In a hybrid memory system using DRAM as the NVM cache, DRAM and NVM can be accessed in serial or parallel mode. However, we found that using either mode alone will bring access latency and bandwidth problems. In this paper, we integrate these two access modes and design a simple but accurate predictor (called SAPredictor) to help choose the appropriate access mode, thereby avoiding long access latency and bandwidth problems to improve memory performance. Our experiments show that SAPredictor achieves an accuracy rate of up to 97.1% and helps reduce access latency by up to 35.6% at fairly low costs.

This paper proposes a sensorless and inductance estimation methods with model predictive control for the interior permanent magnet synchronous motor (IPMSM). The model predictive direct torque and flux control with constant PWM cycle is applied to the control system. The rotor speed and position are estimated based on the current slopes at one active and one zero volage vector during every PWM period where the duty cycle of the active voltage vector is controlled. In addition, the prediction of machine torque and flux is enhanced by the online identification of machine inductances. Extensive numerical simulation has been implemented to validate the robustness and the effectiveness of the proposed sensorless and inductance estimation methods.

This paper proposes a new framework for the deadbeat predictive direct torque control for interior permanent magnet synchronous machine (IPMSM) utilizing active flux. Unlike the existing deadbeat predictive direct torque and stator flux control, it is relatively simple and does not require to neglect any physical quantities such as stator resistance votlage drop and cross-coupling. In addition, a sliding-mode-disturbance-observer (SMDO) is combined to track the system disturbances caused by parameter mismatch in real time. The effectiveness of the proposed composite control is verified by simulation and experiment results.

This paper presents an improved direct torque and flux control of a sensorless control system with Interior Permanent Magnet Synchronous Motor (IPMSM). The estimation of torque and flux is enhanced by the real-time update of machine parameters including stator resistances, d- and q- axis inductance, permanent magnet flux linkage. The estimation of rotor speed and position is based on the measurement of current slopes at one zero- and two active-voltage vectors during every PWM cycle. The d- and q- axis inductances are estimated at PWM frequency based on those current derivatives and the DC bus voltage. The stator resistance and permanent magnet flux linkage which vary slowly due to temperature and aging factors are estimated based on the use of recursive least square technique. The numerical simulation and experimental study of the proposed methods show the effectiveness of the proposed parameter identification method and the improvement of estimated torque and flux of the sensorless control system.

This paper proposes and experimentally assesses an online capacitor condition monitoring algorithm for use with a drive system using an open-end winding topology. The proposed algorithm periodically evaluates the dc-link capacitance during a capacitor discharging state when the motor is at standstill. Expressions of capacitor voltage and current are derived for discharging cycle and provide key information for capacitance estimation using a recursive least square method. Also, the operation range of the proposed algorithm is extended to multiple insulated gate bipolar transistor failure conditions in the inverter. Experimental results verify that the proposed algorithm is capable of identifying capacitor deterioration from both healthy and postfault state for a 3010 uF capacitor (450V 9.8A). but the estimation accuracy is reduced for 438 uF capacitor (385V 2.7A).

This paper presents an alternative implementation of the finite control set model predictive control (FCS-MPC) approach for a 3-Ø, two-level grid-connected power converter. The presented approach combines the concept of discrete space vector modulation into the FCS-MPC structure to improve the input current quality of the power converter. Further, with the help of Lyapunov's stability theory, it is shown that the predictive control law used in the present analysis ensures the stability of the overall system. However, the additional virtual voltage vectors can cause an unacceptable computational burden to the controller. To alleviate this issue, the proposed control approach uses a preselection technique that reduces the number of possible voltage vectors for the optimization process from 38 to 10, thereby allowing the proposed technique to be implemented in a standard control platform. Finally, measurement results are presented from an experimental prototype which demonstrates the efficacy of the proposed algorithm concerning the improvement of the input current quality.

