Reference Input Research Articles

Single-Loop Robust Model Predictive Speed Regulation of PMSM Based on Exogenous Signal Preview

Speed regulation problem of permanent magnet synchronous motor (PMSM) with overcurrent protection is addressed in this paper by using a single-loop robust model predictive control (MPC) approach. The unique feature of this new disturbance rejection MPC method is the utilization of the preview information of lumped exogenous signal. Different from most of the existing disturbance observer-based MPC approaches, the reference inputs, the lumped disturbances in PMSM, and their higher-order differences are explicitly considered as a part of this new concept of lumped exogenous signal by exploiting output regulation theory. Preview of the possible future behaviors of this exogenous signal is conducted based upon the development of two generalized proportional integral observers (GPIOs). An accuracy enhanced prediction model is obtained by exploiting the estimation and preview of the exogenous signal during the prediction horizon. Speed regulation problem of the PMSM is transformed into an error stabilization problem by means of regulator equations and preview information where the faster time-varying exogenous signal is considered. The overcurrent protection problem is also taken into account throughout the receding horizon optimization process. Experimental studies show that the proposed method achieves effective functionality in overcurrent protection, and much better dynamic performance against time-varying exogenous inputs.

Mode standardization: A practical countermeasure against mode collapse of GAN-based signal synthesis

Intelligent fault diagnosis, particularly via data-driven deep learning, is vital for industrial health management. However, it often faces challenges due to unbalanced datasets, with either insufficient fault data or redundant data representing the same condition. For signal-based diagnosis, generative adversarial networks (GANs) provide a countermeasure by generating new signals for data augmentation but can suffer from mode collapse, causing monotonous new signals and further imbalance. Inspired by the conditional mechanism, we propose mode standardization to mitigate mode collapse in GAN-based signal synthesis. This method utilizes part of the original signals as reference input to the generator. As a result, although mode collapse still occurs, and the new signals may still be monotonous, this monotony is confined to their references. In other words, as long as the references are diverse, the generated signals will maintain an acceptable diversity, similar to the original. The negative effects of mode collapse are diminished, decreasing harm to the generation process. Comparative experiments demonstrate mode standardization's effectiveness in diversity and quality on various datasets, affirming it as a practical countermeasure against mode collapse and a suitable strategy for industrial practice.

Geomorphic flood hazard mapping: from floodplain delineation to flood hazard characterization

ABSTRACTRecent studies show how geomorphic descriptors, retrieved from digital elevation models (DEMs), can be used for flood hazard mapping. As they strictly depend on the accuracy of the input DEMs and reference flood hazard maps used for training, DEM-based flood hazard models may display severe inconsistencies. Our study shows the application of two advanced DEM-based models to a large study area, and presents two main innovative points. First, the delicate tasks of appropriately selecting the input DEM and flood hazard map are specifically addressed with newly defined methods. Second, the ability of DEM-based models to exploit their natural features to enhance flood hazard mapping over the study region is investigated. Our results show (a) the benefits of considering multiple geomorphic descriptors, (b) the potential of DEM-based models for completing the information of imperfect reference flood hazard maps, and (c) the advantages of continuous representation of hazard over binary flood maps.

A novel parallel multi-harmonic global multi-channel control algorithm for helicopter active vibration control

The vibrations of the helicopter fuselage are mainly induced by the rotor with blade pass frequency and the high order harmonics. The conventional filtered-x least mean square (FxLMS) control algorithm usually used a uniform convergence factor for all the harmonics which leads poor effect in controlling multi-harmonic vibration. In this paper, a novel parallel multi-harmonic global multi-channel (MHGMC) control method is proposed to suppress the multi-harmonic vibration components transmitted from the main rotor to the fuselage. Bandpass filters are used to separate multiple frequency components of the error signals, the control channel models are identified for the corresponding frequency range to independently control each frequency component, and the reconstruction of the reference input signals can be obtained from the separated error signal, effectively improving the performance of tracking interference signals. In addition, the coupling of the control channels is considered, and the global vibration optimization is taken as the control objective to update the weight coefficient of the controller. An active vibration control system of the helicopter main gearbox eight-strut installation configuration has been established. The simulation and experiment results show that the proposed controller has faster control convergence speed and better control effect of multiple harmonics than the conventional filtered-x least mean square algorithm, and the attenuations of the disturbing frequency harmonic components at all measurement points in the experiment are over 38dB. The experimental results of variable excitation also verify that the proposed control algorithm has excellent adaptability and strong robustness.

