Tuning Method Research Articles

DEBCM: Deep Learning-Based Enhanced Breast Invasive Ductal Carcinoma Classification Model in IoMT Healthcare Systems.

Accurate breast cancer (BC) diagnosis is a difficult task that is critical for the proper treatment of BC in IoMT (Internet of Medical Things) healthcare systems. This paper proposes a convolutional neural network (CNN)-based diagnosis method for detecting early-stage breast cancer. In developing the proposed method, we incorporated the CNN model for the invasive ductal carcinoma (IDC) classification using breast histology image data. We have incorporated transfer learning (TL) and data augmentation (DA) mechanisms to improve the CNN model's predictive outcomes. For the fine-tuning process, the CNN model was trained with breast histology image data. Furthermore, the held-out cross-validation method for best model selection and hyper-parameter tuning was incorporated. In addition, various performance evaluation metrics for model performance assessment were computed. The experimental results confirmed that the proposed model outperformed the baseline models across all evaluation metrics, achieving 99.04% accuracy. We recommend the proposed method for early recognition of BC in IoMT healthcare systems due to its high performance.

Research on dynamic PI parameter tuning of double-fed wind turbine based on ant colony algorithm

Considering the drawbacks of flexible adjustment of PI controller control parameters in the constant pressure control system of doubly fed fans, a PI controller control parameter flexible adjustment method considering ant colony optimization algorithm (ACO) is proposed. This method uses the proportional coefficient and integration time parameters in the PI controller as the ants in the ant colony optimization algorithm, and the ultimate optimization goal is to control the absolute error integration function. During the control process, the parameters of the PI controller are dynamically adjusted. When the electrified wire netting IR-drop and wind velocity changes, a comparative analysis of the dynamic tuning PI controller parameters and the non-dynamic tuning method was conducted. At last, the simulation studies have shown that the constant voltage control system using the PI parameter Flexible adjustment control method found on ACO can rapidly improve the grid voltage stability of double-fed wind turbines and reduce response time.

A Small-Signal Stability Analysis Method Based on Minimum Characteristic Locus and Its Application in Controller Parameter Tuning

A small-signal stability analysis method based on minimum characteristic locus (MCL) was recently proposed by the authors. The method is found to be particularly useful in analyzing various oscillation modes in a unified way. The present work continues this line of research. After providing a brief review of the basic principle of MCL method, the paper proceeds to show the mathematical relationship between the stability margin obtained using an MCL method, and that obtained by traditional modal analysis method. Next, a sensitivity analysis procedure is proposed to study quantitatively the effects of control parameters on the stability of the system. Third, the properties of the so-called exciter mode are explained in detail, in particular, explicit formulas of exciter mode frequency and power system stabilizer (PSS) critical gain are derived. Finally, taking PSS4B as an example, a controller parameter tuning method is proposed. The effectiveness and practicability of the proposed method are verified by case studies of Kundur's four-machine-two-area system and China's Yunnan power grid.

Tuning methods for multigap drift tube linacs.

Multigap cavities are used extensively in linear accelerators to achieve velocities up to a few percent of the speed of light, driving nuclear physics research around the world. Unlike for single-gap structures, there is no closed-form expression to calculate the output beam parameters from the cavity voltage and phase. To overcome this, we propose to use a method based on the integration of the first and second moments of the beam distribution through the axially symmetric time-dependent fields of the cavity. A beam-based calibration between the model's electric field scaling and the machine's rf amplitudes is presented, yielding a fast online energy change method, returning cavity amplitude and phase necessary for a desired output beam energy and energy spread. The method is validated with 23Na6+ beam energy measurements.

Reconfigurable integrated photonic filters for optical signal processing using a silicon photonic platform.

We present a systematic photonic filter design approach by deploying pole-zero optimization. The filter transfer function is derived from its specifications by formulating closed-form optimization objective functions and subsequently translating them into optical design parameters. Two distinct filter examples, namely Chebyshev and elliptic filters, are considered for the design and validation. A compact reconfigurable three-pole photonic filter is fabricated on a silicon photonic platform to illustrate the proposed design technique including transmission tunability. Integrated thermal phase shifters coupled with micro-ring resonators are used to reconfigure filter responses. A well-matched experimental demonstration is presented to validate the proposed tuning method. We achieved a sharp out-of-band edge rejection of at least 20 and 40 dB for the elliptic and Chebyshev filter, respectively.