The last two decades have seen growing interest in promoting physical activities by using self-tracking technologies. Previous work has identified social interactions in self-tracking as a crucial factor in motivating users to exercise. However, it is unclear how integrating fitness features into complex pre-existing social network affects users' fitness tracking practices and social interactions. In this research, we address this gap through a qualitative study of 32 users of WeRun--a fitness plugin of the widely adopted Chinese mobile social networking service WeChat. Our findings indicate that sharing fitness data with pre-existing social networks motivates users to continue self-tracking and enhances their existing social relationships. Nevertheless, users' concerns about their online personal images lead to challenges around privacy. We discuss how our study could advance understanding of the effects of fitness applications built on top of pre-existing social networks. We present implications for future social fitness applications design.

A finite-state predictive torque control system for a speed-sensorless induction motor drive supplied from a three-level neutral-point clamped inverter is proposed. For sensorless operation, the controller requires estimated speed and rotor/stator flux. In this study, the rotor speed and the rotor flux are estimated accurately by using an extended Kalman filter. Due to the large number of available voltage vectors, the control algorithm for a multilevel inverter-fed drive is computationally expensive. As a consequence, the controller requires longer execution time that yields worse torque, flux, and speed responses, especially at low-speed. In order to reduce the computational burden, a reduced number of voltage vectors for prediction and optimization in the control algorithm is proposed in this paper. The sign of the stator flux deviation and the position of the stator flux are predicted to lessen the number of voltage vectors tested. Experimental results illustrate that the proposed encoderless strategy can estimate the speed accurately over a wide speed range including field-weakening region while maintaining robustness and excellent torque and flux responses.

Many new IPMSM applications require a high level of fault tolerance. A good option for improving fault tolerance, with respect to open circuit faults, is the single DC supply open-ended winding configuration. Currently, all post-fault control techniques for three phase open-ended winding configurations assume that the IPMSM back EMF is sinusoidal. However, the majority of commercial distributed wound IPMSMs will have harmonics in the back EMF. These back EMF harmonics will couple with the current to produce torque pulsations. This paper suggests a post-fault control strategy which suppresses these torque pulsations. When compared to a current sinusoidal back EMF control method, practical experimental results show that the proposed method significantly reduces the peak to peak torque ripple at speeds up to and below two thirds of the rated speed. At rated speed, the performances of the proposed method and current method converge due to a current tracking error. This error is produced from the DC bus not being able to supply enough voltage for high rates of change in current which are required to suppress torque pulsations caused by high order BEMF harmonics.

The power control of a novel fractional slot concentrated wound interior permanent magnet synchronous generator, directly driven by non-pitchable wind turbine emulator above base wind speeds is presented in this paper. The small scale fractional slot concentrated wound interior permanent magnet synchronous generator utilized has good flux weakening properties due to the interior permanent magnet rotor structure. Therefore, the speed of the generator can be increased beyond base speed. Hence, in this study, the turbine power above base wind speeds is controlled at the rated power by increasing generator speed beyond its base speed since this drops the turbine torque output. A flux weakening control strategy, which increases direct axis current according to operating speed and maximum induced voltage, is used to maintain generator voltage within the limits imposed by the inverter DC link. The dynamic power control of the directly driven prototype is experimentally evaluated using the above strategy. Further, analysis of steady state operating points above base speeds is also included in this study. Finally, the effectiveness of the approach for this generator is demonstrated regarding the operation under current and voltage limitations.

Recent research suggest many flux weakening control techniques for interior permanent magnet synchronous motors. The most established one is the use of two current controllers to control the direct and quadrature axis current components such that the total flux linkage is reduced. If the characteristic current of the motor is less than the rated current of the system, maximum torque per voltage control should be carried out in the flux weakening operation in order to minimize the flux further for a maximum torque. In this paper, the performance of a prototype segmented interior permanent magnet synchronous motor under the flux weakening control with two current controllers are discussed. Because the motor has a characteristic current less than the rated current, maximum torque per voltage control is studied. It is observed from the experimental results that the constant power range can be improved approximately to 3:1 when the maximum torque per voltage control is used, whereas it is 2.3:1 with the conventional flux weakening operation.

