The paper recapitulates recently conducted investigations of non-proportional Luenberger observers, applied to reconstruction of state variables of induction motors. Three structures of non-proportional observers are analyzed, a proportional-integral observer, modified integral observer and observer with integrators. Criteria for gain selection of the observer are described, classical ones based on poles, as well as additional, increasing observer’s robustness. Fulfilment of the presented criteria can be ensured with the three proposed methods for gain selection, two analytical, based on dyadic transformation and one based on optimization.

Electromagnetic mill installation for dry grinding represents a complex dynamical system that requires specially designed control system. The paper presents model-based predictive control which locates closed loop poles in arbitrary places. The controller performs as gain scheduling prototype where nonlinear model – artificial recurrent neural network, is parameterized with additional measurements and serves as a basis for local linear approximation. Application of such a concept to control electromagnetic mill load allows for stable performance of the installation and assures fulfilment of the product quality as well as the optimization of the energy consumption.

Tuning rules for PID and PI-PI servo controllers are developed using a pole placement approach with a multiple pole, i.e. a triple one in the case of PID and a quadruple for PI-PI. The controllers involve complex roots in the numerators of the transfer functions. This is not possible in the classical P-PI structure which admits real roots only. The settling time of the servos determined by the multiple time constant is the only design parameter. Nomograms to read out discrete controller settings in terms of the time constant and control cycle are given. As compared to the classical structures, the upper limit on the control cycle is now twice longer in the case of PID, and four times in the case of PI-PI. This implies that the settling times can be shortened by the same ratios. Responses of a PLC-controlled servo confirm the validity of the design.

This paper presents a state feedback controller (SFC) for position control of PMSM servo-drive. Firstly, a short review of the commonly used swarm-based optimization algorithms for tuning of SFC is presented. Then designing process of current control loop as well as of SFC with feedforward path is depicted. Next, coefficients of controller are tuned by using an artificial bee colony (ABC) optimization algorithm. Three of the most commonly applied tuning methods (i.e. linear-quadratic optimization, pole placement technique and direct selection of coefficients) are used and investigated in terms of positioning performance, disturbance compensation and robustness against plant parameter changes. Simulation analysis is supported by experimental tests conducted on laboratory stand with modern PMSM servo-drive.

The paper addresses the problem of constrained pole placement in discrete-time linear systems. The design conditions are outlined in terms of linear matrix inequalities for the Dstable ellipse region in the complex Z plain. In addition, it is demonstrated that the D-stable circle region formulation is the special case of by this way formulated and solved pole placement problem. The proposed principle is enhanced for discrete-lime linear systems with polytopic uncertainties.