Reset Scheme Research Articles

A practical real-time control strategy for high-performance building HVAC operation concerning potential pandemic outbreaks in post-pandemic era

The lessons learned from the COVID-19 pandemic emphasize the need for building HVAC systems to be adaptable and prepared to adjust their operation for infection risk mitigation for future pandemics. Most guidelines suggest increasing outdoor air fraction in HVAC systems during pandemics. However, this approach is not energy-efficient due to the conditioning of additional outdoor air, and many practical systems face limitations in introducing more outdoor air than normal due to capacity or design constraints. Therefore, there is an urgent need for an alternative solution for HVAC system operation during pandemics that is energy-efficient, can effectively mitigate infection risks and does not require extensive retrofits to existing systems. To meet this need, this study proposes a practical real-time control strategy for high-performance HVAC operation in response to potential pandemic outbreaks. First, a supply air temperature (SAT) reset scheme for infection risk mitigation is proposed based on Mamdani fuzzy inference theory. Then, a coordinated control scheme is proposed to coordinate SAT reset with chilled water temperature adjustment for energy-efficiency enhancement. This strategy does not require system equipment retrofits but only changes in control logic to transition to pandemic operation. The effectiveness of the proposed strategy is validated in a high-fidelity Modelica-based simulation environment under various weather conditions. Results show that, compared to normal operation, the proposed strategy can significantly reduce new infection cases by 32∼46 % without increasing energy use, and may even achieve slight energy savings of 9∼13 %, while maintaining expected occupant comfort.

Implementation of two-step gradual reset scheme for enhancing state uniformity of 2D hBN-based memristors for image processing

In-memory computing facilitates efficient parallel computing based on the programmable memristor crossbar array. Proficient hardware image processing can be implemented by utilizing the analog vector-matrix operation with multiple memory states of the nonvolatile memristor in the crossbar array. Among various materials, 2D materials are great candidates for a switching layer of nonvolatile memristors, demonstrating low-power operation and electrical tunability through their remarkable physical and electrical properties. However, the intrinsic device-to-device (D2D) variation of memristors within the crossbar array can degrade the accuracy and performance of in-memory computing. Here, we demonstrate hardware image processing using the fabricated 2D hexagonal boron nitride-based memristor to investigate the effects of D2D variation on the hardware convolution process. The image quality is evaluated by peak-signal-to-noise ratio, structural similarity index measure, and Pratt’s figure of merit and analyzed according to D2D variations. Then, we propose a novel two-step gradual reset programming scheme to enhance the conductance uniformity of multiple states of devices. This approach can enhance the D2D variation and demonstrate the improved quality of the image processing result. We believe that this result suggests the precise tuning method to realize high-performance in-memory computing.

Reconfigurable supply-based feedback control for enhanced energy flexibility of air-conditioning systems facilitating grid-interactive buildings

Air-conditioning systems have great potential to provide energy flexibility services to the power grids of high-renewable penetration, due to their high power consumption and inherent energy flexibilities. Direct load control by switching off some operating chillers is the simplest and effective means for air-conditioning systems in buildings to respond to urgent power reduction requests of power grids. However, the implementation of this approach in today's buildings, which widely adopt demand-based feedback controls, would result in serious problems including disordered cooling distribution and likely extra energy consumption. This study, therefore, proposes a reconfigurable control strategy to address these problems. This strategy consists of supply-based feedback control, incorporated with the conventional demand-based feedback control, a control loop reconfiguration scheme and a setpoint reset scheme, facilitating effective control under limited cooling supply and smooth transition between supply-based and demand-based feedback control modes. The proposed control strategy is deployed in a commonly-used digital controller to conduct hardware-in-the-loop control tests on an air-conditioning system involving six AHUs. Test results show that the reconfigurable control achieves commendable control performance. Proper chilled water distribution enables even thermal comfort control among the building zones during demand response and rebound periods. Temperature deviation of the building zones is controlled below 0.2 K most of the time. 11.6 % and 27 % of power demand reductions are achieved during demand response and rebound periods respectively, using the proposed reconfigurable control compared with that using conventional controls.

