This book, written by two major figures in adaptive control, provides a wealth of material for researchers, practitioners, and students. While some researchers in adaptive control may note the absence of a particular topic, the book‘s scope represents a high-gain instrument. It can be used by designers of control systems to enhance their work through the information on many new theoretical developments, and can be used by mathematical control theory specialists to adapt their research to practical needs. The book is strongly recommended to anyone interested in adaptive control.

Adaptive Control

System Identification I

Dynamics of structures

Brief paper: Adaptive control with guaranteed transient and steady state tracking error bounds for strict feedback systems

The use of power converters is very important in maximizing the power transfer from renewable energy sources such as wind, solar, or even a hydrogen-based fuel cell to the utility grid An LCL filter is often used to interconnect an inverter to the utility grid in order to filter the harmonics produced by the inverter Although there is an extensive amount of literature available describing LCL filters, there has been a gap in providing a systematic design methodology Furthermore, there has been a lack of a state-space mathematical modeling approach that considers practical cases of delta- and wye-connected capacitors showing their effects on possible grounding alternatives This paper describes a design methodology of an LCL filter for grid-interconnected inverters along with a comprehensive study of how to mitigate harmonics The procedures and techniques described in this paper may be used in small-scale renewable energy conversion systems and may be also retrofitted for medium- and large-scale grid-connected systems

$LCL$ Filter Design and Performance Analysis for Grid-Interconnected Systems

Adaptive fuzzy control of a class of MIMO nonlinear systems

analysis is essential in improving condition monitoring and fault diagnostics of rotating machinery. Many signal analysis methods are able to extract useful information from vibration data. Currently, the most of these methods use spectral analysis based on Fourier Transform (FT). However, these methods present some limitations; it is the case of non-stationary signals. In the present work, we are interested to the vibration signal analysis by the Wavelet Transform (WT). The WT is one of the most important methods for signal processing; it is especially suitable for non-stationary vibration measurements obtained from accelerometer sensors. The monitoring results indicate that the WT can diagnose the abnormal change in the measured data.

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Application of Wavelet Transform for Fault Diagnosis in Rotating Machinery

This paper presents the analysis, modelling and control model of the electric part of a grid connected photovoltaic generation system. The model contains a detailed representation of the main components of the system that are the solar array, and the grid side multilevel neutral point clamped (NPC) voltage source inverter (VSI). In order to extract the maximum amount of from the photovoltaic generator, we propose an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and insulation conditions. This method uses a fuzzy logic controller. As part of our work, we will focus on voltage inverter at three levels to NPC structure. The latter can increase the voltage supplied to the load (network) through their topology. Thus, they can generate more voltage sinusoidal possible and improve the total harmonic distortion through the high voltage levels provided by the structure of this new converter. The grid interface inverter transfers the energy drawn from the PV module into the grid by keeping common dc voltage constant. The PQ control approach (Direct Power Control) has been presented for the multilevel inverter. The simulation results under Matlab/Simulink show the control performance and dynamic behaviour of grid connected photovoltaic system.

Modeling and control of a gird connected PV generation system

Display Omitted An hybrid approach for vector control of the three-phase induction motor is proposed.The proposed approach combines in a different manner that existing in literature the two techniques: the artificial neuronal network (ANN) and the fuzzy logic (FL).The performances of the proposed hybrid control; applied to the three-phase induction motor supplied by voltage source inverter; are investigated by simulations; and performances proofs are further verified by comparative results to others controls in different operating conditions.The results show the feasibility and good performance obtained by the proposed control: improved response time and mostly enhanced the robustness of the system. Furthermore, it reinforces the principle of vector control, procuring a good decoupling between the electromagnetic torque and rotor flux. Nowadays, the microcomputer performs calculations at an incredibly high rate of billions of instructions per second. That represents an exponential increase in the processing speed since the early days of the computer development, eventhough such growth did not show complex reasoning that even the simple biological organisms can make. The artificial intelligence techniques as an attempt to work about those limitations, are a promising alternative.Each intelligent technique has its particular strengths and weaknesses and cannot be universally implemented to any problem. Mixed together, these techniques can improve the solutions quality and allow application to various tasks. It is the reason why the AI is used increasingly in order to solve complex problems in engineering. Where, it is still necessary to make progress in the controller tuning.The idea proposed in this paper is simple and original. It is the result of a study that compared the performances of two controls based on the artificial intelligence techniques: the artificial neural networks and the fuzzy logic. The control proposed in this paper combines in a different manner these two techniques in the form of a hybrid control. The aim is to benefit from performances of each of these techniques, by using them in the same control block at the most suitable place.The performances of the this proposed hybrid control; applied to the three-phase induction motor supplied by voltage source inverter; are investigated and compared to those obtained from the controls based on artificial neural networks; fuzzy logic and conventional techniques. The results of simulation show the feasibility and the good performances achieved by the proposed control.

Hybrid control of the three phase induction machine using artificial neural networks and fuzzy logic

This paper presents a simulation model of the electric part of a grid connected photovoltaic generation system The model contains a detailed representation of the main components of the system that are the solar array, and the grid side inverter multilevel inverter Neutral Point Clamped (NPC) VSI In order to extract the maximum amount of from the photovoltaic generator, we propose an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and insulation conditions This method uses a fuzzy logic controller As part of our work, we will focus on voltage inverter at three levels to NPC structure The latter can increase the voltage supplied to the load (network) through their topology Thus, they can generate more voltage sinusoidal possible and improve the total harmonic distortion through the high voltage levels provided by the structure of this new converter The grid interface inverter transfers the energy drawn from the PV module into the grid by keeping common dc voltage constant The PQ control approach has been presented for the multilevel inverter The simulation results under Matlab/Simulink show the control performance and dynamic behaviour of grid connected photovoltaic system

Mohamed Seghir Boucherit

Papers

Adaptive fuzzy control of a class of MIMO nonlinear systems

Application of Wavelet Transform for Fault Diagnosis in Rotating Machinery

Modeling and control of a gird connected PV generation system

Hybrid control of the three phase induction machine using artificial neural networks and fuzzy logic

Modeling and simulation of a gird connected PV generation system with MPPT fuzzy logic control