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The purpose of this paper is to obtain an estimation of not measured mechanical state variables of the drive system with elastic coupling between the driven motor and a load machine, using neural networks (NN) of different type for the sensorless drive system.

The load‐side speed and the torsional torque are estimated using multi‐layer perceptron (MLP) and radial basis function (RBF) networks. The special forms of input vectors for neural state estimators were proposed and tested in open‐ and closed‐loop control structure. The estimation quality as well as sensitivity of neural estimators to the changes of the inertia moment of the load machine were evaluated and compared.

It is shown that an application of RBF‐based neural estimators can give better accuracy of the load speed and torsional torque estimation, especially for the proper choice of the input vector of NN, also in the case of a big change of the load machine time constant.

The investigation and comparison is based on simulation tests and looked mainly at the quality of state variable estimation while the realisation cost in parallel processing devices (FPGA) still need to be addressed.

The proposed neural state variable estimators of two‐mass system can be practically implemented in the control structure of two‐mass drive with additional feedbacks from load machine speed and torsional torque, which results in the successive vibration damping.

The application of RBF neural state estimators for two‐mass drive and their comparison with commonly used MLP‐based estimators, as well as testing of both type of NN in the closed‐loop control structure with additional feedbacks based on state variables estimated by neural estimators.

The purpose of this paper is to discuss the design and verification of a new control algorithm for the drive with permanent magnet synchronous motor (PMSM) and flexible coupling based on “Forced dynamics control”. Control laws are derived and tested for the rotor and load angle control and achieve non‐oscillatory position step response with a specified settling time.

“Forced dynamics control” is a new control technique based on feedback linearization which forces rotor or load position to follow demanded position with prescribed closed‐loop dynamics. The proposed control structure is developed in two steps: first, the feedback linearisation is applied to the rotor speed and then similar technique is used for position control loop.

The proposed controller is of the cascade structure, comprising an inner speed control loop, respecting vector control principles and outer position control loop designed to control the rotor or load angle, respectively. Estimates of load torques acting on the motor and load side as inputs of control algorithms are produced in observers and used to compensate disturbances offering a certain degree of robustness. Preliminary experiments confirm that proposed system follows the ideal closed‐loop dynamics with moderate accuracy.

The focus is on experimental verification of the position control of flexible PMSM drive with two position sensors and moderate precision, where the oscillations due to hardware setup, achieved sampling frequency and corresponding observers adjustment are limited up to 50 rad s⁻¹.

The designed control structure can substantially improve control performance of industrial plants subjects to torsion oscillations.

Experimental results of a novel control structure for the PMSM drives with torsion oscillations are sufficiently promising and confirmed that the rotor and load angle responses follow the prescribed ones fairly closely.

The purpose of this paper is to obtain a fully sensorless permanent magnet synchronous motor (PMSM) drive control algorithm used for robot arm drive with load recognition. The paper shows how to use an extended Kalman filter (EKF) instead of sensors of the mechanical quantities as well as how to adapt the model of the PMSM to the filter procedures and aims at the real time application in the field‐oriented control (FOC) structure of the high‐dynamic drive.

The synthesis of the control system is based on the method of the FOC, theory of the EKF and object description in the form of state equation with suitable choice of state vector. The adequate connection of these three methodologies is a core of the approach to design. First, the control algorithm was tested by means of simulation method then the real laboratory plant was built and investigated.

Owing to task‐oriented formulation of the PMSM model, adequate organization of the EKF procedures and suitable choice of covariance matrices the proper control algorithm was obtained. The algorithm can be applied on DSP and gives a good result for the high dynamic drive in spite of the fact that the Kalman procedures are recognized as a time‐consumed solution of the estimation problem.

The proposed algorithm can be used also in the case of another type of drive, for instance induction motor drive, although the model of the motor has a different formula. A disadvantage of the method is lack of the general rules for choosing the elements of the covariance matrices.

The presented algorithm is written in open‐programming language. Obtained results may be important for synthesis of robot arm drive, where the information about load forces is needed.