Improving the Performance of Optimization Algorithms Using the Adaptive Fixed-Time Scheme and Reset Scheme

Optimization algorithms have now played an important role in many fields, and the issue of how to design high-efficiency algorithms has gained increasing attention, for which it has been shown that advanced control theories could be helpful. In this paper, the fixed-time scheme and reset scheme are introduced to design high-efficiency gradient descent methods for unconstrained convex optimization problems. At first, a general reset framework for existing accelerated gradient descent methods is given based on the systematic representation, with which both convergence speed and stability are significantly improved. Then, the design of a novel adaptive fixed-time gradient descent, which has fewer tuning parameters and maintains better robustness to initial conditions, is presented. However, its discrete form introduces undesirable overshoot and easily leads to instability, and the reset scheme is then applied to overcome the drawbacks. The linear convergence and better stability of the proposed algorithms are theoretically proven, and several dedicated simulation examples are finally given to validate the effectiveness.

A Front-End Amplifier With Fast Reset Scheme for Capacitive Heart Rate Monitoring

Non-contact capacitive electrodes are a suitable choice for unobtrusive and long-term ECG/heart-rate monitoring applications, but require a front-end amplifier with large input impedance, low noise, and motion artifact (MA) reduction methods. This paper proposes a front-end amplifier structure with a fast reset scheme. It enables MA recovery prior to saturation and therefore avoids a long recovery process which may take up to several seconds and results in signal loss in typical capacitive sensing systems. A reconstruction algorithm restores the waveform and hence extends the dynamic range beyond the original saturation level. The proposed fast-reset amplifier and a conventional pseudo-resistor biased amplifier were fabricated in an 180nm CMOS technology. The electrical characterization results s how that the fast-reset version is superior to the conventional structure, by achieving an input resistance of 1.8 TΩ, a 3-100Hz 2.3 μV <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rms</sub> integrated noise level with a 10 pF source impedance, and the ability to deal with MA saturation. Finally a 4-channel system employing the proposed amplifiers was built. It can successfully measure ECG R-peaks through clothes, while the fast reset scheme enables continuous detection in the presence of MAs.

An Efficient Parameter Optimization of Maximum Correntropy Criterion

The maximum correntropy criterion (MCC) algorithm depends upon two fundamental parameters, i.e., step-size and kernel width. Previous studies of parameter optimization in the MCC mainly focus on a single parameter (mainly the kernel width), lacking optimization research concerning both parameters. To this end, this letter investigates a novel optimization scheme simultaneously involving step-size and kernel width. The optimization framework is based on making the power of weight error vector undergo the steepest attenuation. Under the premise of maintaining the same evolutionary trend for time-varying step-size and kernel width, we formulate a constrained parameter optimization problem, where the step-size is subject to a kernel width induced constraint. By taking this approach, the original bivariate optimization can be transformed into a univariate optimization problem, which facilitates optimization solving. We further develop an existing reset scheme to make it suitable for kernel width to ensure a good tracking capability. In addition, we investigate the convergence behavior of the optimized algorithm. Simulation results demonstrate that the developed optimization scheme is beneficial for performance improvement, and the resulting algorithm outperforms some state-of-art MCC-based algorithms.

Initial experimental results on a superconducting-qubit reset based on photon-assisted quasiparticle tunneling

We present here our recent results on qubit reset scheme based on a quantum-circuit refrigerator (QCR). In particular, we use the photon-assisted quasiparticle tunneling through a superconductor–insulator–normal-metal–insulator–superconductor junction to controllably decrease the energy relaxation time of the qubit during the QCR operation. In our experiment, we use a transmon qubit with dispersive readout. The QCR is capacitively coupled to the qubit through its normal-metal island. We employ rapid, square-shaped QCR control voltage pulses with durations in the range of 2–350 ns and a variety of amplitudes to optimize the reset time and fidelity. Consequently, we reach a qubit ground-state probability of roughly 97% with 80-ns pulses starting from the first excited state. The qubit state probability is extracted from averaged readout signal, where the calibration is based on Rabi oscillations, thus not distinguishing the residual thermal population of the qubit.