PV Grid-Connected Inverter With DC Voltage Regulation in CCM and VCM Operation to Reduce Switching Losses

In this paper, a photo-voltaic (PV) grid connected inverter (GCI) is employed for multi-functional control (i.e., real power flow control form PV panels, mitigation of current and voltage related power quality (PQ) problems) and the GCI input reference dc voltage is formulated as a function of GCI output currents for loss reduction during low currents through inverter switches. In the latest literature, PV GCI is used for mitigating current related PQ problems, and it is also used for mitigating minor voltage related PQ problems (voltage sag, voltage swell, and voltage imbalance). During voltage sag conditions, GCI output current is high enough to maintain rated voltage at the point of common coupling (PCC) and in this case the reference dc voltage requirement is high. But, during rated grid voltage condition, low power generation from PV, and minimum load condition keeping maximum dc voltage at the input of GCI leads to heavy burden on GCI switches. In the proposed method, in order to reduce losses in GCI, the input dc voltage of GCI is reduced during low GCI output current. The proposed method is validated with MATLAB simulation and hardware experiment by comparing data existing in literature with the proposed method.

Observer-based adaptive dynamic sliding mode control for automatic clutch position tracking

The automatic clutch’s precise and stable position tracking is critical in automated manual transmission, significantly influencing vehicle performance. Clutch position control is challenging due to directly unmeasurable clutch output position, nonlinear characteristics, parameter uncertainties, and external disturbance of the automatic clutch system. This paper proposes an observer-based adaptive dynamic sliding mode control strategy to overcome these obstacles to the clutch position tracking process. The extended state observer (ESO) introduced in the designed strategy handles total disturbance, including nonlinearities and uncertainties for feedback control and total compensation. A sigmoid tracking differentiator arranges the transient process and smooth approach signal for the reference input and its differential signal. An adaptive dynamic sliding mode controller acts as the primary feedback control to realize fast and precise position tracking of the automatic clutch system based on the signal from ESO. Simulation and hardware-in-loop (HIL) experimental tests verify the effectiveness and advantage of the proposed control strategy for the clutch position tracking performance in the face of parameter perturbation and external disturbance, for example, the root mean square value of static tracking error of the designed strategy is 14.9% and 24.7% lower than that of ESO-based sliding mode control and robust sliding mode control strategy in the HIL test, respectively.

Hybrid input shaping and fuzzy logic‐based position and oscillation control of tower crane system

AbstractEffective control of the tower crane system (TCS) is crucial for the safe and quick transport of goods from one point to another in industries and construction sites. However, the existing literature either depends on the dynamic model of the system, which is prone to errors and assumptions, or requires the feedback of the states to be controlled, which can be costly and or complex. In particular, the TCS has many states and is highly nonlinear. Thus, a non‐model‐based control approach that depends on minimal feedback sensors is needed. The primary contribution of this work is that the potential hybrid configurations of the input shaping control (ISC) and fuzzy logic control (FLC) were proposed and investigated. The study provides the best hybrid configuration of the ISC and FLC (non‐model‐based controllers) for optimal positioning and anti‐swing control of the TCS. Three configurations of the ISC + FLC, namely shaper as reference input (SARI), shaper as input to the FLC (SAI2F), and shaper as input to the plant (SAI2P) were investigated to assess the optimal hybrid configuration of the ISC + FLC. The results demonstrated that the hybrid ISC + FLC scheme had improved the response of ISC by at least 150% and enhanced the oscillation reduction of FLC by 72%. Finally, these analyses showed that the ISC + FLC could achieve reasonable control of the tower crane by only considering the output of one state (position). This makes the control scheme cheaper and reduces the complexity and computational time compared to other full‐state feedback controllers.

The Design of a Low-Noise, High-Speed Readout-Integrated Circuit for Infrared Focal Plane Arrays

This paper describes the design of a low-noise, high-speed readout-integrated circuit for use in InGaAs infrared focal plane arrays, and analyzes the working principle and noise index of the pixel circuit in detail. The design fully considers the dynamic range, noise, and power consumption of the pixel circuit in which a capacitance transimpedance amplifier structure is adopted as the input stage circuit, and chip fabrication via an XFAB 0.18 µm CMOS process is successfully realized. The ROIC adopts monolithic integration and implements various functions, such as windowing, subsampling, and different integration and readout modes. The ROIC reached an array scale of 32 × 32, a frame rate of 100 Hz, and a readout rate of 20 Mbps with an analog power consumption of less than 52 mW. The measurement results show that the input reference noise can be reduced to 143 e- via the CDS, and the fully customized scheme has certain advantages in the research of high-performance ROICs.

Movienet: Deep space-time-coil reconstruction network without k-space data consistency for fast motion-resolved 4D MRI.

