Jakub Bernat

Modeling and optimal control of variable reluctance stepper motor

Purpose – The purpose of this paper is to present a method of modeling the variable reluctance stepper motor using the time‐stepping finite element technique. The proposed model is used to obtain the optimal control law for the input circuit solving the linear‐quadratic problem.Design/methodology/approach – A strongly coupled field‐circuit model of the stepper motor is presented. Also, the method of the optimal control that minimizes the power loss in the motor windings is proposed.Findings – The proposed optimal control method can be applied to the electrical machines connected to the electronic converters. Calculated control signals may be used to obtain the optimal waveforms of the input voltages at each phase of the analyzed machine.Originality/value – The paper examines the application of the presented control method to minimize the power loss in the stator windings of the four‐phased variable reluctance stepper motor.

Multi-modelling as new estimation schema for high-gain observers

The presented paper proposes a novel method of observer design. A new two-layer observer structure is introduced. The first layer consists of multiple high-gain observers. The latter is built to connect the first layer observers into single one. As the new contribution, the new mapping is defined between an unknown state and measurable outputs allowing to explore new estimation schema. Hence, the proposed method enhances the estimation process for linear and nonlinear systems. Furthermore, it is shown that the introduced observation scheme improves the transients. Illustrative examples are calculated to show the properties of the new observation method.

The study on the model reference adaptive control with proportional derivative action

This article presents a study on the novel method of model reference adaptive control (MRAC). As a new contribution, the derivative action is included into MRAC control to improve the controller performance and efficiency. The stability is analysed using a recent technique called immersion and invariance. The simulations of derived laws are presented based on nonlinear models.

Minimum energy control analysis of the switched reluctance stepper motor considering a nonlinear finite element model

Abstract A method of modeling and numerical simulation of a minimum energy control of the switched reluctance motor using time stepping finite element (FE) technique is presented. In proposed model, the nonlinear electromagnetic field equations and the circuit equations are strongly coupled and solved together with motion equation at each time step. The nonlinearity problem is solved employing the Newton–Raphson (NR) procedure. Presented control technique is based on linear–quadratic problem and adopted to the nonlinear finite element model. The optimal control strategy is numerically investigated and compared with commonly used control strategy for the square wave excitation.

Adaptive control of permanent magnet synchronous motor with constrained reference current exploiting backstepping methodology

The presented paper proposes a novel control method of Permanent Magnet Synchronous Machine. Thanks to a recent technique called adaptive backstepping, adjustment of all motor parameters is obtained considering well known dq model. Furthermore, the introduction of a new trajectory generator gives the possibility to limit the reference current without breaking the adaptation process. Examples are calculated to illustrate the properties of the new control method.

Sensorless position estimator applied to nonlinear IPMC model

This paper addresses the issue of estimating position for an ionic polymer metal composite (IPMC) known as electro active polymer (EAP). The key step is the construction of a sensorless mode considering only current feedback. This work takes into account nonlinearities caused by electrochemical effects in the material. Owing to the recent observer design technique, the authors obtained both Lyapunov function based estimation law as well as sliding mode observer. To accomplish the observer design, the IPMC model was identified through a series of experiments. The research comprises time domain measurements. The identification process was completed by means of geometric scaling of three test samples. In the proposed design, the estimated position accurately tracks the polymer position, which is illustrated by the experiments.

The adaptive torque controller for the brushless DC motor

Abstract This research presents a new adaptive torque controller for the brushless DC motor. The command torque is achieved by the phase current reshaping. The recursive least square algorithm is used for the online parameters estimation, hence the indirect adaptive controller is built.

Multiple models input-output adaptive controller applied to Ionic Polymer Metal Composite

Ionic Polymer Metal Composites(IPMCs) belong to the class of wet Electro-active Polymers (EAPs) and is promising candidate actuator for various potential applications mainly due to its flexible, low voltage/power requirements, small and compact design and lack of moving parts. Among the smart materials available, IPMCs seem to fit nicely in the constraints of robotics because they react mechanically when stimulated by an electrical signal. However, being a widely used material in industry, it requires complex control methods due to its strongly nonlinear nature. This paper presents a novel approach to tuning multiple models adaptive controller. By adding additional filters we significantly improve convergence of the estimates to the true values of the IPMC parameters as compared to conventional adaptive controllers. Numerical results and comparison with experimental data are presented. The effectiveness of the proposed multiple models adaptive control strategy is verified in experiments.

The Adaptive Speed Controller for the BLDC Motor Using MRAC Technique

Abstract This research presents a new adaptive speed controller for the brushless DC motor. The methodology of model reference adaptive control is applied to a novel model of BLDC motor. This novel model provides the possibility to compensate the torque ripples and load torque. The system stability is proven using Lapunov function.

Multiple model adaptive control applied to fractional order systems

A new structure to design an adaptive controller for a fractional order system is presented in this paper. The system has two layers, in which the first one consists of multiple models, while the second one interconnects them to provide weighted state estimates. The key challenge is to analyze the stability of multilayer fractional order adaptive processes. The primary objective is to determine the feedback for the computation of the second layer weights. The models from the first layer are used to define the second level adaptive law. The proposed multilayer structure significantly improves the transient characteristics of the fractional order adaptation process, which results in a more effective control system.