Stable Control Performance Research Articles

Smooth Pulse Number Transition Strategy Considering Time Delay in Synchronized SVPWM

In high power motor drive systems, synchronized space vector pulsewidth modulation (synchronized SVPWM) is widely used to guarantee stable control performance. Synchronized SVPWM has a characteristic that the switching frequency varies abruptly when the pulse number transitions. This article proposes a pulse number transition point at which the phase difference is minimized to remove the phase difference of the sampling point that appears during synchronized SVPWM control. In addition, for a smooth pulse number transition of synchronized SVPWM, a compensation method for the magnitude and phase error of the inverter output voltage due to the time delay and a method of removing the existing phase difference without using a phase-locked loop are proposed in consideration of the characteristic of changing switching frequency. The validity and the implementation of the proposed method are verified by experimental results using a high-power inverter driving 332 kW interior permanent magnet synchronous motor (IPMSM).

Research on motor speed control algorithm of UAV Based on Reinforcement Learning

Aiming at the hovering control problem of four-rotor UAVs, this paper proposes to use the reinforcement learning method to control the motor speed of UAVs to improve the intellectual control level of four-rotor UAVs. Firstly, two reinforcement learning algorithm models of DDPG (deep deterministic policy gradient) and PPO (proximal policy optimization) are built using the PARL framework, and the super parameters of the algorithm model are set. Secondly, the algorithms are trained and optimized to obtain scores in the RLSchool simulation environment. Finally, the performance differences between the two algorithm models in the same simulation environment are analyzed. The test and analysis results show that the two algorithms can realize the four-axis aircraft suspension control in the simulation environment. Between them, the PPO algorithm features high scores, simple and convenient parameter adjustment, stable control, and good performance.

Performance Analysis of a Robust Controller with Neural Network Algorithm for Compliance Tendon–Sheath Actuation Lower Limb Exoskeleton

Robotic rehabilitation of the lower limb exoskeleton following neurological injury has proven to be an effective rehabilitation technique. Developing assistive control strategies that achieve rehabilitative movements can increase the potential for the recovery of the motor coordination of the participants. In this paper, the innovative contributions are to investigate a robust sliding mode controller (SMC) with radials basis function neural network algorithm (RBFNN) compensator for a novel compliance tendon–sheath actuation lower limb exoskeleton (CLLE) to provide intrinsic thigh and shank rehabilitation training. The controller employing the RBFNN compensator is proposed to reduce the impact of friction from the compliance tendon–sheath actuation system (CTSA). In the design of the compensator, a single parameter is investigated to replace the weight information of the neural network. Our proposed controller is shown to yield fast, stable, and accurate control performance regardless of uncertainties interaction. Two additional algorithms, including a robust adaptive sliding mode controller (RASMC) and a sliding mode proportional-integral controller (SMPIC), are introduced in this paper for comparison. The simulations were presented with MATLAB/SIMULINK to validate the superiority of the performance of the proposed controller.

Modeling and Finite-Horizon MPC for a Boiler-Turbine System Using Minimal Realization State-Space Model

This paper aims to address a finite-horizon model predictive control (MPC) for non-linear drum-type boiler-turbine system using a system-identification method. Considering that the strong state coupling of a non-linear mechanism model, the subspace identification method is first utilized to obtain a linear state-space model, and transformed into an input–output model. By taking the inputs and outputs of the input–output model as system states, an augmented non-minimal state-space (NMSS) model of state measurable is constructed. In order to reduce the computation burden, the augmented NMSS model is further transformed into a canonical formulation by adopting a Kalman decomposition. Based on the minimal realization state-space model, the MPC controller is parameterized as a finite-horizon optimization problem. Finally, simulations are performed and evaluated the performance of the proposed method, and the simulation results show that: the linear model approximate the non-linear system accurately; the proposed MPC method can achieve a satisfactory stable control performance; and the computation time 18.388 s for the overall optimization problem also illustrates the real-time performance effectively.

Driving system for Mach-Zehnder electro-optic modulators in microwave photonics.