To develop a novel deep learning approach for 4D-MRI reconstruction, named Movienet, which exploits space-time-coil correlations and motion preservation instead of k-space data consistency, to accelerate the acquisition of golden-angle radial data and enable subsecond reconstruction times in dynamic MRI. Movienet uses a U-net architecture with modified residual learning blocks that operate entirely in the image domain to remove aliasing artifacts and reconstruct an unaliased motion-resolved 4D image. Motion preservation is enforced by sorting the input image and reference for training in a linear motion order from expiration to inspiration. The input image was collected with a lower scan time than the reference XD-GRASP image used for training. Movienet is demonstrated for motion-resolved 4D MRI and motion-resistant 3D MRI of abdominal tumors on a therapeutic 1.5T MR-Linac (1.5-fold acquisition acceleration) and diagnostic 3T MRI scanners (2-fold and 2.25-fold acquisition acceleration for 4D and 3D, respectively). Image quality was evaluated quantitatively and qualitatively by expert clinical readers. The reconstruction time of Movienet was 0.69 s (4 motion states) and 0.75 s (10 motion states), which is substantially lower than iterative XD-GRASP and unrolled reconstruction networks. Movienet enables faster acquisition than XD-GRASP with similar overall image quality and improved suppression of streaking artifacts. Movienet accelerates data acquisition with respect to compressed sensing and reconstructs 4D images in less than 1 s, which would enable an efficient implementation of 4D MRI in a clinical setting for fast motion-resistant 3D anatomical imaging or motion-resolved 4D imaging.

Composite nonlinear feedback control of a DC-DC boost converter under input voltage and load variation

Voltage boost converters are one of the most important components of DC microgrids, since they are used to enhance the voltage of naturally intermittent energy sources such as solar panels in order to feed unknown demands. In this work, a novel tuning algorithm for Composite Nonlinear Feedback (CNF) is studied in depth to improve transient performance and address output voltage regulation for a DC-DC boost converter in the presence of DC input uncertainty. The proposed CNF controller comprises both linear and nonlinear feedback terms. The linear part contributes to the stability and output tracking with a small damping ratio and a quick response. The nonlinear part, i.e., damping term, reduces the overshoot stemming from the linear feedback law and increases the damping ratio of the overall closed-loop system. The nonlinear part is automatically tuned whereby the transient performance of the DC-DC boost converter improves significantly. To assess the performance of the proposed technique, a boost converter is simulated in MATLAB Simulink considering different scenarios such as changing load, DC input, and voltage reference. The numerical results demonstrate that the tuned CNF controller outperforms the linear controller in the DC boost converter. Additionally, several experiments are conducted to validate the efficacy of the suggested technique.

Adaptive noise cancelling for an AUV-mounted passive inverted USBL array

Noise interference of an autonomous underwater vehicle (AUV) is a critical factor affecting the performance of AUV-mounted sonar payloads, especially for passive acoustic systems. Adaptive noise cancellers (ANCs) are used to eliminate noise in many scenarios for signal enhancement. However, a conventional ANC uses a primary sensor to get the data and a secondary sensor to get correlated reference noise input, which adds complexity to the AUV-mounted sonar systems. In this paper, a modified ANC is proposed to improve the performance of an AUV-mounted passive inverted ultra-short baseline (piUSBL) positioning system receiver. Unlike the conventional ANC, the reference input of this ANC is not the noise obtained using a secondary sensor; instead, the transmitted source signal is used as the reference signal, independent of the noise characteristics. The performance of the ANC is thoroughly evaluated using the field navigation data collected from an AUV sea trial. Post-processing results indicate that the ANC can effectively improve the beamforming performance of the piUSBL array, suppressing the beamformed power of the AUV noise by up to 13.8 dB. To our knowledge, this work is the first ANC study for piUSBL, which is of great significance for the further development of piUSBL.

Development of nuclear de-excitation model EBITEM Ver.2

ABSTRACT The gamma de-excitation model of the general-purpose radiation transport code Particle and Heavy Ion Transport code System, called the Evaluated Nuclear Structure Data File (ENSDF)-Based Isomeric Transition and isomEr production Model (EBITEM) has been upgraded with a focus on precise neutron-capture reaction simulation. The first de-excitation subsequent to neutron capture of numerous nuclei, which was formerly simulated by a model based on the single particle model, is calculated using the Evaluated Gamma Activation File. The database used for further de-excitation, ENSDF, retrieved in 2013, was replaced with Reference Input Parameter Library 3 to consider internal conversion. The internal conversion process was interfaced with the atomic de-excitation model to assess the emission of Auger electrons and fluorescent X-rays. The spectra of gamma-rays from neutron-capture reactions calculated by the upgraded EBITEM correlate better with the evaluated cross-section data than those of the previous version.

