Foreword

Predictive Control of Power Converters and Electrical Drives is an essential work on modern methodology that has the potential to advance the performance of future energy processing and control systems. The main features of modern power electronic converters such as high efficiency, low size and weight, fast operation and high power densities are achieved through the use of the so-called switch mode operation, in which power semiconductor devices are controlled in ON/OFF fashion (operation in the active region is eliminated). This leads to different types of pulse width modulation (PWM), which is the basic energy processing technique used in power electronic systems. The PWM block not only controls but also linearizes power converters, thus it can be considered as a linear power amplifier (actuator). Therefore, power converter and drive systems classically are controlled in cascaded multi-loop systems with PI regulators.

Model-based predictive control (MPC) offers quite a different approach to energy processing, considering a power converter as a discontinuous and nonlinear actuator. In the MPC system the control action is realized in a single controller by on-line selection from all possible states, calculated in the discrete-time predictive model only as the one which minimizes the cost function. Therefore, by appropriate cost function formulation it allows larger flexibility and also achieves the optimization of several important parameters like number of switchings, switching losses, reactive power control, motor torque ripple minimization, etc. Thus, the predictive controller takes over the functions of the PWM block and cascaded multi-loop PI control of a classical system, and can offer to industry flexibility, simplicity and software-based optimal solutions where several objectives must be fulfilled at the same time. The price which is paid for the use of a predictive controller is the large number of calculations required. However, it goes well with the fast development of signal processor capacities and the evolution of industrial informatics.

In 13 chapters organized in four parts, the authors cover the basic principles of predictive control and introduce the reader in a very systematic way to the analysis and design methodology of MPC systems for power converters and AC motor drives. The book has the typical attributes of a monograph. It is well organized and easy to read. Several topics are discussed and presented in a very original way as a result of the wide research performed by the authors. The added simulation examples make the book attractive to researchers, engineering professionals, undergraduate/graduate students of electrical engineering and mechatronics faculties.

Finally, I would like to congratulate the authors for their persistence in research work on this class of control systems. I do hope that the presented work will not only perfectly fill the gap in the book market, but also trigger further study and practical implementation of predictive controllers in power electronics and AC drives.

Marian P. Kazmierkowski

Warsaw University of Technology, Poland