Active Control Design Research Articles

Modified Active Disturbance Rejection Control Design Based on Gain Scheduling for Selective Catalytic Reduction Denitrification Processes

Modified Active Disturbance Rejection Control Design Based on Gain Scheduling for Selective Catalytic Reduction Denitrification Processes

A Bayesian-Based Credible and Reliable Control Method for Active Vibration Suppression of Structures with Uncertain Parameters

As a classical design method for addressing uncertainty in control systems, robust control is designed with the goal of complete reliability of the control system. Nevertheless, the pursuit of robustness can inadvertently give rise to considerable performance degradation, rendering the resultant closed-loop control system excessively conservative in its design. Reliability-based design methods serve as an effective approach for managing uncertainties, which will achieve a balance between the robustness and performance of the active control system by taking advantage of the characteristic of reliability that allows for a certain level of permissible failure probability. The accurate quantification of uncertainty is the key to achieving reliable control, but common uncertainty quantification methods cannot achieve credible quantification of uncertainty in small samples and update the distribution of new samples. In this paper, a nonprobabilistic Bayesian inference based interval uncertainty quantification method is proposed. This method updates the distribution of interval boundaries and radii by introducing a small number of samples, and obtains interval parameters under a given confidence level. On the basis of uncertainty quantification, the dynamic reliability of the vibration system is derived, and nonprobabilistic reliability is introduced into the design of active controllers through optimization strategies. The reliable control strategy aims to select the optimal controller parameters on a reliable path with a given credibility, in order to solve the problem of overly conservative robust control theory. Two numerical examples were used to verify the feasibility and applicability of this method.

Design of active disturbance rejection controller for the system with unknown model using Laguerre functions

This paper concentrates on the design problem of linear active disturbance rejection control (LADRC) for uncertain systems, whose order and parameters are unknown. In general, LADRC has diversified structural forms due to different order and parameters selection. To clarify the prerequisites for constructing the LADRC strategy, a Laguerre-based LADRC (LLADRC) method is proposed, which provides controller design guidance for systems with unknown models by capturing the impulse response. Then, intensive attention is focused on establishing internal stability conditions of the feedback system and parameter tuning rules of the prescribed controller. To gain a better understanding, the internal correlation between LLADRC and standard LADRC of the same order is analyzed. It is shown that observer and controller gains of the standard LADRC can be tuned via a workable LLADRC to achieve better control performance. Finally, a numerical example and an application design of DC motor speed control are studied, both of which demonstrate the feasibility and validity of the proposed method.

Integrated Design for Active Fault Diagnosis and Control: A Decomposition-Composition Method

Integrated Design for Active Fault Diagnosis and Control: A Decomposition-Composition Method

Adverse respiratory events during treatment with gabapentin and opioids among older adults with spine-related conditions: a propensity-matched cohort study in the US Medicare population.

Recent work indicates no increased mortality risk with concurrent gabapentin and opioid use when using an active comparator control design. However, concurrent gabapentin and opioid prescriptions have been associated with greater risk of respiratory depression in some studies. To compare the risk of respiratory events among Medicare enrollees with spine-related diagnoses treated with gabapentin + opioids vs those treated with tricyclic antidepressants (TCA) or duloxetine + opioids. We hypothesized that enrollees treated with gabapentin + opioids would have increased risk of adverse respiratory events compared to those treated with an active control + opioids. Propensity score-matched cohort study with an incident user, active comparator (TCA/duloxetine) control design. The primary analysis included those who concurrently (within 30 days) filled ≥1 incident gabapentin + ≥1 opioid or ≥1 incident TCA/duloxetine + ≥1 opioid prescription. U.S. Medicare beneficiaries with spine-related diagnoses 2017-2019. People treated with gabapentin + opioids (n=66,580) were matched on demographic and clinical factors to people treated with TCAs/duloxetine + opioids (n=66,580). Time to a composite respiratory outcome consisting of mechanical ventilation, intubation, respiratory failure, pneumonia, or acute respiratory distress syndrome. Cox proportional hazard regression was used to estimate adjusted hazard ratios (aHRs) and 95% confidence intervals (95% CIs). Among 133,160 Medicare enrollees (median age 73.3 years; 66.7% female), 6089 (4.6%) experienced respiratory events before the end of follow-up. A total of 3297 (5.0%) of people who were treated with gabapentin + opioids (median initial dose/day of gabapentin was 338 mg) had respiratory events compared to 2792 (4.2%) of those treated with an active control + opioids. The increased risk in those treated with gabapentin + opioids was statistically significant after adjustment (HR 1.14; 95% CI 1.09, 1.20; p<0.0001). The most common respiratory events were pneumonia (3.5% of people in the gabapentin + opioids group versus 3.0% of people in the TCA/duloxetine + opioids group) and respiratory failure (2.2% in the gabapentin + opioids group versus 1.8% in the TCA/duloxetine + opioids group). Results were similar in analyses (a) restricted to ≤30-day follow-up and (b) that required ≥2 fills of each prescription. While recent work has indicated no increased mortality risk with concurrent gabapentin and opioid use, the current findings suggest clinicians should exercise caution in prescribing gabapentin to people experiencing pain who are also being treated with opioids, due to the potentially increased risk of respiratory events.

