In this paper we analyze a low power wind system operating in autonomous mode.We present a control structure that ensures the maximization of wind energy conversion and the balance between required and produced power.We have studied two stand alone wind system structures based on the capacitor voltage control and the buffer battery operation.The simulation results have been obtained in Matlab/Simulink environment, using PowerSim toolbox.

The paper deals with the optimization of an anaerobic digester with respect to a performance criterion which targets the maximization of the methane production. It is penalized by the environment pollution with the discharged water. The paper includes a comparative study regarding the performances of two optimization approaches: the extremum seeking control, in stochastic and deterministic versions, and the model-based control respectively. The latter uses a characteristic of the optimal regimes which supplies the optimal setpoint (the dilution rate) as a function of the substrate concentration in the inflow, estimated by an extended Kalman filter.

An important issue in analyzing a Wastewater Treatment Plant (WWTP) is modelling the disturbances acting on the control loops of the plant, especially in case of urban WWTPs. Although in the literature periodic variations are systematically adopted for the influent description, the control solutions to reject these disturbances are not taken into consideration. This paper aims to establish a WWTP control solution based on PI + Resonant controller (PI+R), which are suitable for the rejection of the periodical disturbances. The control strategy was validated on a Activated Sludge Model No. 1 (ASM1) based WWTP implemented in SIMBA®.

In this paper a simple solution to obtain a feedback controller from input - output process data is proposed. The method uses the virtual reference structure and the virtual error in order to identify a dynamic compensator (DC) that achieves the derivative behaviour of the controller. The DC, defined as an adaptive filter, achieves a precise and extended compensation of the process dynamics. The controller gain is computed in two ways: either by imposing the gain stability margin, as in the case of processes with significant dead time or with large pole excess, or by imposing the phase stability margin, for other types of processes. Both ways are illustrated in the paper by conclusive case studies.

The paper presents the issue of power control law synthesis, in the case of a large wind system that operates under full-load regime, based on dynamic properties details in frequency domain. Solving this problem involves two phases: the establishment of a linearized model as faithfully as possible in various operating points of the full-load region, and synthesis of the power controller, considered with classic structure, taking into account frequency particularities of the obtained linearized model. Obtained linear model of the controlled process is of order 16 and encloses subsystems for tower fore-aft oscillations damping, and for drive-train torsion oscillations damping. The designed controller contains a PI component and a lag compensator for dynamic correction at high frequencies. It is known that the main features of wind system dynamics generated by the interaction of wind-tower-blade ensemble cause a gap in the gain characteristic of the model and complex conjugate zeros, which can move between right and left half-planes, depending on the average wind speed value. Consequently, for control law synthesis an interactive frequency solution is adopted. This is "transparent" in relation to particularities induced by wind-tower-blade interaction. This solution allows evaluation of the extent to which control law is affected by the subsystem for tower oscillations damping. Given the strong dependence between the model and the mean wind speed value, a gain scheduling control law is designed. At different values of average wind speed, controller synthesis is performed in two ways: one applying the desired values to the stability reserve, and the other requiring the minimization of a performance criterion, aimed at reducing mechanical stress, while the controller parameters are kept in an area that ensures admissible values to the stability reserve. This second way allows obtaining a solution for designing a simple classic controller, dedicated to large wind turbines, to which may be imposed requirements for mechanical fatigue mitigation. The proposed solutions are backed by numerical results obtained through numerical simulation. (C) 2014 Elsevier Ltd. All rights reserved.

his paper presents the rotational wind speed turbulence modeling with a view towards a large wind turbine simulation. The dynamic of high power wind systems is analyzed in relation to rotational wind speed turbulence acting on the wind turbine blades. Rotational wind speed turbulence generation is accomplished through a shaping filter. The paper proposes a method for this filter synthesis, using the correlation technique based on von Karman fixed point spectrum model. A "rated" non parametric frequency model of the rotationally sampled turbulence is deduced in conformity with the theoretical support provided by the correlation technique. The model uses as input data the steady state values of wind speed and rotational speed shaft, as well as site properties like turbulence intensity and turbulence length. The parametric model of the shaping filter is obtained through an optimization procedure which deals with the minimization error between the "rated" frequency characteristic of the filter and the parametric frequency characteristic of the shaping filter that must be synthesized. The paper analyzes how the power spectral density changes when the system operating point moves through different operating regions of the power-wind speed characteristic. It provides numerical results to prove the good approximation between the "rated" rotationally sampled spectrum given by the correlation technique, and the rotationally sampled spectrum given by the synthesized shaping filter. Finally, it shows how the rational shaping filter can be used in the numerical simulation of high-power wind energy conversion systems. (C) 2013 Elsevier Ltd. All rights reserved.