Research and Analysis of IndoBERT Hyperparameter Tuning in Fake News Detection

The rapid advancement of communication technology has transformed how information is shared, but it has also brought concerns about the proliferation of false information. A recent report by the Ministry of Communication and Informatics in Indonesia revealed that around 800,000 websites were involved in spreading false information, underscoring the seriousness of the problem. To combat this issue, researchers have focused on developing techniques to detect and combat fake news. This research centers on using IndoBERT-base-p1 for fake news detection and aims to enhance its performance through three methods to tune the hyperparameter value of the model namely: Bayesian optimization, grid search, and random search. After comparing the outcomes of the three hyperparameter tuning methods, Bayesian Optimization emerged as the most effective approach. Achieving a precision of 88.79%, recall of 94.5%, and F1-score of 91.56% for the “fake” label, Bayesian Optimization outperformed the other hyperparameter tuning methods as well as the model using the fine-tuning hyperparameter value. These findings emphasize the importance of hyperparameter tuning in improving the accuracy of fake news detection models. Utilizing Bayesian Optimization and optimizing the specified hyperparameters, the model demonstrated superior performance in accurately identifying instances of fake news, providing a valuable tool in the ongoing battle against disinformation in the digital realm.

A real-time patient-specific treatment strategy for enhanced external counterpulsation.

Diastolic/systolic blood pressure ratio (D/S) ≥ 1.2 is the gold standard of enhanced external counterpulsation (EECP) treatment, but it does not show a clear clinical correspondence with the configuration of the EECP mode. As such, a single target results in different treatment effects in different individuals. The local haemodynamic effect (wall shear stress, WSS) of EECP on vascular endothelial cells is conducive to promote the growth of collateral circulation vessels and restore the blood supply distal to the stenosis lesion. Considering the haemodynamic effects of WSS on human arteries, this study developed a real-time patient-specific treatment strategy of EECP for patients with cardio-cerebrovascular diseases. Based on patient-specific haemodynamic data from 113 individuals, an optimization algorithm was developed to achieve the individualization of a 0D lumped-parameter model of the human circulatory system, thereby simulating the patient-specific global haemodynamic effects. 0D/3D coupled cardio-cerebrovascular models of two subjects were established to simulate the local WSS. We then established statistical models to evaluate clinically unmeasurable WSS based on measurable global haemodynamic indicators. With the aim of attaining appropriate area- and time-averaged WSS (ATAWSS, 4-7 Pa), as evaluated by global haemodynamic indicators, a closed-loop feedback tuning method was developed to provide patient-specific EECP treatment strategies. Results showed that for clinical data collected from 113 individuals, the individualized 0D model can accurately simulate patient-specific global haemodynamic effects (average error <5%). Based on two subjects, the statistical models can be used to evaluate local ATAWSS (error <6%) for coronary arteries and for cerebral arteries. An EECP mode planned by the patient-specific treatment strategy can promote an appropriate ATAWSS within a 16 s calculation time. The real-time patient-specific treatment strategy of EECP is expected to improve the long-term outcome for each patient and have potential clinical significance.

Reaction Curve-Assisted Rule-Based PID Control Design for Islanded Microgrid

In a renewable energy-based islanded microgrid system, frequency control is one of the major challenges. In general, frequency oscillations occur in islanded microgrids due to the stochastic nature of load and variable output power of distributed generating units (DGUs). In the presented research proposal, frequency oscillations are suppressed by implementing the proportional integral derivative (PID) controller-based control design strategy for an islanded microgrid. The modeling of the islanded microgrid is firstly presented in the form of a linearized transfer function. Further, the derived transfer function is approximated into its equivalent first-order plus dead time (FOPDT) form. The approximated FOPDT transfer function is obtained by employing the reaction curve method to calculate the parameters of the FOPDT transfer function. Furthermore, the desired frequency regulation is achieved for the manifested FOPDT transfer function by incorporating PID control design. For PID controller tuning, different rule-based methods are implemented. Additionally, comparative analysis is also performed to ensure the applicability of the comparatively better rule-based tuning method. The Wang–Chan–Juang (WCJ) method is found effective over other rule-based tuning methods. The efficacy of the WCJ method is proved in terms of transient response and frequency deviation. The tabulated data of tuning parameters, time domain specifications, and error indices along with responses are provided in support of the presented control strategy.