Design of active vibration isolation controller for pointing stabilization mechanism based on feedforward–feedback hybrid control

The use of space technology and small space loads is increasingly common. To address this, a mechanism for isolation vibration in small optical load has been proposed. The mechanism includes a coarse and fine stage parallel pointing platform (CFPP). This paper investigates an active vibration isolation scheme for the novel pointing stabilization mechanism. The kinetic energy minimization principle is derived from the analysis of its working mechanism and dynamic feedforward characteristics. This principle is confirmed by the feedforward of the indeterminate degrees of freedom of the under-constrained mechanism. A hybrid control scheme of feedback and feedforward is developed based on the H∞ algorithm and the optimal feedforward control algorithm. Simulation and experimentation have proven that the vibration isolation efficiency of more than 20 dB can be achieved in all three axis rotation directions. This meets the precision pointing requirements of small optical load effectively.

Assessment of Quality of Reporting in Randomized Controlled Trials of Moxibustion for Chronic Diseases Using the Consolidated Standards of Reporting Trials and Standards for Reporting Interventions in Clinical Trials of Moxibustion Statements

Introduction: Moxibustion is clinically used for treating various chronic diseases; however, the reporting quality of current published RCTs of moxibustion is unclear. The objective of this study was to assess the reporting quality of RCTs focusing on moxibustion as a treatment for chronic diseases. Methods: Seven databases were searched to identify relevant RCTs. Criteria for evaluating the reporting quality of standard RCT elements and moxibustion intervention-related information were developed based on the CONSORT statement and its STRICTOM extension, respectively. Multivariate regression models were used to investigate factors impacting reporting quality. Results: A total of 310 RCTs were included, with 41 (7.6%) published in English journals and 269 (92.4%) in Chinese journals. The median CONSORT and STRICTOM scores of these RCTs, with a maximum score of 100, were 41.2 and 62.9, respectively. RCTs with a later publication year and protocol registration or ethical approval exhibited significantly higher CONSORT and STRICTOM scores. Higher CONSORT scores were also significantly associated with English language publication, funding support, and inclusion of a safety evaluation, while higher STRICTOM scores were additionally associated with an active control design. Conclusion: The reporting quality of RCTs focusing on moxibustion treatment for chronic diseases is subpar, with gradual but limited improvement over the last 25 years. To enhance the reporting quality of moxibustion RCTs, researchers should develop a comprehensive study protocol and standardize result reporting based on CONSORT and STRICTOM statements. Registration platforms, ethical approval organizations, funders, and journals can also contribute to this improvement by bolstering structured information reporting in the review process.

Active Adaptive Composite Fault Tolerant Controller Design For Nonlinear Systems

Abstract It can be seen from the public opinion monitoring that there are many cases of death and injury caused by quality problems of mechanical products, which poses a serious threat to people’s lives. Therefore, it is particularly important to analyze the reliability of mechanical products. This study focuses on active adaptive composite fault tolerant controller (ACFTC) design for nonlinear system with actuator fault. Firstly, a novel iterative learning observer (ILO) is proposed to estimate the early potential fault. And then, the ACFTC approach is proposed in order to obtain desired performance in the faulty case based on the fault estimation information from ILO. Finally, simulation of the flexible joint robot system verifies the validity and applicability of the algorithm.

Design of Active Posture Controller for Trailing-Arm Vehicle: Improving Path-Following and Handling Stability

To address the question of which posture trailing-arm vehicles (TAVs) should be adopted while driving, this study introduces an innovative active posture controller (APC) to improve both path-following and handling stability performance. Leveraging a nonlinear tire model that considers corner load variation and wheel camber, alongside the kinematics and double-track model of TAVs, the impact of vehicle body posture on handling performance has been investigated. To fully utilize the four-wheel independent drive and posture adjustable characteristics of the TAV mechanisms, an integrated nonlinear model predictive control (NMPC) combining APC and tire forces distribution is devised. Through simulations conducted using Simulink-Multibody (2023a), the effectiveness of the proposed controller is demonstrated, particularly when compared to the scheme that does not account for the unique posture adjustment mechanisms of TAVs.