Research on the control strategy of interlinking converters for photovoltaic storage hybrid microgrid

This article mainly solves the problem of accurate power distribution and stable running in the photovoltaic storage hybrid microgrid and studies different control strategies of the interlinking converter connected to the AC-DC subnet under on-grid and off-grid conditions. The relationship between DC-side voltage, active power and active current is analyzed in the on-grid, and the DC voltage stability is supported by using a closed-loop voltage and current; in the off-grid mode, an improved bidirectional sag control method based on unitization processing is adopted, in which the power to be transmitted by the converter is differed from the actual value as the reference input of the current loop on the traditional double sag control, which can coordinate the power transmission between subgrids more precisely; And the action threshold is designed for the problem of repeated switching of converter operating modes. The results of simulation show that the converter able effectively to judge the magnitude and power direction in both parallel and off-grid operation modes, which ensures the normal operation of the important loads inside the subnets on both sides, thus verifying the feasibility of the control method.

Computing Phylo- k-Mers.

Finding the correct position of new sequences within an established phylogenetic tree is an increasingly relevant problem in evolutionary bioinformatics and metagenomics. Recently, alignment-free approaches for this task have been proposed. One such approach is based on the concept of phylogenetically-informative k-mers or phylo- k-mers for short. In practice, phylo- k-mers are inferred from a set of related reference sequences and are equipped with scores expressing the probability of their appearance in different locations within the input reference phylogeny. Computing phylo- k-mers, however, represents a computational bottleneck to their applicability in real-world problems such as the phylogenetic analysis of metabarcoding reads and the detection of novel recombinant viruses. Here we consider the problem of phylo- k-mer computation: how can we efficiently find all k-mers whose probability lies above a given threshold for a given tree node? We describe and analyze algorithms for this problem, relying on branch-and-bound and divide-and-conquer techniques. We exploit the redundancy of adjacent windows of the alignment to save on computation. Besides computational complexity analyses, we provide an empirical evaluation of the relative performance of their implementations on simulated and real-world data. The divide-and-conquer algorithms are found to surpass the branch-and-bound approach, especially when many phylo- k-mers are found.

Optimal tracking in two-degree-of-freedom control systems: Coupled tank system

This article presents an optimal design of a two-degree-of-freedom (2-DoF) controller that will lead to zero asymptotic steady-state tracking error. The reference inputs are chosen from the set of steps, ramps, and other persistent signals used currently. The main idea is to transform the tracking 2-DoF problem into an equivalent state-space feedback-control synthesis one. Where, an internal model of the reference input is introduced. Then, through the linear quadratic regulator (LQR) technique, the desired performance objectives are addressed by minimizing a quadratic cost function. Finally, the computed state-feedback optimal gains are linked to the polynomials used within the 2-DoF formalism. The fundamental aspect of the design is that it only utilizes the measurable information of the plant provided by its inputs and outputs and take advantage of efficient state-space numerical algorithms. The proposed method is applied to a coupled-tank system, the results achieved confirm the effectiveness of the approach.

Speed sensorless Adaptive Power Control for photovoltaic-fed water pump using Extended Kalman–Bucy filter

In this study, a speed sensorless control method is proposed for a photovoltaic water-pump system operating under variable atmospheric conditions. The developed system not only continuously determines the maximum power point of the photovoltaic system but also generates a reference speed appropriate for each power value produced. The MATLAB/Simulink model of the driver system incorporates Adaptive Power Control, Direct Torque Control, a 3-phase induction motor, and the power plant. The determination of the maximum power point of the photovoltaic system and the input reference speed information for the Direct Torque Control under varying atmospheric conditions is accomplished through the application of the Adaptive Power Control algorithm. Notably, the control process operates as a closed-loop system without the requirement of a speed sensor. Instead, the Extended Kalman–Bucy estimator is employed for speed estimation. Empirical evaluation of the proposed method was conducted under constant temperature conditions and varying irradiance values. The results clearly illustrate the consistent operation of the motor, with a constant torque production aligned with each identified maximum power point corresponding to distinct irradiance levels. The control system demonstrates robust performance and operational efficiency across the entire range of operating points. The efficacy of the Kalman estimator in monitoring the reference speed, the utilization of a single solar radiation sensor, and the successful implementation of sensorless operation are significant advantages of the developed adaptive approach. The demonstrated performance of the proposed system showcases its potential for enhancing the efficient and reliable control of photovoltaic water-pump systems in real-world applications.

