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The paper is concerned with proving differential flatness of the three-phase voltage source converter (VSC) model and its resulting description in the Brunovsky (canonical) form. For the linearized canonical model of the converter a feedback controller is designed. At a second stage, a novel Kalman Filtering method (Derivative-free nonlinear Kalman Filtering) is introduced. The proposed Kalman Filter is redesigned as disturbance observer for estimating additive input disturbances to the VSC model. These estimated disturbance terms are finally used by a feedback controller that enables the DC output voltage track desirable setpoints. The efficiency of the proposed state estimation-based control scheme is tested through simulation experiments.

A control method is developed for the VSC-HVDC system, that is for an AC to DC voltage source converter connected to the electricity grid through a high voltage DC transmission line terminating at an inverter. By showing that the VSC-HVDC system is a differentially flat one, its transformation to the linear canonical form becomes possible. This is a global input–output linearization procedure that results into an equivalent dynamic model of the VSC-HVDC system for which the design of a state feedback controller becomes possible. Moreover, to estimate and compensate for modeling uncertainty terms and perturbation inputs exerted on the VSC-HVDC model it is proposed to include in the control loop a disturbance observer that is based on the Derivative-free nonlinear Kalman Filter. This filtering method makes use of the linearized equivalent model of the VSC-HVDC system and of an inverse transformation which is based on differential flatness theory and which finally provides estimates of the state variables of the initial nonlinear model. The performance of the proposed VSC-HVDC control scheme is evaluated through simulation experiments.

The use of three-phase voltage inverters (DC to AC converters) is frequently met in the electric power system, such as in the connection of photovoltaics with the rest of the grid. The paper proposes a nonlinear feedback control method for three-phase inverters, which is based on differential flatness theory and a new nonlinear filtering method under the name Derivative-free nonlinear Kalman Filter. First, it is shown that the inverter’s dynamic model is a differentially flat one. This means that all its state variables and the control inputs can be written as functions of a single algebraic variable which is the flat output. By exploiting differential flatness properties it is shown that the inverter’s model can be transformed to the linear canonical (Brunovsky’s) form. For the latter description the design of a state feedback controller becomes possible, e.g. using pole placement methods. Moreover, to estimate the non-measurable state variables of the linearized equivalent of the inverter, the Derivative-free nonlinear Kalman Filter is used. This consists of the Kalman Filter recursion applied on the linearized inverter’s model and of an inverse transformation that is based on differential flatness theory, which enables to compute estimates of the state variables of the initial nonlinear system. Furthermore, by redesigning the aforementioned filter as a disturbance observer it becomes also possible to estimate disturbance terms that affect the inverter and subsequently to compensate for them. The performance and disturbance rejection capability of the proposed nonlinear feedback control scheme is evaluated through simulation experiments.

This paper presents a model reference adaptive control method which is particularly appropriate in the control of electrical drives. The control algorithm has been developed taking into account both the control problems (such as the influence of a discrete control action on the behavior of a continuous system) and the hardware and software structures of the computing device, which is generally a multiple processor system in order to satisfy real-time; requirements. This approach allows the realization of simple and modular microprocessor-based adaptive controllers. To evaluate the effectiveness of the adaptive control method, the paper presents the results of simulations which have been carried out in the case of a D.C. drive and compares performances obtained with the adaptive controller and a P.I.D. regulator. To obtain from the simulations results which match with the actual behavior of the D.C. motor, its mathematical model takes into account the saturation of the magnetic core and the parameter variations.