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.
A brushless direct-current (BLDC) and permanent-magnet synchronous motors (PMSMs) with permanent magnets are characterised by the highest operating parameters among all electric motors. High dynamics and the possibility of controlling their work improves the operating parameters of the drive system and reduces the operating costs of such a device. The high cost of these machines associated with the complexity of their construction is a serious barrier to increasing their range in small propulsion systems, where lower energy consumption does not give such spectacular financial profits. To reduce costs, manufacturers often limit the variety of manufactured engines so that by increasing the volume, the unit cost of the device can be minimised. This is often hindered by the implementation of projects deviating from standards where it is necessary to use drive systems of different power. The solution to this problem could be the use of two independent drive systems working in strict correlation to ensure sufficient operating parameters of the device. The article presents a method of controlling a drive system in which two propulsion systems with PMSM engines were used. These devices are communicated with each other by a serial bus, by means of which data necessary for the correct operation of motors connected by a drive belt are transmitted. Since these machines affect both the working machine and each other, it is necessary to optimise such a system so as to avoid excessive oscillation of the drive torque in the system.
Acoustical Driving Forces (ADF), induced by propagating waves in a homogeneous and inhomogeneous lossy fluid (suspension), are determined and compared depending on the concentration of suspended particles. Using integral equations of the scattering theory, the single particle (inclusion) ADF was calculated as the integral of the flux of the momentum density tensor components over the heterogeneity surface. The possibility of negative ADF was indicated. Originally derived, the total ADF acting on inclusions only, stochastically distributed in ambient fluid, was determined as a function of its concentration. The formula for the relative increase in ADF, resulting from increased concentration was derived. Numerical ADF calculations are presented. In experiments the streaming velocities in a blood-mimicking starch suspension (2 μm radius) in water and Bracco BR14 contrast agent (SF6 gas capsules, 1 μm radius) were measured as the function of different inclusions concentration. The source of the streaming and ADF was a plane 2 mm diameter 20 MHz ultrasonic transducer. Velocity was estimated from the averaged Doppler spectrum obtained from originally developed pulsed Doppler flowmeter. Numerical calculations of the theoretically derived formula showed very good agreement with the experimental results.
This paper investigates the application of a novel Model Predictive Control structure for the drive system with an induction motor. The proposed controller has a cascade-free structure that consists of a vector of electromagnetics (torque, flux) and mechanical (speed) states of the system. The long-horizon version of the MPC is investigated in the paper. In order to reduce the computational complexity of the algorithm, an explicit version is applied. The influence of different factors (length of the control and predictive horizon, values of weights) on the performance of the drive system is investigated. The effectiveness of the proposed approach is validated by some experimental tests.
In this paper, we propose sensorless backstepping control of a double-star induction machine (DSIM). First, the backstepping approach is designed to steer the flux and speed variables to their references and to compensate uncertainties. Lyapunov”s theory is used and it demonstrates that the dynamic tracking of trajectories tracking is asymptotically stable. Second, unfortunately, this law control called sophisticated is a major problem which leads to the necessity of using a mechanical sensor (speed, load torque). This imposes an additional cost and increases the complexity of the montage. In practice, this variable is unknown and its measurement is expensive. To restrain this problem we estimate speed and load torque by using a Luenberger observer (LO). Simulation results are provided to illustrate the performance of the proposed approach in high and low variable speeds and load torque disturbance.
The purpose of this paper is to show possibility and advantages of initial control plane reproduction for an adaptive fuzzy controller. Usually the fuzzy control is used when the object is not very well known. Yet the truth is, however, that some, at least general information about the object, is available. Usually, in such a case, optimization algorithms are used to tune the control structure. The purpose of this article is to show how to find a starting point that is closer to optimum than a statistically random point, and this way to obtain better results in a shorter time.