In order to obtain a modulation signal with high bandwidth and highly stable output power without distortion, an electro-optic modulator driving system with quick response to the input signal is designed in this paper. The system mainly includes three parts: power supply module, microwave signal generation module, and automatic gain control (AGC) module. The power supply module provides appropriate voltage and current for other two modules. The microwave signal generation module is used to generate microwave signals. The AGC module adopts the digital AGC control structure and the PID control principle to achieve stable control of the output power of the microwave signal. The hardware is developed, and the software algorithm is integrated into the driving system to verify the effectiveness and stability. The experimental results show that the bandwidth of the AGC module reaches 20 GHz. The proposed AGC module can effectively stabilize the output power of the microwave signal at 10 dBm with fluctuations less than ±1.5 dB, and its stability is improved by 74.95% compared to existing instrument. When the input power changes at 10 KHz, the system can still achieve stable control performance and has exhibited excellent dynamic response characteristics.

Review of Model Predictive Control of Distributed Energy Resources in Microgrids

In recent years, in response to increasing environmental concerns, advances in renewable energy technology and reduced costs have caused a significant increase in the penetration of distributed generation resources in distribution networks. Nonetheless, the connection of distributed generation resources to distribution networks has created new challenges in the control, operation, and management of network reliability. This article is a review on the model predictive control (MPC) for distributed energy resources (DER) in microgrids. The solutions of MPC for energy conversion of solar photovoltaic, wind, and energy storage systems are covered in detail. MPC’s applications for increasing reliability of grid-connected converters under (a)symmetrical grid faults are also discussed. The promising potentials of the applications of MPC to the stable multi-variable control performance of DERs are highlighted. This work reflects strong symmetry on MPC control strategies and provides guidance map for readers to facilitate future research works in these exciting fields.

Opening and Closing Positioning Control of the Seedling Picking-Up Mechanism Based on Fuzzy-PID Control Algorithm

The success rate of automatic transplanter seedling picking is affected by the harsh operating environment of the transplanter and the reduced output accuracy of the opening and closing positioning of the seedling-picking mechanism due to the interference of the external environment. To solve such problems, the paper proposes to use an adaptive fuzzy PID control algorithm as the opening and closing positioning-control system of the seedling-picking mechanism. Based on the theoretical analysis and calculation of the positioning accuracy of the seedling-picking mechanism, a mathematical model of stepper motor angular velocity control was established, and a stepper motor angular velocity control model based on fuzzy PID (conventional PID) control was established in MATLAB/Simulink. In order to further simulate the actual working condition of the seedling-picking mechanism, a simulation model of stepper motor control with disturbance was built, and the response results showed that the fuzzy PID control system could get rid of the disturbance faster under the action of external disturbance signals. The results of the opening and closing positioning test of the seedling-picking mechanism showed that the fuzzy PID control system has higher control accuracy and more stable control performance than the PID control system, which meets the design requirements.

Improved modeling and active disturbance rejection control of tank gun control system

In order to improve the stability control performance of the tank barrel at high speed, a new 2-degree-of-freedom nonlinear dynamics model of yaw and pitch bodies is established, taking into account the 6-degree-of-freedom motion of the tank chassis. By analyzing the direction of the tank barrel in space, the barrel stability control scheme for the tank gun control system with the arbitrary motion of the tank chassis in space is realized. The new dynamics equations of the tank gun control system are established by analytical mechanics. It effectively solves the problem of modeling methods for the tank gun control system in azimuth and elevation when considering the 6-degree-of-freedom motion of tank chassis. Then, an improved active disturbance rejection control strategy for tank gun control system is proposed. A smooth nonlinear function faln(·) is constructed to avoid the switching problem of the function fal(·) at the piecewise points. Next, an improved extended state observer is designed based on the deviation principle by means of the deviation between each state variable and its observation. Afterwards, the stability of the system is analyzed by constructing a Lyapunov function. Simulations were carried out with different input signals to verify the reliability of the dynamics model and control algorithm. The improved active disturbance rejection control has a faster response speed and smaller steady state error. The results show that the stability and tracking performance of the tank gun control system has been improved using the proposed method.