Constructing Built-In Electric Field in NiCo2O4-CeO2 Heterostructures to Regulate Li2O2 Formation Routes at High Current Densities.

Developing catalysts with suitable adsorption energy for oxygen-containing intermediates and elucidating their internal structure-performance relationships are essential for the commercialization of Li-O2 batteries (LOBs), especially under high current densities. Herein, NiCo2O4-CeO2 heterostructure with a spontaneous built-in electric field (BIEF) is designed and utilized as a cathode catalyst for LOBs at high current density. The driving mechanism of electron pumping/accumulation at heterointerface is studied via experiments and density functional theory (DFT) calculations, elucidating the growth mechanism of discharge products. The results show that BIEF induced by work function difference optimizes the affinity for LiO2 and promotes the formation of nano-flocculent Li2O2, thus improving LOBs performance at high current density. Specifically, NiCo2O4-CeO2 cathode exhibits a large discharge capacity (9546mAhg-1 at 4000mAg-1) and high stability (>430 cycles at 4000mAg-1), which are better than the majority of previously reported metal-based catalysts. This work provides a new method for tuning the nucleation and decomposition of Li2O2 and inspires the design of ideal catalysts for LOBs to operate at high current density.

Thermally tunable binary-phase VO2 metasurfaces for switchable holography and digital encryption

Abstract Metasurface holography has aroused immense interest in producing holographic images with high quality, higher-order diffraction-free, and large viewing angles by using a planar artificial sheet consisting of subwavelength nanostructures. Despite remarkable progress, dynamically tunable metasurface holography in the visible band has rarely been reported due to limited available tuning methods. In this work, we propose and numerically demonstrate a thermally tunable vanadium dioxide (VO2) nanofin based binary-phase metasurface, which generates holographic information in the visible varying with temperature. The insulator-to-metal phase transition in VO2 nanofins allows two independent binary-phase holograms generated by machine learning to be encoded in the respective phases of VO2 and switched under thermal regulation. By elaborately designing the dimensions and compensated phase of VO2 nanofins, high-quality images are reconstructed at corresponding temperatures under appropriate chiral illumination. In contrast, much poorer images are produced under inappropriate chiral illumination. We further demonstrate the advantage of applying the VO2 phase-compensated metasurface in high-security digital encryption, where two desired character combinations are read out with appropriate excitations and temperatures, whereas one identical fraudulent message is received with inappropriate excitations. Our design approach offers a new and efficient method to realize tunable metasurfaces, which is promisingly adopted in dynamic display, information encryption, optical anti-counterfeiting, etc.

Feasibility study of a method for tuning wave energy converters

A Wave Energy Converter (WEC) cannot operate efficiently if left alone floating to the mercy of the random sea surface. For a WEC to be efficient, its natural frequency should be close to the peak frequency of the local dominant waves. This paper introduces a method for tuning any natural frequency of a WEC to the peak frequency of a wave spectrum and converting dynamic responses into mechanical power. An innovative lightweight and dual-drag force subsea structure with a huge amount of entrapped seawater can be attached to any vessel using cables. This structure increases the roll mass moment of inertia of a medium size barge, and the mass of a small heaving floater, reducing their natural frequencies. The tension in the cables is converted into mechanical power. The study focuses on the Galápagos Islands, where swells with a typical 13 s peak period and significant wave height between 1 to 3 m dominate the wave climate. For the dynamic systems based on roll and heave responses, annual averages of mechanical power are 178 and 73 kW with efficiencies of 49 and 67% respectively. The method developed in this paper can improve the efficiency of existing and novel WECs.