A new control approach for maximum torque per ampere control is proposed to improve the efficiency of fractional slot concentrated wound interior permanent magnet synchronous generators under light load conditions. The proposed method is compared with existing current reference trajectories (id zero, conventional maximum torque per ampere and total loss minimization) by experimentally measuring the generator efficiency. The generated power is delivered to the grid through a fully controlled back to back converter. The generator-side converter regulates the speed of the generator while the grid-side inverter is responsible for maintaining a constant dc link voltage. The steady-state analysis of efficiency taken at rated speed shows the effectiveness of the new control compared with id zero control and conventional maximum torque per ampere control. Moreover, efficiency can also attain the same values as loss minimization control for particular operating points after modifying the control approach while operating along the same maximum torque per ampere trajectory. The technique provides the same dynamic performance as the conventional maximum torque per ampere control. Field oriented control based on space vector modulation is adopted for generator control.

This paper presents a closed-loop control strategy for dual inverter-fed, permanent magnet synchronous motors with non-sinusoidal back-EMFs. The inverters are connected to both ends of the machine winding but use only one power source, thus providing a path for zero sequence currents to circulate in the motor windings. If neglected, the zero sequence current can cause higher maximum peak and rms phase currents. Moreover, for the PMSM machine, the zero sequence current is heavily influenced by the back-EMF. Therefore, a closed-loop control strategy to suppress the circulation of zero sequence currents and amplitude of the dominant harmonics caused by non-sinusoidal back-EMF is developed and demonstrated by experiment. It is shown to reduce the zero sequence current. The efficiency of the system before and after the suppression of the zero sequence current is also considered. Analysis of experimentally measured efficiency shows that the losses are higher without harmonic suppression which reduces the efficiency.

This paper proposes three overmodulation schemes in the three-to-five phase indirect matrix converter. The first scheme uses only the adjacent large vectors to produce the reference output voltages. The second scheme improves on that by reducing vector elimination in the d2-q2vector space based on the requirements of the output. The third scheme reduces the overmodulation requirements of the inverter stage by utilizing the available dc-link voltage. All three schemes are shown to be able to increase the voltage transfer ratio of the three-to-five phase indirect matrix converter from 0.7886 to 0.9233 by producing some low order harmonics. The second and third schemes have lower THD generation compared to the first scheme, but require additional calculation for vector elimination. The third scheme generates lower THD on the output compared to the second scheme, but produces some even harmonics. Experimental results from a prototype three-to-five phase indirect matrix converter validate the three proposed schemes.

This paper proposes a Simulated Annealing based Global Maximum Power Point Tracking (GMPPT) technique designed for photovoltaic (PV) systems which experience partial shading conditions (PSC). The proposed technique is compared with the common Perturb and Observe MPPT technique and the Particle Swarm Optimization approach to GMPPT. The performance is assessed by considering the time taken to converge and the number of cases where the technique converges to the GMPP Simulation results indicate the improve performance of the Simulated Annealing based GMPPT algorithm in tracking to the Global maxima in a multiple module system experiencing PSC.

This paper proposes a new high-bandwidth speed sensorless field orientated control system for interior permanent magnet synchronous motor drives for wide speed range operation, including standstill. The sliding mode observer is used for joint stator flux and rotor speed estimation at all speeds. At low speeds, the flux vector estimate of the observer is enhanced by the fundamental PWM excitation technique. This sensorless approach features high control bandwidth, immunity to the motor parameter variation and no additional signal or separate test vector injected. Extensive simulation results are shown to verify the effectiveness of the proposed method. By using the enhanced sliding mode observer, the proposed sensorless drive exhibits smooth transition between the low and high speeds operation and high dynamic and steady-state performances over a wide speed range.