Implementation of Dynamic and Static Moisture Control in Fluidized Bed Granulation.

The application of process analysis and control is essential to enhance process understanding and ensure output material quality. The present study focuses on the stability of the feedback control system for a fluidized bed granulation process. Two strategies of dynamic moisture control (DMC) and static moisture control (SMC) were established based on the in-line moisture value obtained from the near-infrared sensor and control algorithm. The performance of these strategies on quality consistency control was examined using process moisture similarity analysis and principal component analysis. The stable moisture control performance and low batch-to-batch variability indicated that the DMC method was significantly better than other granulation methods. In addition, the investigation of robustness further showed that the implemented DMC method was able to produce predetermined target moisture values by varying process parameters. This study provides an advanced and simple control method for fluidized bed granulation quality assurance.

Flow field and sealing performance analysis of compliant foil face gas seal

Based on the theory of gas lubrication and elastic mechanics, a theoretical model of gas-elastic coupling lubrication of compliant foil face gas seal (CFFGS) is presented. The correlation between the film pressure and thickness of CFFGS and its effect on the flow field are investigated, and the differential effect of pressure conditions on the flow field and sealing performance is analyzed. Also explored the influence law of operating and structural parameters on sealing performance. Results show that CFFGS have stable and excellent leakage control performance, and the pressure forms has a differential effect on the coordination mechanism of film pressure-deformation-film thickness and the sealing performance. Moreover, compliant foil structure has a positive impact on the end-face adaptive capability and leakage control performance of the seal.

Research on Takagi-Sugeno Fuzzy-Model-Based Vehicle Stability Control for Autonomous Vehicles

Human–machine cooperative driving is an important stage in the development of autonomous driving technology. However, in emergencies, the problem of vehicle stability control for human–computer cooperative autonomous vehicles is still worthy of attention. This paper mainly realizes the stability control of the human–machine cooperative driving vehicle through active steering and considers the influence of the change of vehicle speed on the vehicle stability control performance. Therefore, a vehicle stability control method based on the superposition of steering torque is proposed, in which the Takagi-Sugeno fuzzy model is used to solve the variable parameter problem. Firstly, a vehicle system model with steering moment as input is established to ensure that the driver can participate in the steering control. Secondly, the nonlinear T-S fuzzy model is established by fuzzifying the local linear model. Then, the parallel-distributed-compensation (PDC) method is used to design the vehicle stability controller, and the asymptotic stability of the system in the range of variable parameters is proved by using the Lyapunov stability principle. Finally, the simulation and experimental results show that the control method can improve the handling stability of the human–machine cooperative driving vehicle under the condition of vehicle speed variation.

New Optimal Supply Air Temperature and Minimum Zone Air Flow Resetting Strategies for VAV Systems

Buildings account for a large portion of the total energy use in the US; therefore, improving the operation of typical variable-air-volume (VAV) systems in buildings can provide a tremendous economic opportunity. ASHRAE Guideline 36 recommends a resetting strategy for supply air temperature (SAT) for VAV systems based on outside air temperature. However, this strategy may not produce optimal performance, particularly when simultaneous cooling and heating occurs in zones. In addition, there is no strategy recommended in the Guideline to reset the zone minimum airflow set point in a single-duct VAV terminal unit with reheat, although this setpoint has a great impact on zone reheat requirements and ventilation efficiency. Thus, this paper introduces new strategies to reset both the SAT and zone minimum airflow rate set points to improve the efficiency of typical VAV systems. The strategies were tested under various conditions through experiments performed in fully instrumented VAV systems located in the HVAC lab at the University of Cincinnati. The experiments were conducted on a chilled-water VAV system that serves three controlled zones with hot-water reheat VAV boxes controlled by a typical commercial BACnet web-based building automation system BAS. The simulation studies were performed using the building energy simulation software EnergyPlus to evaluate the strategies at a larger scale in various locations. The simulation results show that the proposed resetting strategies can provide fan energy savings between 1.6% and 5.7% and heating load savings between 7.7% to 33.7%, depending on the location. The laboratory testing shows that the proposed strategies can provide stable control performance in actual systems as well as achieving the anticipated reheat and fan energy savings. The result offers significant improvements that can be implemented in the Guideline for single-duct VAV system operation and control.