The paper presents an original sensorless vector control of PMSM with load recognition based on EKF. The originality elements are the choice of the covariance matrix elements and the real‐time realisation of the algorithm on the DSP.

The purpose of this paper is to develop a generalized observer and controller for brushless direct current (BLDC) motor to make the system more robust for parameter variations, load torque and speed tracking.

A robust interconnection and damping assignment passivity-based control (IDA-PBC) technique for BLDC motor is introduced in this paper. The IDA-PBC is used to obtain the reference voltages for pulse width modulation (PWM) control. The immersion and invariance (I&I) observer is used to estimate the load torque and speed of the BLDC motor. At the time of starting, the motor rotates in arbitrary direction, and sometimes, because of the cogging action, it may take a huge current. Therefore, a new start-up method is proposed for the BLDC motor, which maintains the alignment of the rotor.

From the simulation and experimental results, it can be seen that the proposed controller and observer satisfactorily work for parameter variations, load torque and speed tracking.

The authenticity of the proposed technique is tested experimentally on two different BLDC motors using low-cost 32-bit STM32F407VG microcontroller. The response of the proposed technique is evaluated by changing motor parameters such as stator resistance, inductance, flux linkage constant and torque constant.

The purpose of this paper is to discuss the design and verification of a non‐classical structure of servo‐drive controller with the state feedback and a load torque feedforward compensation.

First a well known nonlinear mathematical model of a PMSM is transformed into a linear form by introducing new variables. The state space new model presented in rotated orthogonal reference frame is decoupled by means of equation in d and q axis. To achieve correct dynamic performance of the servo‐drive system the state feedback with an internal input model and load torque feedforward compensation is proposed. The observed load torque has been used as an input signal for the feedforward compensator. The design of the control system and simulation analysis were performed in Matlab/Simulink. The proposed control algorithm was implemented in a DSP controller (TMS320F2812). The experiments were carried out by using a 0.6 kW PMSM drive system.

It is shown that the proposed compensator can eliminate the effects of load torque changes by steady‐state operation and significantly improve dynamic behaviour during load changing. A novel mathematical formula how calculate an appropriate gain for feedforward compensator is given.

Analysis of possible disturbance compensation shows that full dynamic compensation of disturbance is impossible. Only the compensation of load torque for a steady state is possible. The described control structure operates without state variables limitations so it is not recommended to application where the high dynamic of transient process is required.

The proposed control system can be used in industrial applications where load torque compensation is needed instead the high dynamic performance.

Presented mathematical formula how calculate an appropriate gain for feedforward compensator is a theoretical contribution of the authors. The test results are consistent with the computer simulation test results and validate the correct dynamic performance of the proposed control method.

The purpose of this paper is position control scheme for a servo induction motor (SIM) with uncertainty has been designed using a new observer issue and a dynamic sliding mode control (DSMC).

In DSMC, the chattering is removed due to the integrator (or a low-pass filter) which is placed before the input control of the plant. However, in DSMC, the augmented system has one dimension bigger than the actual system (if integrator is used) and then, the plant model should be completely known. To solve this problem in SIM, the use of a new adaptive state observer (ASO) is proposed.

The advantage of the proposed approach is to maintain the system controlled under the external load torque variations. Then, the load variations do not affect the motor positioning. Moreover, it is demonstrated that the observer error converges to zero based on the Lyapunov stability theory.

The knowledge of the upper bound for the system uncertainty is not necessary in an adaptive state observer, which is important in practical implementation. Simulation results are presented to demonstrate the performance of the proposed approach.

The purpose of this paper is to improve the performance of sensorless vector control of induction motor drives by developing a new sliding mode observer for rotor speed and fluxes estimation from measured stator currents and voltages and estimated stator currents.

In the present paper, the discontinuity in the sliding mode observer is smoothed inside a thin boundary layer using fuzzy logic techniques instead of sign function to reduce efficiently the chattering phenomenon that affects the rotor speed.