Dynamic light manipulation via silicon-organic slot metasurfaces

Active metasurfaces provide the opportunity for fast spatio-temporal control of light. Among various tuning methods, organic electro-optic materials provide some unique advantages due to their fast speed and large nonlinearity, along with the possibility of using fabrication techniques based on infiltration. In this letter, we report a silicon-organic platform where organic electro-optic material is infiltrated into the narrow gaps of slot-mode metasurfaces with high quality factors. The mode confinement into the slot enables the placement of metallic electrodes in close proximity, thus enabling tunability at lower voltages. We demonstrate the maximum tuning sensitivity of 0.16nm/V, the maximum extinction ratio of 38% within ± 17V voltage at telecommunication wavelength. The device has 3dB bandwidth of 3MHz. These results provide a path towards tunable silicon-organic hybrid metasurfaces at CMOS-level voltages.

Mechanical resonance suppression of the high-speed parallel robot based on fractional order disturbance observer

Considering the flexibility of the transmission shaft system, this paper presents an approach for mechanical resonance suppression of the high-speed parallel robot based on fractional order disturbance observer. First, in order to evaluate mechanical resonance, a decoupled mechatronic dynamics model is built. Based on the proposed decoupled dynamics model, the mechanical resonance under different influence factors is analyzed. Then, based on the three closed-loop control structure of servo system, a model-based parameter tuning method is adopted in the controller parameter tuning. Finally, inspired by the traditional disturbance observer, a fractional order disturbance observer is established by introducing a fractional order filter. Results show that due to the flexibility of the transmission shaft system, under the combined action of mechanical disturbance torque and electromagnetic driving torque, the joint transmission system will generate mechanical resonance phenomena. Therefore, this paper proposes a method for the mechanical resonance suppression of the high-speed parallel robot based on the fractional order disturbance observer. And the proposed method can be applied to other mechatronic device including flexible transmission shaft system.

Fractional PID with Genetic Algorithm Approach for Industrial Tank Level Control Process

Process control is used in various types of industries to boost production while using current resources, product quality, and safety, with level control being one of the most important schemes. It is suggested that study be conducted on nonlinear continuous processes, particularly in process control applications such as conical tank level control. Initially, each process receives one set of Proportional-Integral (PI) controller settings and a First Order Plus Dead-Time (FOPDT) model using the Ziegler Nicholas (ZN) step response tuning method. The numerous FOPDT models and parameter sets are also obtained. Responses obtained with a single set of parameters and responses obtained with many sets of parameters are compared. By creating a Fractional PID Controller (FPID) with Genetic Algorithm (GA), a simulation-based tuning strategy is proposed. The step responses are acquired through experimental research using fine-tuned settings. At most operational points, the Fractional PID Controller with Genetic Algorithm-based tuning approach outperforms, with lowest oscillation, extremely tiny overshoot, minimum average ISE, and minimum average IAE. The proposed FPID with GA method provides better setpoint and regulatory tracking performance compared to ZN-PID.

Linear Matrix Inequality-Based Robust Model Predictive Speed Control for a Permanent Magnetic Synchronous Motor with a Disturbance Observer

In this paper, a linear matrix inequality (LMI)-based robust model predictive speed control (RMPSC) with a disturbance observer (DOB) is proposed to guarantee stability and control performance against the parameter uncertainty and disturbance of a permanent magnetic synchronous motor (PMSM). All external torques applied to the PMSM are defined as disturbance, estimated by the DOB, and used to construct the RMPSC method. The proposed DOB and RMPSC are determined by a multiple LMI-based optimization approach. Furthermore, parameter uncertainty within a certain range, due to manufacturing errors or aging deterioration, is considered and a systematic tuning method is proposed to obtain the optimal gains. Finally, an offline optimization method is developed that ensures a low computational load to enable real-time processing. Simulation results demonstrate the effectiveness and validity of the proposed control method.

Remote tele‐operation using model reference discrete‐time sliding mode control

AbstractIn this article, a dissipativity based discrete time sliding mode controller is proposed for bilateral tele‐operation in presence of communication delays and packet losses. The controllers for both master and slave arm are designed to follow a predefined impedance dynamics with dissipative characteristics. The slave arm controller is designed as a two layered structure. The first layer uses the tracking error between master and slave to create a target velocity profile based on the user defined impedance dynamics. The second layer uses this target velocity profile, slave motion and the contact forces to design a reaching law based discrete time sliding mode controller. A model following reaching law approach is used to design the sliding mode control which alleviates the chattering in the input by removing the impact of the accumulated effects of the past disturbance from the system. Moreover, an adaptive tuning method is used for the switching gain of the sliding mode control so that the controller can be designed even when exact information on the uncertainty bounds are unknown. Numerical simulations are presented for Phantom Omni arm to show the efficacy of the proposed method.