Harmonic Suppression and Stability Enhancement of a Voltage Sensorless Current Controller for a Grid-Connected Inverter Under Weak Grid

This paper presents the harmonic suppression and stability enhancement of a grid voltage sensorless current controller for a grid-connected inverter under weak grid conditions. Given that inductive-capacitive-inductive (LCL) filters represented as higher-order dynamics cause resonance problems, a considerate resonance frequency damping process is required. In particular, the resonance phenomenon of the LCL filter crucially influences the current quality when the grid-connected inverter is connected to a weak grid with uncertain grid impedance and distorted harmonics. Additionally, there is a possibility that the control system will become unstable due to changes in system parameters, even after considerate resonance frequency damping. In order to solve these problems, this paper presents an active damping (AD) method by using integral variables in an integral state feedback current controller for a grid voltage sensorless inverter system, which significantly improves the current harmonics and stability of the grid-connected inverter under weak grid condition. The presented closed-loop current control scheme only requires the measurement of the injected grid currents and DC-link voltage. Compared to the traditional state feedback control methods, the reliability and robustness of the proposed control scheme are much improved even with reduced system cost. The stability and current control performance of the closed-loop system are investigated in the presence of uncertainty in the grid impedance and filter capacitor parameter under distorted grids. In order to support the theoretical analyses, the comprehensive simulation results are presented in terms of the grid current quality and control stability in an environment with both uncertain grid impedance and a distorted grid. Experimental results are also presented by using a 32-bit digital signal processor (DSP) TMS320F28335 controller for a 2 kVA grid-connected inverter to validate the feasibility of the proposed scheme practically.

A resonant damping control and analysis for LCL-type grid-connected inverter

The inverter becomes an essential part in the distributed energy units, where an inductor–capacitor–inductor (LCL) filter is an up-to-date adoption for grid interfacing. However, the challenging issue of resonance related to the LCL-filter worsens the dynamic control characteristics and produces stability threat for the voltage source inverter system. The proper design of inverter control plays a substantial part in ensuring a steady state operation and a high quality of grid injected current according to grid connection codes. This paper offers a different design method of inverter control which alters the inner damping loop structure to enhance the damping and stability features of the inverter system. In the proposed solution, a modified compensator is employed through the LCL filter network and filter capacitor current feedback loop, the resultant augmented plant’s output is then sent back at the reference point of a grid-connected inverter system to damp the unwanted resonance spike. This particular arrangement to form a damping loop is termed as parallel feedforward compensation. The damping loop is implemented by calculating the filter capacitor current, and a first order high-pass filter is employed as a damper in the suggested arrangement. Moreover, for comparative studies and analysis, the conventional filter capacitor current feedback active damping method is selected. In addition, the stability margins and control performance of the open current loop are examined under different filter parameters values. The substantial results of the suggested structure are quicker dynamic response, comparatively improved resonance damping, better tracking performance and higher delay compensation capability. A laboratory prototype is established to confirm the effectiveness of the suggested scheme on the bases of control performance and stability margins.

Stability Analysis and Impedance Reshaping Method for DC Resonance in VSCs-based Power System

With the rapid growth of renewable energy and power electronic loads, voltage source converters (VSCs) have been commonly applied in different VSCs-based power systems, which also bring in stability issues due to their power electronic characteristics. The impedance-based stability theory and corresponding reshaping method can be used to analyze and solve system stability issue. However, dc stability issue in VSCs-based power systems becomes more complicated when considering ac/dc coupling relationship. This paper proposes an improved reshaping control strategy based on the detailed impedance model considering grid impedance and control delay. The influence of grid impedance, control delay and control parameters of VSC on dc stability are further analyzed to identify the cause of potential resonance risk. The proposed impedance reshaping method considers the trade-off between stability improvement and control performance, and compensates the impacts of grid impedance and control delay at the same time. The validity of stability analysis and reshaping method is further verified through the simulation and experimental results.

