic systems as the drive and response chaotic systems. The... 

In this paper, an adaptive multi-model controller based on CMAC neural networks (AMNNC) is developed for uncertain nonlinear MIMO systems. AMNNC is a kind of adaptive feedback linearizing controller where nonlinearity terms are approximated with multiple neural networks. The weighted sum of the multiple neural networks is used to approximate the system nonlinearity for a given task. The proposed control scheme is applied to control a robotic manipulator, where some varying tasks are repeated but information on the load is not defined; it is unknown and varying. It is shown how the proposed controller is effective because of its capability to memorize the control skill for each task using... 

Boiler–turbine units may show quasiperiodic behavior due to the bifurcation occurrence in the presence of harmonic disturbances. In this study, a multi-input–multi-output nonlinear dynamic model of a boiler–turbine unit is considered. Drum pressure, electric output, and fluid density are the state variables and adjusted at the desired values by manipulation of the input variables. Control inputs are the valve positions for fuel, steam and feed-water flow rates. To improve the quasiperiodic behavior of the system and bifurcation control in tracking problem, two controllers are designed: feedback linearization control and nonlinear sliding mode control (SMC). The feedback linearization... 

Reducing the renewable energy costs is necessary for the competition with the fossil energies and control strategies have great impact on the efficiency of wind machines. In the wind turbine industry, a practical approach is to maximize the energy capture of a wind machine by optimizing the power coefficient in the under-rated situations. In this paper, with the main objective of maximizing the energy capture in the second region, four different control strategies are compared in the presence of uncertainties. The proposed control methods are compared based on their power capture and robustness against probable uncertainties in the structural and environmental parameters. A two-mass... 

This paper presents the feedback linearization control of HIV infection. A multi-input multi-output (MIMO) dynamic nonlinear HIV infection model for this purpose has been used. For this purpose, three widely used drugs are considered. A Luenberger-like nonlinear observer (LNO) is designed for estimation of unavailable states. To minimize the side effects of drugs, the concentration of ZDV which has the highest side effect is fixed to a minimum value and the external controllers parameters are obtained by maximizing an objective function. In the control design, limitations on drug consumption and unavailability of all states are taken into account. The closed-loop stability has been... 

A globally convergent algorithm for synthesis of sparse optimal state feedback (SOSF) control of linear time-invariant (LTI) systems is proposed. This problem is known to be NP-hard due to its combinatorial nature. A structured H2 norm controller design problem is intrinsically non-convex, even if a fixed structure is known in advance. The proposed algorithm minimizes the H2 norm performance index, simultaneously regularizes the sparsity of the control structure using the norm. It guarantees that the solution converges to a stationary point of the original problem. The algorithm is implemented using Linear Matrix Inequalities (LMIs) which are efficient, reliable and extendable to other... 

In this paper, the swing-up problem of the Furuta pendulum has been solved by introducing a new combined method based on the frequency response, and the sliding mode method. Furthermore, a trajectory tracking controller has been introduced and applied to the Furuta pendulum; which the pendulum remained regulated at the upward position, while the arm tracks a desired time-varying trajectory. The hierarchical sliding mode control (HSMC) approach has been employed to achieve the mentioned goals. The Furuta system is made up of two subsystems. Based on this physical structure, the hierarchical structure of the sliding surfaces is designed as follows: first, the sliding surface of each subsystem... 

Reducing the renewable energy costs is necessary for the competition with the fossil energies and control strategies have great impact on the efficiency of wind machines. In the wind turbine industry, a practical approach is to maximize the energy capture of a wind machine by optimizing the power coefficient in the under-rated situations. In this paper, with the main objective of maximizing the energy capture in the second region, four different control strategies are compared in the presence of uncertainties. The proposed control methods are compared based on their power capture and robustness against probable uncertainties in the structural and environmental parameters. A two-mass... 

In this paper, dynamic modelling and control of WindPACT 1.5 MW wind turbine in Region 2 for extracting the maximum energy from wind is investigated (where the wind velocity is greater than ‘cut in’ and below ‘rated’ wind speeds). In this region, the generator torque must regulate the rotor speed in its optimal value while the blade pitch angle is considered constant in its optimal value. To achieve a more accurate model, wind turbine is modeled as an electromechanical system with two masses dynamics. A new method based on adaptive neuro fuzzy inference system (ANFIS) is considered for wind speed estimation; where rotor speed, output power and pitch angle are inputs of such system and... 

This paper presents an input/output feedback linearization control strategy for the three-level three-phase neutral-point-clamped rectifier using it's dual Lagrangian modeling, which is obtained based on the superposition law, the load current and The Euler-Lagrange description of the rectifier. The load current can be given in two forms: 1. the load current involving the current of capacitor C1 and 2. The load current involving the current of capacitor C2 Applying the obtained load current to the Euler-Lagrange parameters of the rectifier, two nonlinear models of the system are derived. Also two the power-balance equations between the input and output sides are obtained by considering the...