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Item Open Access PI anti-windup speed control of permanent magnet synchronous motor based on feedforward compensation(Nazarbayev University School of Science and Technology, 2018-06-26) Do, Ton Duc; Zhetpissov, Yernar; Kaibaldiyev, AzamatThis paper designs simulation model of PI anti-windup speed controller based on a simple set-point weighting for the interior permanent-magnet synchronous motor (IPMSM). Firstly, a mathematical model of IPMSM drive system utilized in the simulation is introduced. Also, the maximum torque per ampere (MTPA) control suitable for IPMSM was employed. This controller is simple for implementation in practice and it has advantages over a conventional PI controller. The proposed anti-windup PI controller demonstrates better dynamic step changes response in speed in terms of overshoots, improved settling time, and improved robustness to parameter variations in comparison with conventional PI. The performance of proposed PI anti-windup controller with set-point weighting was compared with the conventional PI.Item Open Access Direct-torque control system design using maximum torque per ampere method for interior permanent magnet synchronous motors(Nazarbayev University School of Science and Technology, 2018-06-26) Do, Ton Duc; Nurtay, Bekarys; Duisenbay, BotaThe paper proposes a method for controlling interior Permanent Magnet Synchronous Motor (IPMSM) drives, that combines Direct-Torque control (DTC) and Maximum Torque Per Ampere (MTPA) in a synchronously rotating (d-q) frame. It has been proven that the increase of electromagnetic torque is proportional to the increase of angle between rotor and stator flux linkages. The use of the DTC method for controlling IPMSM shows a quick and robust response with torque and flux ripples. Combined with MPTA the efficiency of the system is increased as there is no need for prior estimation of flux. Also, speed control loop with PI controller is also introduced to the system for speed regulation. Here, we introduce a simple MTPA-based DTC scheme with speed control with satisfied performance. The feasibility of the system is confirmed by Simulink model, the results of which are presented in the paper.Item Open Access Feature extraction and real-time recognition of hand motion intentions from EMGs via artificial neural networks(Nazarbayev University School of Science and Technology, 2018-01-05) Oleinikov, Artemiy; Abibullaev, Berdakh; Shintemirov, Almas; Folgheraiter, MicheleElectromyography (EMG) signal analysis is one of the key determinants of the effectiveness of prosthetic devices. Modern researchers provide various methods of detection of different hand movements and postures. In this work, we examined the possibility to produce efficient detection of hand movement to a specific posture with the minimum possible number of electrodes. The data acquisition is produced with 1 channel BiTalino EMG sensor based on bipolar differential measurement. Using feature extraction and artificial neural network we achieved 82% of offline classification accuracy for 8 hand motions and 91% accuracy for 6 hand motions based on 200 ms of EMG signal. Also, the motion detection algorithm was developed and successfully tested that allowed to implement the algorithm for real-time classification and that showed sufficient accuracy for 2 and 4 motion classes cases.Item Open Access Trained by Demonstration Humanoid Robot Controlled via a BCI system for Telepresence(Nazarbayev University School of Science and Technology, 2018-01-15) Saduanov, Batyrkhan; Alizadeh, Tohid; Abibullaev, Berdakh; An, JinungOnerous life of paralyzed people is a substantial problem of the world society and improving their life quality would be a great achievement. This paper proposes a solution in this regard based on telepresence, where a patient perceives and interacts with a world through an embodiment of a robot controlled by a Brain-Computer Interface (BCI) system. The proposed approach brings together two leading techniques: Programming by Demonstration and BCI. Several tasks could be learned by the robot observing someone performing the function. The end user would issue commands to the robot, using a BCI system, concerning its movement and the tasks to be performed. An experiment is designed and conducted, verifying the applicability of the proposed approach.Item Open Access Brain-Computer Interface Humanoid Pre-trained for Interaction with People(Nazarbayev University School of Science and Technology, 2018-03-08) Saduanov, Batyrkhan; Tokmurzina, Dana; Alizadeh, Tohid; Abibullaev, BerdakhPeople with the disabilities are in need to have an assistive technology that will alleviate their life through improving its social aspects. This article presents a Brain-Computer Interface (BCI) based remote presence system for humanoid NAO robot. The system would be useful for partially or fully paralyzed patients to interact with people and live active social life. A P300 based BCI is used to control high-level desires of the humanoid and visual stimulus presentation is implemented to control a humanoid robot. ”Programming by Demonstration (PbD)” methods are used to train the robot to perform human interactive actions and NAO robot native speller is used to talk with people. In general, the proposed solution combines two major techniques: Programming by demonstration and BCI. An experiment is designed and conducted on 5 different healthy subjects to perform a handshake, waving, walking and etc., verifying the applicability of the proposed approach.Item Metadata only MOBY-DIC: A MATLAB Toolbox for Circuit-Oriented Design of Explicit MPC(IFAC Proceedings Volumes, 2012-01-01) Oliveri, Alberto; Barcelli, Davide; Bemporad, Alberto; Genuit, Bart; Heemels, Maurice; Poggi, Tomaso; Rubagotti, Matteo; Storace, Marco; Alberto, OliveriAbstract This paper describes a MATLAB Toolbox for the integrated design of Model Predictive Control (MPC) state-feedback control laws and the digital circuits implementing them. Explicit MPC laws can be designed using optimal and sub-optimal formulations, directly taking into account the specifications of the digital circuit implementing the control law (such as latency and size), together with the usual control specifications (stability, performance, constraint satisfaction). Tools for a-posteriori stability analysis of the closed-loop system, and for the simulation of the circuit in Simulink, are also included in the toolbox.Item Open Access An Electromagnetic Steering System for Magnetic Nanoparticle Drug Delivery(2015) Do, Ton Duc; Noh, Yeongil; Kim, Myeong Ok; Yoon, JungwonTargeted delivery of pharmaceutical agents to the brain using magnetic nanoparticles (MNPs) is an efficient technique to transport molecules to disease locations. MNPs can cross the blood–brain barrier (BBB) and can be concentrated at a specific location in the brain using non-invasive electromagnetic forces. The proposed EMA consists of two coil-core system. The cores are added in the center of each coil to concentrate the flux in the region of interest. The EMA can enhance the gradient field 10 times compared to only coil system and generate the maximum magnetic field of 160 mT and 5.6 T/m. A 12-kW direct-current power supply was used to generate sufficient magnetic forces on the MNPs by regulating the input currents of the coils. Effective guidance of MNPs is demonstrated via simulations and experiments using 800-nm-diameter MNPs in a Y-shaped channel. The developed EMA system has high potentials to increase BBB crossing of MNPs for efficient drug targeting to brain regions