Search Results (5)

This paper summarizes a robust controller based on the fact that, in the operation of a permanent magnet synchronous motor (PMSM), a number of disturbance factors naturally occur, among which both changes in internal parameters (e.g., stator resistance R_s and combined inertia of rotor and load J) and changes in load torque T_L can be mentioned. In this way, the performance of the control system can be maintained over a relatively wide range of variation in the types of parameters mentioned above. It also presents the synthesis of robust control, the implementation in MATLAB/Simulink, and an improved version using a reinforcement learning twin-delayed deep deterministic policy gradient (RL-TD3) agent, working in tandem with the robust controller to achieve superior performance of the PMSM sensored control system. The comparison of the proposed control systems, in the case of sensored control versus the classical field oriented control (FOC) structure, based on classical PI-type controllers, is made both in terms of the usual response time and error speed ripple, but also in terms of the fractal dimension (DF) of the rotor speed signal, by verifying the hypothesis that the use of a more efficient control system results in a higher DF of the controlled variable. Starting from a basic structure of an ESO-type observer which, by its structure, allows the estimation of both the PMSM rotor speed and a term incorporating the disturbances on the system (from which, in this case, an estimate of the PMSM load torque can be extracted), four variants of observers are proposed, obtained by combining the use of a multiple neural network (NN) load torque observer and an RL-TD3 agent. The numerical simulations performed in MATLAB/Simulink validate the superior performance obtained by using properly trained RL-TD3 agents, both in the case of sensored and sensorless control. Full article

Starting from the problem of studying the parametric robustness in the case of the control of a permanent magnet-synchronous motor (PMSM), although robust control systems correspond entirely to this problem, due to the complexity of the algorithms of the robust type, in this article the use of switched systems theory is proposed as a study option, given the fact that these types of systems are suitable both for the study of systems with variable structure and for systems with significant parametric variation under conditions of lower complexity of the control algorithms. The study begins by linearizing a PMSM model at a static operating point and continues with a systematic presentation of the basic elements and concepts concerning the stability of switched systems by applying these concepts to the control system of a PMSM based on the field-oriented control (FOC) strategy, which usually changes the value of its parameters during operation (stator resistance R_s, stator inductances L_d and L_q, but also combined inertia of PMSM rotor and load J). The numerical simulations performed in Simulink validate the fact that, for parametric variations of the PMSM structure, the PMSM control switched systems preserve qualitative performance in terms of its control. A series of Matlab programs are presented based on the YALMIP toolbox to obtain P_i matrices, by solving Lyapunov–Metzler type inequalities, and using dwell time to demonstrate stability, as well as the qualitative study of the performance of PMSM control switched systems by presenting in phase plane and state space analysis of the evolution of state vectors: ω PMSM rotor speed, i_q current, and i_d current. Full article

The accuracy estimation of induction motors’ efficiency is beneficial and crucial in the industry for energy savings. The requirement for in situ machine efficiency estimation techniques is increasing in importance because it is the precondition to making the energy-saving scheme. Currently, the torque and speed identification method is widely applied in online efficiency estimation for motor systems. However, the higher precision parameters, such as stator resistance R_s and equivalent resistance of iron losses R_fe, which are the key to the efficiency estimation process with the air gap torque method, are of cardinal importance in the estimation process. Moreover, the computation burden is also a severe problem for the real-time data process. To solve these problems, as for the torque and speed-identification-based efficiency estimation method, this paper presents a lower time burden method based on Quantum Particle Swarm Optimization-Trust Region Algorithm (QPSO-TRA). The contribution of the proposed method is to transform the disadvantages of former algorithms to develop a reliable hybrid algorithm to identify the crucial parameters, namely, R_s and R_fe. Sensorless speed identification based on the rotor slot harmonic frequency (RSHF) method is adopted for speed determination. This hybrid algorithm reduces the computation burden by about 1/3 compared to the classical genetic algorithm (GA). The proposed method was validated by testing a 5.5 kW motor in the laboratory and a 10 MW induction motor in the field. Full article

In this work, supported cellulose acetate (CA) mixed matrix membranes (MMMs) were prepared and studied concerning their gas separation behaviors. The dispersion of carbon nanotube fillers were studied as a factor of polymer and filler concentrations using the mixing methods of the rotor–stator system (RS) and the three-roll-mill system (TRM). Compared to the dispersion quality achieved by RS, samples prepared using the TRM seem to have slightly bigger, but fewer and more homogenously distributed, agglomerates. The green γ-butyrolactone (GBL) was chosen as a polyimide (PI) polymer-solvent, whereas diacetone alcohol (DAA) was used for preparing the CA solutions. The coating of the thin CA separation layer was applied using a spin coater. For coating on the PP carriers, a short parameter study was conducted regarding the plasma treatment to affect the wettability, the coating speed, and the volume of dispersion that was applied to the carrier. As predicted by the parameter study, the amount of dispersion that remained on the carriers decreased with an increasing rotational speed during the spin coating process. The dry separation layer thickness was varied between about 1.4 and 4.7 μm. Electrically conductive additives in a non-conductive matrix showed a steeply increasing electrical conductivity after passing the so-called percolation threshold. This was used to evaluate the agglomeration behavior in suspension and in the applied layer. Gas permeation tests were performed using a constant volume apparatus at feed pressures of 5, 10, and 15 bar. The highest calculated CO₂/N₂ selectivity (ideal), 21, was achieved for the CA membrane and corresponded to a CO₂ permeability of 49.6 Barrer. Full article

The main scope of this work is to develop nano-carbon-based mixed matrix cellulose acetate membranes (MMMs) for the potential use in both gas and liquid separation processes. For this purpose, a variety of mixed matrix membranes, consisting of cellulose acetate (CA) polymer and carbon nanotubes as additive material were prepared, characterized, and tested. Multi-walled carbon nanotubes (MWCNTs) were used as filler material and diacetone alcohol (DAA) as solvent. The first main objective towards highly efficient composite membranes was the proper preparation of agglomerate-free MWCNTs dispersions. Rotor-stator system (RS) and ultrasonic sonotrode (USS) were used to achieve the nanofillers’ dispersion. In addition, the first results of the application of the three-roll mill (TRM) technology in the filler dispersion achieved were promising. The filler material, MWCNTs, was characterized by scanning electron microscopy (SEM) and liquid nitrogen (LN₂) adsorption-desorption isotherms at 77 K. The derivatives CA-based mixed matrix membranes were characterized by tensile strength and water contact angle measurements, impedance spectroscopy, gas permeability/selectivity measurements, and water permeability tests. The studied membranes provide remarkable water permeation properties, 12–109 L/m²/h/bar, and also good separation factors of carbon dioxide and helium separations. Specifically, a separation factor of 87 for 10% He/N₂ feed concentration and a selectivity value of 55.4 for 10% CO₂/CH₄ feed concentration were achieved. Full article