Cells of a prototype powered wheelchair can be designed in various connections to provide different supply voltages which has impact on the efficiency of other wheelchair drive elements. The impact of cell configuration and resulting battery voltage on overall efficiency of power elements have been studied to determine the optimal configuration and voltage of the pack. A brief description of a battery energy storage system was given, and main requirements and variables were introduced to reveal the flexibility of the battery design. The efficiency versus supply voltage plots of a drive converter and battery charger were presented and discussed to find the optimal battery voltage. The motor design was analyzed from the fill factor perspective. The calculated efficiency parameters of all drive power elements were used to discuss and select an optimal battery cell configuration.
Accurate information on Induction Motor (IM) speed is essential for robust operation of vector controlled IM drives. Simultaneous estimation of speed provides redundancy in motor drives and enables their operation in case of a speed sensor failure. Furthermore, speed estimation can replace its direct measurement for low-cost IM drives or drives operated in difficult environmental conditions. During torque transients when slip frequency is not controlled within the set range of values, the rotor electromagnetic time constant varies due to the rotor deep-bar effect. The model-based schemes for IM speed estimation are inherently more or less sensitive to variability of IM electromagnetic parameters. This paper presents the study on robustness improvement of the Model Reference Adaptive System (MRAS) based speed estimator to variability of IM electromagnetic parameters resulting from the rotor deep-bar effect. The proposed modification of the MRAS-based speed estimator builds on the use of the rotor flux voltage-current model as the adjustable model. The verification of the analyzed configurations of the MRAS-based speed estimator was performed in the slip frequency range corresponding to the IM load adjustment range up to 1.30 of the stator rated current. This was done for a rigorous and reliable assessment of estimators’ robustness to rotor electromagnetic parameter variability resulting from the rotor deep-bar effect. The theoretical reasoning is supported by the results of experimental tests which confirm the improved operation accuracy and reliability of the proposed speed estimator configuration under the considered working conditions in comparison to the classical MRAS-based speed estimator.
Short-term contact losses between a pantograph and a contact wire are not included in the standards nor are they taken into account in evaluating pantograph-contact wire interaction. These contact losses, however, accelerate wear and tear as well as disturb operation of vehicles’ drive systems. The article presents the effects of short-term contact breaks as well as an analysis of impact of contact breakages on a vehicle’s current at 3 kV DC power supply. Results of voltage and current oscillations measured in real conditions when pantograph of a DC driven chopper vehicle was running under isolators were presented. Then a simulation model of a vehicles with ac motors and voltage inverters was derived to undertake simulation experiments verifying operation of such a vehicle in condition similar to those measured in real condition.
One of the little described problems in hydrostatic drives is the fast changing runs in the hydraulic line of this drive affecting the nature of the formation and intensity of pressure pulsation and flow rate occurring in the drive. Pressure pulsation and flow rate are the cause of unstable operation of servos, delays in the control system and other harmful phenomena. The article presents a flow model in a hydrostatic drive line based on fluid continuity equations (mass conservation), maintaining the amount of Navier-Stokes motion in the direction of flow (x axis), energy conservation (liquid state). The movement of liquids in a hydrostatic line is described by partial differential equations of the hyperbolic type, so modeling takes into account the wave phenomena occurring in the line. The hydrostatic line was treated as a cross with two inputs and two outputs, characterized by a specific transmittance matrix. The product approximation was used to solve the wave equations. An example of the use of general equations is presented for the analysis of a miniaturized hydrostatic drive line fed from a constant pressure source and terminated by a servo mechanism.
The paper presents a method for designing a neural speed controller with use of Reinforcement Learning method. The controlled object is an electric drive with a synchronous motor with permanent magnets, having a complex mechanical structure and changeable parameters. Several research cases of the control system with a neural controller are presented, focusing on the change of object parameters. Also, the influence of the system critic behaviour is researched, where the critic is a function of control error and energy cost. It ensures long term performance stability without the need of switching off the adaptation algorithm. Numerous simulation tests were carried out and confirmed on a real stand.
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