In the paper a comparative study of the two control structures based on MPC (Model Predictive Control) for an electrical drive system with an induction motor are presented. As opposed to the classical approach, in which DFOC (Direct Field Oriented Control) with four controllers is considered, in the current study only one MPC controller is utilized. The proposed control structures have a cascade free structure that consists of a vector of electromagnetic (torque, flux) and mechanical (speed) states of the system. The first investigated framework is based on the finite-set MPC. A short horizon predictive window is selected. The continuous set MPC is used in the second framework. In this case the predictive horizon contains several samples. The computational complexity of the algorithm is reduced by applying its explicit version. Different implementation aspects of both MPC structures, for instance the model used in prediction, complexity of the control algorithms, and their properties together with the noise level are analyzed. The effectiveness of the proposed approach is validated by some experimental tests.

The paper aims to present the novel control structures for a drive system with an elastic connection. Two control structures based on forced dynamic control (FDC) laws are investigated. The first one is based on the state controller approach, the second one on cascade methodology. These two approaches ensure different dynamic properties of the drive system. In the first approach, called full-FDC, the ability to remove the effect of the load torque from the load speed is assured, but the shaft torque cannot be directly limited. In the second approach the possibility of fast elimination of the load torque effect is limited, yet the shaft torque can be fully controlled. The detailed design methodology of both control structures is presented in the paper. Their properties are analyzed through simulation and experimental studies.

This paper presents some of the issues related to the implementation of advanced control structures (PI controller with additional feedback, Model Predictive Controller) for drives with elastic coupling on a programmable logic controller (PLC). The predominant solutions to electric drive control include the use of rapid prototyping cards, signal processors or programmable matrices. Originally, PLC controllers were used to automate sequential processes, but for several years now, a trend related to their implementation for advanced control objects can be observed. This is mainly due to their compact design, immunity to disturbances and standard programming languages. The following chapters of the paper present the mathematical model of the drive and describe the implementation of the proposed control structures. A PI controller with additional feedback loops and a predictive controller are taken into consideration. Their impact on the CPU load was analysed, and the work was summarised by a comprehensive experimental study. The presented results confirm that it is possible to implement advanced control structures on a PLC controller for drives with elastic coupling while maintaining a sufficiently low load on its CPU.

This article discusses speed control methods for electric motor drives with elastic mechanical coupling causing torsional vibrations, which negatively affect the operation of the system. Model Predictive Control (MPC) is often presented as an effective solution; however, it is notoriously difficult to implement in real-time due to the high computational complexity of the controller. In this paper, a simplified predictive control approach in the form of Analytical MPC (aMPC) is proposed for the speed control of a two-mass motor drive. In contrast to conventional MPC, which requires complex online optimisation, aMPC derives an explicit control law analytically under simplifying assumptions, greatly reducing the computational load. The effect of the controller parameters on the drive performance is investigated and a multi-objective performance function for automatic tuning is proposed. The aMPC structure is compared with conventional State Feedback Control (SFC), including a system robustness test of both approaches. Based on simulation studies and experimental verification, the proposed structure is shown to ensure high dynamics in drive control, with smoother torque control and superior robustness for higher-load inertia ratios than SFC.

The article presents issues related to the application of a moving horizon estimator for state variables reconstruction in an advanced control structure of a drive system with an elastic joint. Firstly, a short review of the commonly used methods for state estimation in presented. Then, a description of a state controller structure follows. The design methodology based on the poles-placement method is briefly described. Next, the mathematical algorithm of MHE is presented and some crucial features of MHE are analysed. Then, selected simulation and experimental results are shown and described. The investigation shows, among others, the influence of window length on the quality of state variables estimation.

In this paper issues connected with the application of the model predictive control (MPC) to the speed control of an induction motor drive are presented. The predictive controller regulates the state of the two-mass system (motor speed, shaft torque, load speed) in one algorithm. In order to ensure the proper work in the field weakening region the adaptation of the electromagentic as well as shaft torque constraints is necessary. The theoretical considerations are supported by simulation and experimental tests.