The feasibility of the proposed fuzzy sliding mode observer has been verified by experimentation. The experimental results are obtained with a 1 kW induction motor using a dSPACE system with DS1104 controller board showing clearly the effectiveness of the proposed approach in terms of dynamic performance compared to the classical sliding mode observer.

The experimental results of the whole control structure highlights that this kind of sensorless induction motor drive can be used for variable speed drive in industrial applications such as oil drilling, electric vehicles, high speed trains (HSTs) and conveyers. Such drives may work properly at zero and low speed in both directions of rotation.

Both the proposed speed observer and the classical sliding mode observer have been developed and implemented experimentally with other adaptive observers for detailed comparison under different operating conditions, such as parameter variation, no-load/load disturbances and speed variations in different speed operation regions.

The purpose of this paper is to elaborate a robust model‐based protective control algorithm for multi‐mass motor drives that are subjected to physical and safety constraints on their variables.

The algorithm relies on the off‐line computed maximum robust controlled invariant set or its approximation for the given drive system and imposed constraints. It can be used to patch any existing drive control scheme with a firm constraints satisfaction guarantee. The online patch implementation is actually a simple correction of the control signal computed with the existing control scheme, with a mandatory state observer.

Performance of the patch is tested on a two‐mass drive system in combination with classical two‐mass drive speed controllers – P+I and reduced state controller. All constraints violations that exist in the presented responses obtained without the protection patch are suppressed by using the patch which shows the effectiveness of the approach. A brief implementation analysis shows that a digital signal processor could be used for online implementation of the controller with the protective patch.

Robust invariant sets theory is efficiently and effectively used in a new application area – protection of multi‐mass electrical drives.

Sensorless online measurements, application of variable speed drives has been given a great attention, especially over the past few years. In most of the previous literates dealing with permanent magnet synchronous motor (PMSM) drives, the combination of inter-sampled behavior with high gain design approach has not been discussed yet. This paper aims to discuss this feature in-depth.

The study contains a different approach for an observer running with surface-mounted permanent magnet synchronous machine drives to implement sensorless control. Design of sampled data observer methodology for one kind of AC machine having non-linear model and backed by an elegant formal stability convergence analysis using the tools of Lyapunov stability techniques was highly recommended in scientific contributions, and it is yet needed to be solved.

In this study, a solution to observation problem is covered and developed by combining ideas from the high-gain design approach and inter-sample predictor based on stator voltage measurements. The output state currents are accessible only at the sampling instant to solve the problem of states observation at continuous-time mode. This allows to reducing the usage of online appliances, improving reliability of control design and saving costs.

The proposed observer is capable of guaranteeing an acceptable closed loop dynamic response over a wide range of operation region and industrial process for random initial conditions.

The output state predictor has been interred in constructing the innovation correct term to prove the robustness of the proposed observer against attenuated sampling interval. To validate the theoretical results introduced by the main fundamental theorem and prove the observer stability convergence, the proposed observer is demonstrated through a sample study application to variable speed permanent magnet synchronous machine drive.

The purpose of this paper is to develop the Permanent Magnet Synchronous Motors drive which has possibility to work in sensorless mode at low speed based on back EMFs estimation.

Estimation uses modified Luenberger observer and the preprocessing of the EMFs before calculating the speed, using derivative and the Kalman filter (KF) to obtain smooth waveform of the estimated speed. This modification is needed because of the nonlinear change of the estimated back EMFs amplitude as a function of speed, in low-speed range.

How to use back EMF observer to estimate a speed in the low-speed range was found in the course of the work. Simple and effective algorithm uses KF and can work even with a relatively big deformation of the estimated back EMF.

Such sensorless drive may be used in low-cost constant or variable speed drive in domestic use or industrial application. Such drive may work properly where there is no initial load torque and the sign of the speed does not change.

Presented results challenge the view that at low-speed range (not the standstill), the back EMF-based method of position estimation is very difficult or impossible. However, the problem lays in proper speed estimation, not the position estimation.