Design of stepper motor driver based on STM32

In the field of industrial control, stepping has been widely used as an actuator. For this article, based on STM32F103 as the control core, the functions of start and stop, forward rotation, reverse rotation and speed regulation of the stepping motor are realized through four buttons. The system uses L293D to drive a stepper motor, LED0 and LED1 two status lights display the motor’s forward and reverse rotation status, and the digital tube displays the current stepper motor speed. The whole system includes L293D module, button module, status light module and speed display module. The whole system is modeled, theoretically analyzed and simulated based on the drive control principle of the stepper motor, and the precise and stable control performance of the system under different occasions is further verified through experiments.

Reinforcement Learning based on Deep Deterministic Policy Gradient for Roll Control of Underwater Vehicle

The existing underwater vehicle controller design is applied by linearizing the nonlinear dynamics model to a specific motion section. Since the linear controller has unstable control performance in a transient state, various studies have been conducted to overcome this problem. Recently, there have been studies to improve the control performance in the transient state by using reinforcement learning. Reinforcement learning can be largely divided into value-based reinforcement learning and policy-based reinforcement learning. In this paper, we propose the roll controller of underwater vehicle based on Deep Deterministic Policy Gradient(DDPG) that learns the control policy and can show stable control performance in various situations and environments. The performance of the proposed DDPG based roll controller was verified through simulation and compared with the existing PID and DQN with Normalized Advantage Functions based roll controllers.

Test-Retest Reliability of Low-Cost Posturography for Assessing Postural Stability Control Performance during Standing.

Postural stability control performance assessment is necessary in providing important information for individuals who are at risk of falling or who have balance impairment. Instrumented assessment is suggested as a valid and reliable test, but the cost and the difficulty of setup are significant limitations. The aim of this cross-sectional (test-retest reliability) study was to develop and determine the reliability of a low-cost posturography for assessing postural stability control performance during standing. The low-cost posturography was developed with four load cells and an acrylic platform. The center of pressure (COP) displacement and velocity were analyzed using written software. Test-retest reliability was performed with six different standing postural stability tests in twenty healthy volunteers on two different days. Intraclass correlation coefficient (ICC), standard error of measurement (SEM), coefficient of variation (CV), and Bland–Altman plot and limits of agreements (LOA) were used for analyses. The low-cost posturography was accurate (ICC = 0.99, p < 0.001; SEM = 0.003 cm) when compared to the true with calculated X and Y coordinates, with a moderate to excellent test-retest reliability for both COP displacement (ICCs ranged 0.62–0.91, p < 0.05; SEMs ranged 17.92–25.77%) and COP velocity (ICCs ranged 0.62–0.91, p < 0.05; SEMs ranged 18.09–27.69%) in all standing postural stability tests. Bland–Altman plots and LOAs suggested good agreement of tested parameters from the developed low-cost posturography between different days. In conclusion, the developed low-cost posturography had adequate reliability for assessing COP displacement and velocity during standing postural control stability performance tests.

An Adaptive Assistance Controller to Optimize the Exoskeleton Contribution in Rehabilitation