Highly Deterministic One-Shot Set–Reset Programming Scheme in PCMO Resistive Random-Access Memory

Resistive random-access memory (RRAM) devices are very versatile with applications ranging from digital nonvolatile memories to analog synapses and integrate-fire neurons. Recently, RRAM based stochastic neurons have also been proposed for optimization networks that solve NP-hard problems. These applications rely on reliably writing a given conductance state repeatedly. A Pr1–xCaxMnO3 (PCMO) based RRAM device is a nonfilamentary, bulk switching RRAM which demonstrates low device-to-device variations compared to filamentary RRAMs. However, a low complexity programming scheme to demonstrate low cycle-to-cycle variations (C2CV) as well is needed. In this work, we propose a one-shot Set (initialize) and Reset (program) scheme to experimentally demonstrate low C2CV (<15%) for multiple devices. Compared to one-shot programming on a filamentary device, there is a 2–4× increment in the number of levels that can be stored per device using PCMO RRAM. Further, one-shot programming in PCMO RRAM leads to a 35× (10×) reduction in the number of pulses for 3 (2) bits per device, respectively. This greatly simplifies the memory controller design for these devices compared to any iterative write-verify schemes. This scheme gives a further insight into the self-heating limited Set operation controlled by a series resistor while reinforcing the analog and precise nature of the Reset operation. We studied the impact of the C2CV in programming RRAM-based stochastic neurons on the Max-Cut optimization problem using Boltzmann machines. PCMO RRAM combined with the one-shot programming scheme emerges as the clear choice for a well-controlled RRAM device with minimal peripheral complexity.

Autonomous quantum error correction in a four-photon Kerr parametric oscillator

Autonomous quantum error correction has gained considerable attention to avoid complicated measurements and feedback. Despite its simplicity compared with the conventional measurement-based quantum error correction, it is still a far from practical technique because of significant hardware overhead. We propose an autonomous quantum error correction scheme for a rotational symmetric bosonic code in a four-photon Kerr parametric oscillator. Our scheme is the simplest possible error correction scheme that can surpass the break-even point—it requires only a single continuous microwave tone. We also introduce an unconditional reset scheme that requires one more continuous microwave tone in addition to that for the error correction. The key properties underlying this simplicity are protected quasienergy states of a four-photon Kerr parametric oscillator and the degeneracy in its quasienergy level structure. These properties eliminate the need for state-by-state correction in the Fock basis. Our schemes greatly reduce the complexity of autonomous quantum error correction and thus may accelerate the use of the bosonic code for practical quantum computation.

Resonator nanophotonic standing-wave array trap for single-molecule manipulation and measurement

Nanophotonic tweezers represent emerging platforms with significant potential for parallel manipulation and measurements of single biological molecules on-chip. However, trapping force generation represents a substantial obstacle for their broader utility. Here, we present a resonator nanophotonic standing-wave array trap (resonator-nSWAT) that demonstrates significant force enhancement. This platform integrates a critically-coupled resonator design to the nSWAT and incorporates a novel trap reset scheme. The nSWAT can now perform standard single-molecule experiments, including stretching DNA molecules to measure their force-extension relations, unzipping DNA molecules, and disrupting and mapping protein-DNA interactions. These experiments have realized trapping forces on the order of 20 pN while demonstrating base-pair resolution with measurements performed on multiple molecules in parallel. Thus, the resonator-nSWAT platform now meets the benchmarks of a table-top precision optical trapping instrument in terms of force generation and resolution. This represents the first demonstration of a nanophotonic platform for such single-molecule experiments.

