Nicolai Christov

Optimal control of variable speed wind turbines

This paper proposes a MIMO linear quadratic regulator (LQR) controller designed for a horizontal variable speed wind turbine with focus on the operating range referring to the above rated wind speeds. The operating conditions of wind turbines make them subject to fluctuating loads that create fatigue and lead to damage. Alleviating these loads would reduce the needed materials, and increase the lifespan and the quality of the produced energy. The optimality of the entire system is defined in relation with the trade-off between the wind energy conversion maximization and the minimization of the fatigue in the mechanical structure. The solution of a control using an LQR regulator is presented. The performances of the optimal control are assessed and discussed by means of a set of simulations.

Parameter and State Estimation of an Anaerobic Digestion Model in Laboratory and Pilot-Scale Conditions

Abstract This work considers the parameter and state estimation of a low-order model of anaerobic digestion of cattle dung. First, on the basis of a previously identified parameter set, partial parameter estimation with laboratory experimental data is performed. A modern numerical sensitivity analysis, to our knowledge not used for microbial biotechnology models so far, is a successful part of the estimation procedure. Second, the estimation results are validated with pilot-scale experimental data and can be considered satisfactory. Third, state estimation of the main AD variables is made via H-infinity filtering.

LQG control of horizontal wind turbines for blades and tower loads alleviation

Abstract The paper deals with the LQG controller design optimizing the amount of power produced by two bladed horizontal variable speed wind turbines. The proposed controller ensures not only an optimal operation of turbines but also enables a compromise with the minimization of the blade oscillations and with the tower bending tendency.

Recursive Model Free Controller for trajectory tracking of MIMO nonlinear systems

This paper deals with a new Recursive Model Free Controller for trajectory tracking of MIMO nonlinear systems whose structure is simple and dose not depend on any physical model. The proposed controller is based on the theory of a particular class of hybrid systems, called Piecewise Continuous Systems, which are characterized by autonomous switchings and controlled impulses. The effectiveness and robustness of the proposed controller is experimented on a three tank system.

Modelling and Composed Recursive Model Free Control for the Anaerobic Digestion Process

This paper presents a modelling and new composite recursive model free controller for trajectory tracking and disturbance compensation for the Anaerobic Digestion Process of cattle dung. The used model is on the basis of a fifth-order continuous anaerobic digestion model. And the proposed controller comprises a recursive model free controller based stabilization component and a time delay control based compensation component with recursive calculation structure which does not require any knowledge of the model parameters. Computer simulation examples illustrate the performance and robustness of the proposed approach.

Robust unknown input observer design for state estimation and fault detection using linear parameter varying model

This paper proposes a robust unknown input observer for state estimation and fault detection using linear parameter varying model. Since the disturbance and actuator fault is mixed together in the physical system, it is difficult to isolate the fault from the disturbance. Using the state transforation, the estimation of the original state becomes to associate with the transform state. By solving the linear matrix inequalities (LMIs)and linear matrix equalities (LMEs), the parameters of the UIO can be obtained. The convergence of the UIO is also analysed by the Layapunov theory. Finally, a wind turbine system with disturbance and actuator fault is tested for the proposed method. From the simulations, it demonstrates the effectiveness and performances of the proposed method.

Energy management of photovoltaic systems using fuel cells

Renewable energy generators show an accelerated growth both production wise, as well as in research fields. Focusing only on photovoltaic panels, the generated energy has the disadvantage of being strongly oscillatory in evolution. The classical solution is to create a network between photovoltaic farms spanning on large distances, in order to share the total energy before sending it to the clients. A solution that was recently proposed is to use hydrogen in order to store the energy surplus. Fuel Cells (FCs) represent energy generators whose energy vector is usually hydrogen. These have already started the transition from the laboratory context towards commercialization. Due to their high energy density, as well as their theoretical infinite storage capacity through hydrogen, configurations based on electrolyzers and FCs are seen as high potential storage systems, both for vehicle and for stationary applications. Therefore, a study on such distributed control systems is of high importance. This paper analyzes existing solutions, with emphasis on a particular case where a supervisory system is developed and tested in a specialized simulation software.

Composed Adaptive Control for a second-order nonlinear model of a biotechnological process

This paper presents a new Composed Adaptive Controller (CAC) for trajectory tracking of a methane fermentation process in stirred tank bio-reactors. The referred biotechnological process is described by a second-order non-linear model based one-stage reaction scheme. The proposed controller comprises an Algebraic Differential Estimation (ADE) based compensation component and a Recursive Model Free Controller (RMFC) stabilization component which dose not require any knowledge of the physical model parameters. The proposed entire control enables trajectories tracking of a variable set point trajectory and over performs the existing anaerobic digestion control schemes, such as a classical Proportional-Integral-Derivative (PID) control or a nonlinear PI control. Computer simulation examples illustrate the performance and robustness of the proposed approach.

Trajectory Tracking of Vision Based Robot Systems Using Piecewise Continuous Controllers and Observers

Abstract This paper deals with a new approach of trajectory tracking for a X-Y robot by using the sampled and delayed output of a low cost vision system. The proposed approach is based on the theory of piecewise continuous systems which constitute a particular class of hybrid systems with autonomous switching and controlled impulses. A new robust trajectory tracking system, consisting of a specific piecewise continuous controller and a piecewise continuous observer, is developed. Real-time results are given to illustrate the effectiveness and robustness of the new robot control system.

Active fault tolerant control of wind turbine systems based on DFIG with actuator fault and disturbance using Takagi–Sugeno fuzzy model

Abstract This paper presents an active fault tolerant control (FTC) for doubly fed induction generator (DFIG) with actuator fault and disturbance using Takagi–Sugeno (TS) fuzzy model. The control structure has two parts: fault and disturbance estimation part and FTC part. First, a TS fuzzy model is used to describe the DFIG system. Using a special linear transformation, the original system is decoupled into three independent subsystems: state subsystem without fault and disturbance, disturbance subsystem without fault, and fault subsystem without disturbance. By solving linear matrix inequalities (LMIs), a TS fuzzy observer is designed for the state subsystem without fault and disturbance. Second, estimations of faults and disturbance are obtained using the other subsystem models. Third, an active FTC scheme is developed to reduce the effect of disturbance and actuator faults. Finally, the performance of the proposed FTC is tested for a wind turbine system based on DFIG with actuator faults and disturbance. The simulation results demonstrate that the new FTC scheme makes possible to obtain an efficient fault and disturbance estimation and to reduce the peak current in the transient process.