Computational Fluid Dynamics-Based Systems Engineering for Ground-Based Astronomy

This paper presents the state-of-the-art techniques employed in aerothermal modeling to respond to the current observatory design challenges, particularly those of the next generation of extremely large telescopes (ELTs), such as the European ELT, the Thirty Meter Telescope International Observatory (TIO), and the Giant Magellan Telescope (GMT). It reviews the various aerothermal simulation techniques, the synergy between modeling outputs and observatory integrating modeling, and recent applications. The suite of aerothermal modeling presented includes thermal network models, Computational Fluid Dynamics (CFD) models, solid thermal and deformation models, and conjugate heat transfer models (concurrent fluid/solid simulations). The aerothermal suite is part of the overall observatory integrated modeling (IM) framework, which also includes optics, dynamics, and controls. The outputs of the IM framework, nominally image quality (IQ) metrics for a specific telescope state, are fed into a stochastic framework in the form of a multidimensional array that covers the range of influencing operational parameters, thus providing a statistical representation of observatory performance. The applications of the framework range from site selection, ground layer characterization, and site development to observatory performance current best estimate and optimization, active thermal control design, structural analysis, and an assortment of cost–performance trade studies. Finally, this paper addresses planned improvements, the development of new ideas, attacking new challenges, and how it all ties to the “Computational Fluid Dynamics Vision 2030” initiative.

Free-form and multi-physical metamaterials with forward conformality-assisted tracing.

Transformation theory, active control and inverse design have been mainstream in creating free-form metamaterials. However, existing frameworks cannot simultaneously satisfy the requirements of isotropic, passive and forward design. Here we propose a forward conformality-assisted tracing method to address the geometric and single-physical-field constraints of conformal transformation. Using a conformal mesh composed of orthogonal streamlines and isotherms (or isothermal surfaces), this method quasi-analytically produces free-form metamaterials using only isotropic media. The geometric nature of this approach allows for universal regulation of both dissipative thermal fields and non-dissipative electromagnetic fields. We experimentally demonstrate free-form thermal cloaking in both two and three dimensions. Additionally, the multi-physical functionalities of our method, including optical cloaking, bending and thermo-electric transparency, confirm its broad applicability. Our method features improvements in efficiency, accuracy and adaptability over previous approaches. This study provides an effective method for designing complex metamaterials with arbitrary shapes across various physical domains.

Development of an Underwater Detection Robot for the Structures with Pile Foundation

Addressing the challenges for detecting underwater damage to the structures with pile foundation, this study presents the design of an adsorption-operated robotic system. Initially, a prototype is proposed for an adsorption-operated robot that is equipped with an automatic movement mechanism. To account for the disturbance of the drag force in the control system, a hydrodynamic numerical model for the detection robot is established. The numerical results of the drag force are then integrated into the control system, leading to the design of a force-redeemed active disturbance rejection controller. Furthermore, a novel detection algorithm based on the image segmentation network UNet is developed for the automatic identification of damages. The performance of the controller and detection algorithm is evaluated against traditional methods. The results indicate that the proposed force-redeemed active disturbance rejection controller outperforms traditional PID and ADR controllers in terms of overshoot and adjustment time. Moreover, the developed detection algorithm exhibits superior performance in precision, F1 score, and mean intersection over union compared to the traditional algorithms of FCN, PSPnet, Deeplabv3, and UNet. Overall, this paper advances the technology of autonomous robots for underwater detection in the structures with pile foundation.

Dynamic simulation and active vibration control design of an ultra-precision fly-cutting machine tool

Dynamic simulation and active vibration control design of an ultra-precision fly-cutting machine tool

Design and Performance Evaluation of a Hybrid Active Power Filter Controller

This paper introduces a novel hybrid filter topology that combines passive and active components to enhance harmonic filtering and resonance damping in electrical power systems. The design integrates a three-phase two-level voltage-source converter with a double-tuned passive filter in parallel, significantly reducing the power rating and operational costs while maintaining good harmonic filtering performance and reactive current compensation. Double-tuned passive filters, compared to single-tuned ones, offer improved harmonic attenuation at multiple frequencies, enhancing overall system efficiency. Moreover, when used with the proposed hybrid filter topology, the double-tuned version allows for even lower dimensions of the active part, thereby further reducing system cost. A state-feedback controller is designed to enhance the performance of the hybrid filter, proving particularly effective in environments with complex impedance conditions. This paper also examines the impact of variations in passive component parameters, demonstrating the design’s robustness against potential deviations expected over the operational lifespan. The results indicate that the hybrid filter effectively mitigates harmonics and maintains operational stability under various transient conditions, as confirmed by analytical and simulation studies on a real industrial network model. These findings underline the hybrid filter’s potential to significantly improve power quality in modern electrical networks.