Improving Flicker of Low-Refresh-Rate Driven Active-Matrix Organic Light-Emitting Diode Display

The brightness of low-temperature polycrystalline silicon and metal-oxide (LTPO) active-matrix organic light-emitting diode (AMOLED) display under low-refresh-rate driving condition tends to increase during pixel voltage holding time of each frame even though there is no critical leakage current path from the storage capacitor. We have found that the main cause of the brightness increase is electron trapping into the gate insulator of driving thin film transistor (DTFT) which operates in the saturation mode prone to hot carrier injection. We propose a novel driving method to suppress the brightness variation by applying a high voltage to the source and drain of the DTFT during the non-emitting time which is inserted periodically for dimming the organic light-emitting diode (OLED) display. Our experimental results show that the brightness variation can be reduced from 3.7 % to 1.4 % at the 63rd gray level by the proposed DTFT reset scheme.

Rapid and unconditional parametric reset protocol for tunable superconducting qubits

Qubit initialization is a critical task in quantum computation and communication. Extensive efforts have been made to achieve this with high speed, efficiency and scalability. However, previous approaches have either been measurement-based and required fast feedback, suffered from crosstalk or required sophisticated calibration. Here, we report a fast and high-fidelity reset scheme, avoiding the issues above without any additional chip architecture. By modulating the flux through a transmon qubit, we realize a swap between the qubit and its readout resonator that suppresses the excited state population to 0.08% ± 0.08% within 34 ns (284 ns if photon depletion of the resonator is required). Furthermore, our approach (i) can achieve effective second excited state depletion, (ii) has negligible effects on neighboring qubits, and (iii) offers a way to entangle the qubit with an itinerant single photon, useful in quantum communication applications.

Non-damping system reset schemes for underwater SINS based on intermittent calibration information

For Strap-down Inertial Navigation System (SINS), the estimation accuracy of gyro drifts in system reset is subject to the steady state horizontal attitude errors induced by accelerometer biases. Two non-damping system reset schemes are proposed to solve this problem. First, the Doppler velocity log (DVL) aided parameter estimation method is derived to estimate the accelerometer biases and equivalent horizontal attitude errors; then the P equation of system reset is reformulated in which the horizontal attitude errors are considered and obtained through the parameter estimation method; finally, on the basis of P equation, with intermittent calibration information, two system reset schemes are designed. Simulation results indicate that by compensating accelerometer biases before system reset, the proposed schemes have higher estimation accuracy of gyro drifts, meanwhile they reduce the time of using DVL and have better error suppression performance than existing schemes.

Investigation of capacitor-less integrate and fire neuron by using dual-gate a PN-body tied silicon on insulator field-effect transistor

In this study, integrate and fire neuron by using a dual-gate (DG) PN-body tied (PNBT) silicon on insulator field-effect transistor (SOI-FET) was investigated. We found out that the DG PNBT SOI-FET has the integrate and fire function in a single device. The floating body and the positive feedback effect can perform the functions of the capacitor and comparator, respectively. The device can generate a continuous spike and also a single spike signal with the additional reset scheme. The reset action requires a recovery time, which can be controlled by voltage conditions. It has a chance of making a refractory period function. These characteristics mean that it is possible to realize the capacitor-less small footprint neuron circuit with the DG PNBT SOI-FET.

A real-time optimal control strategy for multi-zone VAV air-conditioning systems adopting a multi-agent based distributed optimization method

Determining the proper trade-off among thermal comfort, Indoor Air Quality (IAQ) and energy use is important for optimal control of air-conditioning systems. The number of optimization variables increases as systems become increasingly complex, as with multi-zone VAV (Variable Air Volume) air-conditioning systems, leading to large-scale mathematics programming challenges and inconveniences in the implementation of conventional centralized optimization strategies. This paper therefore proposes a real-time optimal control strategy adopting a multi-agent based distributed optimization method for multi-zone VAV air-conditioning systems. The proposed strategy consists of three novel schemes. First, a temperature set-point reset scheme adopts a linear rule to correlate the resetting of the temperature set-points in individual zones to simplify the optimization problem while applying proper optimization in individual zones. Second, a multi-objective optimization scheme optimizes the fresh air ratio of the supply air and the temperature set-point in the critical zone by formulating the multi-objective optimization problem. Third, a multi-agent distributed optimization scheme is developed to solve the optimization problem in a distributed manner, facilitating the deployment of local control devices of limited capacity. A TRNSYS-MATLAB co-simulation testbed is constructed to test and validate the proposed strategy. Test results show that the strategy is effective in properly balancing thermal comfort, IAQ and energy use while largely reducing programming challenges. The distributed optimization method can provide almost the same optimal outputs as conventional centralized optimization methods.