Actuators for Improving Robotic Arm Safety While Maintaining Performance: A Comparison Study

Since robotic arms operating close to people are becoming increasingly common, there is a need to better understand how they can be made safe when unintended contact occurs, while still providing the required performance. Several actuators and methods for improving robot safety are studied and compared in this paper. A robotic arm moving its end effector horizontally and colliding with a person’s head is simulated. The use of a conventional electric actuator (CEA), series elastic actuator (SEA), pneumatic actuator (PA) and hybrid pneumatic electric actuator (HPEA) with model-based controllers are studied. The addition of a compliant covering to the arm and the use of collision detection and reaction strategies are also studied. The simulations include sensor noise and modeling error to improve their realism. A systematic method for tuning the controllers fairly is proposed. The motion control performance and safety of the robot are quantified using root mean square error (RMSE) between the desired and actual joint angle trajectories and maximum impact force (MIF), respectively. The results show that the RMSE values are similar when the CEA, SEA, and HPEA drive the robot’s first joint. Regarding safety, using the PA or HPEA with a compliant covering can reduce the MIF below the safety limit established by the International Organization for Standardization (ISO). To satisfy this ISO safety limit with the CEA and SEA, a collision detection and reaction strategy must be used in addition to the compliant covering. The influences of the compliant covering’s stiffness and the detection delay are also studied.

Optimal design of I-PD controller for disturbance rejection of time delayed unstable and integrating-unstable processes

Disturbance rejection has always been a major phenomenon in control theory. Disturbances that arise in control of unstable or integrating unstable processes with time delay present considerable difficulties for classical PID controllers. This paper supplies analytical tuning rules, derived from optimum disturbance rejection responses to minimise the error signal according to several integral performance criteria to identify the tuning parameters of the I-PD controller. The provided analytical rules offer the advantage of calculating controller parameters without the necessity of employing an optimisation algorithm. This simplifies the tuning process and allows for a straightforward determination of the controller's parameters, making it more convenient and efficient for practical implementation in control systems. Comprehensive simulations were performed to validate the effectiveness of the proposed I-PD controller in terms of disturbance rejection responses, control signals, perturbation in process parameters, measurement noises, TV values, Ms values, and integral performance indicators. Overall, the outcomes demonstrate that the introduced method for the tuning of I-PD controllers offers notable advantages when compared to other tuning methods found in the literature.

Utilization of cage germoxanes as templates for tuning pore characteristics of siloxane-based materials

Abstract We demonstrate the utilization of cage germoxanes as templates for tuning the pore characteristics of siloxane-based materials. Molecular-scale composites of cage germoxanes and cage siloxanes were prepared by hydrosilylation reactions between SiH- and vinyl-modified cage siloxanes in the presence of vinyl-modified cage germoxanes. Subsequent acid treatments selectively removed the germoxane moiety, resulting in variation in the pore structures. These results contribute to developing a novel method for tuning the pore characteristics of siloxane-based nanoporous materials.

Gate-controlled gain tuning of fully depleted silicon-on-insulator-based 1 T pixel for in-sensor white balance

White balance (WB) is a critical back-end processing function in image sensors to keep color constancy under various lighting conditions by adjusting the RGB color channel gain values. In this work, we proposed a novel gate-controlled gain-tuning method for a fully depleted silicon-on-insulator (FDSOI) one-transistor (1 T) pixel to achieve WB inside the sensor. Based on the pixel structure of a p-well under the buried oxide for sensing and an n-type nMOSFET on the top for readout, the 1 T pixel output gain is modulated by the MOSFET gate according to the transistor transfer characteristics. About 5x gain modulation range in RGB spectrum photoresponse (nonlinearity < 3%) is experimentally demonstrated in the devices fabricated by 22 nm FDSOI-based technology. The scheme for in-sensor WB demonstration is provided with a novel 1 T pixel array design, and the evaluation result shows in-sensor WB achieving an almost equivalent performance (Delta-E deviation < 1) compared with using conventional back-end WB.