Nowadays, modern aquaculture technologies are made in recirculating systems, which require the use of high-performance methods for the recirculated water treatment. The present chapter presents the results obtained by the authors in the field of modeling and control of wastewater treatment processes from intensive aquaculture systems. All the results were obtained on a pilot plant built for the fish intensive growth in recirculating regime located in "Dunarea de Jos" University from Galati. The pilot plant was designed to study the development of various fish species, starting with the less demanding species (e.g. carp, waller), or "difficult" species such as trout and sturgeons (beluga, sevruga, etc.).

The paper deals with the state estimation for wastewater treatment processes with activated sludge. In the paper deterministic and stochastic observers were developed. As the models describing the wastewater treatment processes are nonlinear, the extended version of these estimation algorithms was used. A comparative study of the two estimation methods based on the examination of the acquired results and on the implementation complexity of the algorithms was made. The estimation algorithms designed in the paper have been validated based on the data supplied by a pilot plant used for the biological treatment of the wastewaters from food industry.

The paper aims to establish the frequency models and sensitivity analysis of a biological filter in an intensive recirculating aquaculture system when changing the functioning regime of the plant. The starting point is an analytical model of a trickling biofilter, a distributed parameter model identified from experimental data. The software implementation of this model is used as a process emulator, various functioning regimes of the trickling biofilter being simulated. Based on the simulated data sets and using adaptive filters the frequency models for each input - output channel have been identified. The sensitivity analysis of the trickling biofilter upon changing the functioning regime has led to important conclusions regarding the control solutions to be adopted for each input - output channel. Finally, based on the analysis conducted, a strategy for the automatic control of the intensive recirculating aquaculture system is proposed.

The aim of this paper is to analyse the closed-loop stability of a squirrel-cage-induction-generator-based wind energy conversion system equipped with an improved power optimization control law. This control imposes a dependence between the generator torque and its rotational speed, thus heavily modifying the system dynamics and control efforts. A stability analysis made through numerical simulation gives the operating limits of the proposed control.

The paper deals with a control structure of the strip thickness in a rolling mill of quarto type (AGC – Automatic Gauge Control). It performs two functions: the compensation of errors induced by unideal dynamics of the tracking systems lead by AGC system and the control adaptation to the change of dynamic properties of the tracking systems. The compensation of dynamical errors is achieved through inverse models of the tracking system, implemented as adaptive filters.

This paper deals with a specific peak power tracking method designed for low power wind systems operating in autonomous mode. Tracking operation is based on battery control associated to a controlled load structure. The proposed system provides a good compromise between two power supply requirements: to maximize the wind energy conversion and to ensure the balance between required and produced power, considering in the same time the constraints imposed by the battery operation. The considered system performs the maximization of the wind energy conversion by adjusting the output voltage of a permanent magnet synchronous generator. The design of these structures was analyzed by digital simulation in Matlab / Simulink environment.

This paper presents the results of experimental investigation of a low-power wind energy conversion system (WECS), based on a permanent-magnet synchronous generator (PMSG) connected directly to the turbine. A development system was built in order to carry out the experiments. Its detailed description is also provided. The development system can work as an autonomous system for remote sites or as a grid-connected system, illustrating the concept of distributed production of electrical energy. It includes a wind turbine simulator, which is speed or torque controlled and offers a "wind shaft", where the static and dynamic characteristics of a turbine are obtained. The wind shaft generator drives a permanent magnet synchronous generator (PMSG). The other components of the hybrid system are: a battery, a classical source and, possibly, a PV source. The hardware/software application is based on the dSPACE system. The experimental results show that the performance of a multi-polar-PMSG-based small wind power system is strongly determined by the generator's behaviour. Two optimal regimes characteristics (ORC) are defined in this paper: the first one represents the mechanical power versus the rotational speed (ORCm) and the second one is the electrical power delivered to a load versus the rotational speed (ORCe). An optimal control loop aiming to maximize the delivered electrical power is designed, namely its reference is computed based on the ORCe. In this way, the global efficiency of the energy conversion is maximized. The effectiveness of the proposed optimal control loop is illustrated by experimental results.

