Tommaso Cangemi

Convergence Analysis of Extended Kalman Filter for Sensorless Control of Induction Motor

This paper deals with convergence analysis of the extended Kalman filters (EKFs) for sensorless motion control systems with induction motor (IM). An EKF is tuned according to a six-order discrete-time model of the IM, affected by system and measurement noises, obtained by applying a first-order Euler discretization to a six-order continuous-time model. Some properties of the discrete-time model have been explored. Among these properties, the observability property is relevant, which leads to conditions that can be directly linked with the working conditions of the machine. Starting from these properties, the convergence of the stochastic state estimation process, in mean square sense, has been shown. The convergence is also explored with reference to the difference between the samples of the state of the continuous-time model and that estimated by the EKF. The results theoretically achieved have been also validated by means of experimental tests carried out on an IM prototype.

Identification and Robust Control of DC/DC Converter Hammerstein Model

This paper deals with model-based robust control of DC/DC power electronic converters. The converter is described by means of a Hammerstein model consisting of the nonlinear static characteristics of the converter and a linear time-invariant (LTI) uncertain model whose parameters depend on the actual duty-cycle operating range. This suggests that the controller be designed using robust control techniques. In view of applying robust control, identification of the earlier LTI models is performed by means of simulation experiments, carried out on a converter switching model implemented on MATLAB/SIMULINK environment. Internal model control (IMC) structure is employed for the controller design, but its implementation is performed using the equivalent feedback control structure. Comparison with some controllers designed starting from models that do not require identification steps is performed with the aim of showing the advantages connected to the availability of a suitable model, which describes the essential aspects of the behavior of the system, for control purposes. Comparison with a PI controller designed by means of phase margin assignment is carried out with the aim of justifying the use of more sophisticated control methods. Experimental results are also shown that aimed to prove the validity of the whole approach. Comparison of experimental and simulation results is also performed.

Hammerstein Model-Based Robust Control of DC/DC Converters

This paper deals with model-based robust control of DC/DC power electronic converters. The converter is modelled by means of its static characteristic and a few continuous-time linear and time-invariant (LTI) models corresponding to contiguous ranges of duty-cycle. The model appears as a Hammerstein model in which the values of the parameters of the LTI part depend on the actual duty-cycle operating range. This suggests to describe the converter as an uncertain system to be controlled using robust control techniques. Frequency domain approach is used for describing the nominal model and the uncertainty. In view of applying robust control, identification of the LTI models is performed by means of simulation experiments carried out on a converter switched model implemented on MATLAB-SIMULINK environment. Internal Model Control (IMC) structure is employed for the controller design, but its implementation is performed using the equivalent classical feedback control structure. Comparison with a PI controller, designed by means of phase margin assignment, shows the peculiarities of the proposed approach.

Speed and rotor flux estimation of induction motors via on-line adjusted Extended Kalman Filter

This paper deals with the estimation of speed and rotor flux of induction motors via extended Kalman filter (EKF) with on-line adjusting of the system noise covariance matrix. The predictor of EKF consists of a discrete time model obtained by means of a second order discretization of the original nonlinear model of the induction motor. In order to obtain accurate estimation of the above mentioned variables, the load torque is included in the state variables and then estimated. Three different system noise models are also illustrated and compared each other by simulations carried out in Matlab/Simulink environment. For one of these models, EKF is adjusted on-line by means of an additional PID-type control loop driven by the stator current error which gives updates of the system noise covariance matrix

Tracking control of network distributed systems in presence of variable time delay and loss of information

This paper deals with the control of network distributed systems which has been at the centre of interest in a wide area of research in the last few year. The control of such systems is very difficult because the communication networks inevitably introduce variable time delays and possible lost of samples. In particular, it is proposed an extension of the approach, derived in the contest of the optimal stochastic regulator problem to the remote tracking problem considering a distributed control system in which the signals from the transducers to the controller and from the controller to the actuator are transmitted through a communication network with variable delays and possible lost samples. The proposed approach uses timestamps, timeout and an one-step optimal predictor in the case of consecutive timeout. Simulation tests are carried out considering a first order system with the aim of validation of the proposed approach.

A Model-Based Control Strategy for Wind Turbines with Asynchronous Generator

In this paper a model based control methodology is described with reference to a wind turbine for production of alternative energy. The mathematical model of a 600 kW wind turbine is taken into account assuming a well defined profile of the rotor blades. A set of reference angular speeds of the asynchronous generator and a set of reference pitch angles of the blade wind turbine are obtained in order to maximize the extracted wind power and to reach equilibrium conditions between the wind-generated torque and the electric torque of the generator. Finally a PID model based controller is designed and then tested by means of simulation experiments.

Robust control of a Hammerstein model of DC/DC converters

This paper deals with the robust control of a Hammerstein mathematical model of DC/DC converters, consisting of the nonlinear static characteristics of the converter followed by one of a few number of linear time- invariant models which describe the converter in the useful working range. One of these models is assumed as the nominal model of the system and the remaining models are used for describing the model uncertainty. Nominal behaviour is assured using H-2 optimal control method, Robust stability and behaviour are assured by imposing H-infin specifications. The closed loop control system consisting of the converter Hammerstein model and the robust controller is analyzed by means of simulation experiments.