Reset-control-based current tracking for a solenoid with unknown parameters

Abstract We propose a hybrid controller for reference tracking for the output current of a solenoid. The solenoid can be modeled as a first-order linear plant with unknown parameters. The proposed hybrid controller comprises 1) a feed forward action, based on an estimate of the unknown plant parameters exploiting a hybrid formulation of the recursive least-squares method, and 2) a feedback action, exploiting a reset control scheme based on a first-order reset element. We prove stability properties for the closed-loop system and we show through simulations that the current output converges to the reference for sufficiently exciting reference signals.

Non-damping system reset algorithm for shipborne grid strap-down inertial navigation systems

The system reset algorithms realized in damping state rely heavily on the output of Doppler velocity logs (DVLs). Aiming at a shipborne grid strap-down inertial navigation system (SGSINS), this paper addresses a non-damping system reset algorithm to estimate the gyroscope drifts. First, the SGSINS is integrated with the DVL to estimate the horizontal attitude errors, and the estimation results are introduced to the system reset. Next, to ensure the equation can be utilized to design the non-damping system reset scheme, the equation is reformulated by reserving the horizontal attitude errors as the correction terms. Finally, with the assistance of two intermittent or short continuous external yaw and position, the two-point and optimum system reset schemes are designed based on the equation and equation. Simulation results indicate the algorithm can estimate the gyroscope drifts accurately in non-damping state. Compensating the gyroscope drifts can efficiently suppress the drifted errors in SGSINS. Because it takes a short time to estimate the horizontal attitude errors, compared with the existing algorithms realized in damping state, the proposed algorithm greatly shortens the time of using DVL, and this improves the reliability of the algorithm in practical application.

Stability analysis of delayed reset systems with distributed state resetting

In this paper, the author studies the stability of delayed reset control systems with distributed state resetting. First, the concept of distributed state reset is proposed which is capable of compensating for the performance deterioration caused by time delays. Second, a sufficient condition for asymptotical stability based on the Lyapunov–Krasovskii functional method is proved, and a sufficient condition in terms of LMIs to ensure asymptotical stability of reset systems with piecewise constant reset mappings is obtained. Last, an illustrative example is provided to show that compared to the traditional reset scheme, the proposed distributed state reset scheme is potentially capable of achieving better performance.

Pulsed Reset Protocol for Fixed-Frequency Superconducting Qubits

The unconditional and fast reset of fixed-frequency superconducting qubits is crucial for the operation of near-term quantum computers at elevated trigger rates. Many reset schemes are either conditional (depend on the qubit's state) or require flux tunability. This study presents an all-microwave pulsed reset sequence that uses the readout resonator to unconditionally empty a fixed-frequency transmon qubit, and that also reduces the qubit thermal population. This method could be used to increase the repetition rate of a superconducting quantum computer running, for example, variational eigensolvers requiring many measurements.

Fast and Unconditional All-Microwave Reset of a Superconducting Qubit.

Active qubit reset is a key operation in many quantum algorithms, and particularly in quantum error correction. Here, we experimentally demonstrate a reset scheme for a three-level transmon artificial atom coupled to a large bandwidth resonator. The reset protocol uses a microwave-induced interaction between the |f,0⟩ and |g,1⟩ states of the coupled transmon-resonator system, with |g⟩ and |f⟩ denoting the ground and second excited states of the transmon, and |0⟩ and |1⟩ the photon Fock states of the resonator. We characterize the reset process and demonstrate reinitialization of the transmon-resonator system to its ground state in less than 500ns and with 0.2% residual excitation. Our protocol is of practical interest as it has no additional architectural requirements beyond those needed for fast and efficient single-shot readout of transmons, and does not require feedback.