In this paper, we present a novel adaptation rule to optimize the exoskeleton assistance in rehabilitation tasks. The proposed method adapts the exoskeleton contribution to user impairment severity without any prior knowledge about the user motor capacity. The proposed controller is a combination of an adaptive feedforward controller and a low gain adaptive PD controller. The PD controller guarantees the stability of the human-exoskeleton system during feedforward torque adaptation by utilizing only the human-exoskeleton joint positions as the sensory feedback for assistive torque optimization. In addition to providing a convergence proof, in order to study the performance of our method we applied it to a simplified 2-DOF model of human-arm and a generic 9-DOF model of lower limb to perform walking. In each simulated task, we implemented the impaired human torque to be insufficient for the task completion. Moreover, the scenarios that violate our convergence proof assumptions are considered. The simulation results show a converging behavior for the proposed controller; the maximum convergence time of 20 s is observed. In addition, a stable control performance that optimally supplements the remaining user motor contribution is observed; the joint angle tracking error in steady condition and its improvement compared to the start of adaptation are as follows: shoulder 0.96±2.53° (76%); elbow −0.35±0.81° (33%); hip 0.10±0.86° (38%); knee −0.19±0.67° (25%); and ankle −0.05±0.20° (60%). The presented simulation results verify the robustness of proposed adaptive method in cases that differ from our mathematical assumptions and indicate its potentials to be used in practice.

A New Frontier Has Emerged That Enables the Reliable Diagnosis and Subtyping of Von Willebrand Disease (vWD) Clinical Patients in 48 Hours

Remarkably, classical von Willebrand disease (vWD) laboratory work-ups have been shown to require repeat laboratory testing 1 to 20 times to confirm diagnosis [1]. Furthermore, most diagnostic laboratory algorithms terminate with molecular confirmation [2, 3]. Here we present the method validation of a diagnostic laboratory approach that allows for the simultaneous functional and genetic diagnosis and subtyping von Willebrand disease (vWD) and pseudo- or platelet-type vWD within 48 hours. The clinical sensitivity of this test is approximately 85% for subtypes 2A, 2B, 2N, 2M and 3 vWD [4].The method validation is compliant with current Clinical Laboratory Improvement Act (CLIA) and applicable current Good Laboratory Practices (cGLP, 21 CFH Part 58) guidelines and therefore is suitable for clinical utilization and clinical trial utilization. The method validation protocol included the creation of reference intervals, reportable ranges, intra-run precision, inter-run precision, accuracy, lower limit of quantification (LLQ), linearity, analytical and clinical sensitivity assessment, analytical and clinical specificity assessment, interfering substances, stability and longitudinal quality control performance [Table 1.].Historically, no one test has been able to diagnose vWD. Classical laboratory work-ups include aPTT, factor VIII (8) activity, Ristocetin cofactor activity, vWF antigen, ratio calculations, multimeric composition and others. Each of these tests is influenced by numerous factors, such as inflammation, stress, infection, hormone replacement therapy, age, acute phase response, menstrual cycle, pregnancy exercise, ABO blood type, lupus anticoagulant and other factors, making traditional diagnosis a challenging moving target [3, 5, 6].The methodology used in this study employed simultaneous classical vWD laboratory testing and rapid next generation sequencing (NGS) optimized for 48-hour result availability [Table 2]. Furthermore, normal healthy and vWD 2N subtype samples can clearly be distinguished in this testing approach [Table 3].vWD occurs with bleeding symptoms at rate of 1 in 1,000 in the general population [6]. In 10% of those cases the bleeding is severe [3]. This prevalence makes vWD the most common congenital bleeding disorder known [6]. Acquire vWD (1-5% of cases) can be assessed by contrasting functional von Willebrand testing with genetic testing in a specialized coagulation, platelet and genetics laboratory. Common symptoms of vWD include menorrhagia, prolonged bleeding or bruising from minor trauma, recurrent nose bloods, excessive bleeding at childbirth and excessive bleeding associated with surgery.In conclusion, the standard clinical approach of diagnosing vWD can take months to years and require one or more referrals to specialized clinicians to establish diagnosis and subtyping. The data presented in this study proposes that an alternative method of rapidly characterizing suspected vWD patients simultaneously with both functional and genetic tests can revolutionize speed of diagnosis and treatment.vWD Subtypes: (each can have severe clinical presentations)Type 1 = 60%Type 2 = 30%Type 2A = 15%Type 2B = 5%Type 2M < 5%Type 2N <5% (clinically similar to mild hemophilia A)Type 3 = 5-10%Pseudo-vWD or Platelet-type vWD = rare (defect in GP1BA gene)Acquired vWD = 1-5%