This paper presents the results of experimental investigation of a low-power wind energy conversion system (WECS), based on a permanent-magnet synchronous generator (PMSG) connected directly to the turbine. A test rig was built in order to carry out the experiments; its detailed description is also provided. The experimental results show that the performance of a low-power multi-polar-PMSG-based WECS is strongly determined by the generator's behaviour. Two optimal regimes characteristics (ORC) are defined in this paper: the first one represents the mechanical power versus the rotational speed (ORCm) and the second one is the electrical power delivered to a load versus the rotational speed (ORCe). An optimal control loop aiming to maximize the delivered electrical power is designed, namely its reference is computed based on the ORC. In this way, the global efficiency of the energy conversion is maximized. The effectiveness of the proposed optimal control loop is illustrated by experimental results.

Friction is to be considered an essential process for micrometer scale tracking servo systems. Therefore, a high performing and robust control of friction becomes an important issue in mecatronics and robotics field of research. In this paper, considering the LuGre model of friction, a non-model-based friction compensator is proposed to improve position tracking in a DC electrical drive system. The approach to friction influence compensation is based on the disturbance observer. Friction is to be considered as a load torque for the DC drive took into account and will be estimated via three different structures proposed by the authors. Afterwards, the observer is implemented in a classical feedback compensation scheme in which friction is treated as a load disturbance torque. The efficiency of using such observers in DC servo drive with friction is analyzed by computer simulation of a position control system.

Friction is one of the greatest obstacles in high precision positioning systems. It can cause steady state errors and tracking errors, while it may results in limit cycles. Therefore, the influence of friction on the response of systems, such as a DC servo drive, must be seriously considered. In this paper, considering the LuGre model of friction as part of the process taken into account, a hybrid structure of a feedback compensation scheme is proposed. A compensation signal is provided by a model-based observer via an inverse model of DC motor. The model-based observer is tuned using a load disturbance torque estimator. Thereafter, the whole structure is implemented in a typical position closed-loop in which the feedback consists of a state-feedback (P) part and the model-based compensation term. Good transient responses and tracking steady-state errors are achieved for different micrometer scale reference test signals

The paper presents an analytical approach to the design of PID controllers by combining pole placement with symmetrical optimum method, for the integration plus first-order plant model. The desired closed-loop transfer function (c.l.t.f.) contains a second-order oscillating system and a lead-delay compensator. It is shown that the zero value of c.l.t.f. depends on the real-pole value of c.l.t.f. and in addition, there is only one pole value, which satisfies the assumptions of symmetrical optimum method. In these conditions, the analytical expressions of the controller parameters can be simplified. The method is applied to design a PID autopilot for heading control of a ship with firstorder Nomoto model. Copyright  2005 IFAC

The paper deals with the identification and the control of a continuous biotechnological process using dynamic neural networks. The process considered in the paper is the growth process of Candida lipolytica population on an ammonium sulfate substrate and its model includes a mean age equation. The neural network used for identification is trained at every hour, based on the experimental data from the process and the process parameters are given by the neural network weights determined at every training step. The mean age model has been validated based on the fact that the parameters of the mean age equation are the same with the ones from the other model equations (biomass, substrate and enzyme-substrate complex). The mean age control is of PI type. The feedback contains an on-line identification recurrent neural network, together with a mean age observer.

This paper focuses on a control application of optimization in wind power systems. An optimal control structure for variable speed fixed pitch wind turbines is presented. The optimality of the whole system is defined by the trade-off between the energy conversion maximization and the control input minimization that determines the mechanical stress of the drive train. The frequency separation of the short-term and the long-term variations, adopted in the wind modelling, has resulted in a two-loop control structure. The optimal problem is treated within a complete linear quadratic stochastic approach, whose effectiveness was tested on an electromechanical wind turbine simulator.