Robust tracking control for uncertain fuzzy systems with time delay and external disturbances

AbstractIn this article, robust tracking and disturbance rejection problem for Takagi–Sugeno fuzzy systems with time delay and external disturbances are discussed. Specifically, proportional‐integral controller with an enhanced equivalent‐input‐disturbance technique is constructed to force the output trajectories to track the bounded reference input signal even in the presence of external disturbances. Further, the resulting fuzzy control system can be represented as an augmented system with state delay and uncertainties and the output tracking problem is transformed into stabilization problem of the augmented system. In the stabilization analysis, the considered fuzzy system does not share the same membership functions with the proposed control. Moreover, the delay‐dependent stabilization criteria for the addressed fuzzy system are presented in the form of linear matrix inequalities by the virtue of augmented Lyapunov–Krasovskii functional. To be specific, the symmetric matrices involved in the Lyapunov–Krasovskii functional need not be positive definite. Ultimately, three numerical examples are offered to support the validity of the established theoretical results.

Recursive d-step-ahead predictive control of MIMO nonlinear systems with input time-delay via multi-dimensional Taylor network extended from PID

In this paper, a recursive d-step-ahead predictive control scheme based on multi-dimensional Taylor network (MTN) is proposed for the real-time tracking control of multiple-input multiple-output (MIMO) nonlinear systems with input time-delay. The MTN predictive model is designed using a recursive approach to compensate the influence of time-delay, and an extended Kalman filter (EKF) is applied as its learning algorithm. An MTN controller is developed based on a proportional–integral–derivative (PID) controller where the closed-loop errors between the reference input and the system output are set as the MTN controller’s inputs. Then, a back propagation (BP) algorithm, designed to update its weights according to errors caused by system uncertainty, is used as a learning algorithm for the MTN controller. Meanwhile, the convergence of the MTN predictive model and the stability of the closed-loop system are evaluated. Two numerical examples and a practical example – continuous stirred tank reactor (CSTR) process are presented to verify the superiority of the proposed scheme. The experimental results and the computational complexity analysis show that the proposed scheme is effective, promising its desirable robustness, anti-disturbance, tracking and real-time performance.

Development of DSP-based TPS fully digital correction magnet power supply

The Taiwan Photon Source (TPS) is a third-generation 3 GeV synchrotron accelerator light source. After successfully operating for ten years since its first light in 2013, various subsystems are undergoing updates. In the context of magnet power supply upgrades, the trend toward digitization and high-precision modulation control is driving advancements worldwide. This study focuses on developing a fully digital correction magnet power supply (FDCMPS) based on a digital signal processor (DSP). The prototype utilizes a low-power, floating-point DSP with multiple communication functionalities as the core control unit. The output current is converted into digital values using current sensors and high-precision analog-to-digital converters. Discrete PI compensator algorithms are implemented within the DSP to generate pulse-width modulation (PWM) waveforms, driving a full-bridge (H-bridge) converter configuration with metal-oxide-semiconductor field-effect transistors (MOSFET). This forms a complete, fully digital closed-loop current control system. A virtual control interface is designed to operate the FDCMPS state. The control loop design of the prototype has been validated and demonstrates stable output bipolar current performance. When tested with a 0.1 V input reference signal, the prototype achieves a -3 dB bandwidth of 2.03 kHz. Finally, a hardware prototype circuit was constructed in the power supply laboratory, with an input voltage of 48 V, an output current of 10 A, and a maximum power of 400 W. Overall, the developed fully digital correction magnet power supply prototype showcases stable and high-performance output bipolar current performance. The system achieves total harmonic distortion of output current ripple within 0.3 mA peak to peak and long-term stability within ± 15 ppm. The successful implementation of the prototype establishes a solid foundation for advancing magnet power supply technology at the TPS.

Distributed tracking control for heterogeneous multi-agent systems via data-driven parameterisation approach

The distributed tracking control problem for heterogeneous multi-agent systems with unknown system dynamics is investigated. The objective is to provide a data-driven distributed tracking control protocol that ensures tracking performance between agents and the leader. To this end, the concept of data informativity for matching conditions is introduced. Then, the data-based sufficient and necessary conditions to achieve state tracking are provided. Meanwhile, a data-driven parameterisation approach for designing the distributed tracking control protocol is given. Compared with previous results, the reference input is considered in the leader's dynamics, and the computational burden is reduced by solving a set of data-based equations and inequality constraints rather than iteration. Additionally, the developed results are still appropriate for handling the tracking control issue of the single linear system, and the current constraint that the reference system be stable is eased. Finally, two simulation examples are given to verify the proposed schemes' effectiveness.