This paper proposes a new sensorless direct torque and flux controlled interior permanent magnet synchronous machine drive fed by a matrix converter. Closed-loop control of both torque and stator flux is achieved by using two PI controllers. The input and output voltage vectors are modulated with the indirect space vector modulation technique. Additionally, unity power factor on the power supply side of matrix converter is achieved through closed-loop compensation of the input displacement angle created by the input filter of matrix converter. The adaptive observer used for joint stator flux and rotor speed estimation is enhanced by HF signal injection scheme for stable operation at low speed including standstill. The stator resistance variation is compensated with the current estimation error. The operating range of the drive is extended into high speed region by incorporating field weakening. The sensorless drive exhibits high dynamic and steady-state performances over a wide speed range. The implementation of digital control system for the proposed matrix converter drive is described in this paper. Extensive experimental results confirming the effectiveness of the proposed method are also included.

A modified direct thrust control of linear permanent magnet motor with sensorless estimation of mover position and speed is presented. The improved direct thrust control is based on decoupled control of thrust and flux in the stator flux frame using space vector modulation. The thrust regulation loop in the stator flux reference frame is developed using a linearized relation between thrust and load angle. The thrust and flux errors are used as inputs to two PI controllers to generate the orthogonal components of the reference voltage in the stator flux reference frame. These orthogonal components are further converted to stationary frame of reference by using the stator flux vector angle so that required voltage vector can be generated using space vector modulation instead of the conventional switching table. This scheme retains all the inherited advantages of classical direct thrust control. In this research the flux vector angular position and the mover speed is estimated from the orthogonal components of stator flux vector without using any position or speed sensor. The proposed approach is experimentally validated by its application to a prototype linear permanent magnet motor drive system in the laboratory. Practical results prove that excellent thrust and flux response with minimized ripple is achieved by the proposed technique. These practical results also demonstrate the effectiveness of sensorless position and speed estimation. Moreover a constant switching frequency is achieved due to space vector modulation.

This paper presents a neural architecture for learning category nodes encoding mappings across multimodal patterns involving sensory inputs, actions, and rewards. By integrating adaptive resonance theory (ART) and temporal difference (TD) methods, the proposed neural model, called TD fusion architecture for learning, cognition, and navigation (TD-FALCON), enables an autonomous agent to adapt and function in a dynamic environment with immediate as well as delayed evaluative feedback (reinforcement) signals. TD-FALCON learns the value functions of the state-action space estimated through on-policy and off-policy TD learning methods, specifically state-action-reward-state-action (SARSA) and Q-learning. The learned value functions are then used to determine the optimal actions based on an action selection policy. We have developed TD-FALCON systems using various TD learning strategies and compared their performance in terms of task completion, learning speed, as well as time and space efficiency. Experiments based on a minefield navigation task have shown that TD-FALCON systems are able to learn effectively with both immediate and delayed reinforcement and achieve a stable performance in a pace much faster than those of standard gradient-descent-based reinforcement learning systems.

Temporal-Difference-Fusion Architecture for Learning, Cognition, and Navigation (TD-FALCON) is a generalization of adaptive resonance theory (a class of self-organizing neural networks) that incorporates TD methods for real-time reinforcement learning. In this paper, we investigate how a team of TD-FALCON networks may cooperate to learn and function in a dynamic multiagent environment based on minefield navigation and a predator/prey pursuit tasks. Experiments on the navigation task demonstrate that TD-FALCON agent teams are able to adapt and function well in a multiagent environment without an explicit mechanism of collaboration. In comparison, traditional Q-learning agents using gradient-descent-based feedforward neural networks, trained with the standard backpropagation and the resilient-propagation (RPROP) algorithms, produce a significantly poorer level of performance. For the predator/prey pursuit task, we experiment with various cooperative strategies and find that a combination of a high-level compressed state representation and a hybrid reward function produces the best results. Using the same cooperative strategy, the TD-FALCON team also outperforms the RPROP-based reinforcement learners in terms of both task completion rate and learning efficiency.