Novel study on active reliable PID controller design based on probability density evolution method and interval-oriented sequential optimization strategy

Vibration active control is a significant problem in practical engineering, but the influence of hybrid uncertainties in practical engineering cannot be ignored. For the uncertainties with adequate data, probability theory can be used while for the uncertainties with insufficient data, probability theory is limited and interval quantification can be used. Taking the widely used proportional-integral-differential (PID) control as an example, a novel study on controller design based on probability density evolution method and interval-oriented sequential optimization strategy considering interval and random uncertainties is proposed. Firstly, under a certain sample point of interval uncertainties, probability density evolution equation is utilized to calculate the probability density function of uncertain response considering only random uncertainties. In this way the probabilistic reliability corresponding to the sample point can be obtained. Then the hybrid reliability is defined as the average probability within the interval uncertainty and the adaptive dichotomy method is utilized to choose proper sample points of interval uncertainties, in which the reliability curve and the interval uncertainty axis is regarded as the judgement of convergence. Next the hybrid reliability is introduced to the optimization as a constraint and the PID gains reliable design optimization is established to balance the energy-consuming and safety. Finally, the sequential optimization strategy is adopted to improve the efficiency of optimization. In every iteration step of the optimization, the constraint of deterministic optimal design is adjusted according to the static reliability at the moment before the passage or reaching the maximum value. Three numerical examples are presented to demonstrate the accuracy and practicability of the proposed framework.

Nonlinear Active Disturbance Rejection Controller Design for Drag-Free Satellite with Two Test Massess

Nonlinear Active Disturbance Rejection Controller Design for Drag-Free Satellite with Two Test Massess

Design of Active Suspension Controller for Ride Comfort Enhancement and Motion Sickness Mitigation

This paper presents a method for designing an active suspension controller for ride comfort enhancement and motion sickness mitigation. For this, it is necessary to design an active suspension controller, which aims to reduce the vertical acceleration and pitch rate of a sprung mass in a vehicle. A half-car vehicle model was selected. For the controller design, a static output feedback (SOF) control was selected instead of a full-state feedback control because it is hard to measure all state variables in real vehicles. With the available signals, three types of SOF controller were proposed. To determine the gains of the SOF controllers, a linear quadratic optimal control methodology and a simulation-based optimization method were adopted. To validate the proposed method, a simulation was carried out using vehicle simulation software. The simulation results show that the proposed method is quite effective for ride comfort enhancement and motion sickness mitigation.

Active Disturbance Rejection Control Design with Sensitivity Constraint for Drum Water Level

The drum water level plays a crucial role in the safety and economy of heat recovery boilers. However, the control of the drum water level faces many challenges, such as external disturbances and system uncertainties. To enhance the control performance of the drum water level, a modified active disturbance rejection control (MADRC) optimized with sensitivity constraint is proposed in this paper. Firstly, the control structure of the three-element control system for the drum water level is introduced and analyzed. Based on the regular active disturbance rejection control (ADRC) structure, the structure of the MADRC is introduced and the convergence of the proposed MADRC is proven. Then a modified whale optimization algorithm (MWOA) with sensitivity constraint is applied to optimize the parameters of the MADRC. With different sensitivity constraints, the parameters of the MADRC and comparative controllers are obtained, and their control performance for tracking and disturbance rejection abilities is compared. Moreover, the ability to handle system uncertainties is analyzed. Simulation results and performance indexes show that the proposed MADRC can obtain the best tracking and disturbance rejection abilities with satisfactory robustness. The satisfactory control performance shows that the proposed MADRC has wide application potential for heat recovery boilers and other industrial processes.

Design of Active Disturbance Rejection Control for Rehabilitation-Assistant Device of Lower Limbs under Cross Coupling Effect

The robotic exoskeleton is a device which is designed to actuate the lower limbs of human leg for rehabilitation purposes. This device is used instead of physicians in rehabilitation clinics to recover the normal activities of dysfunctional parts. In this study, design of ADRC has been presented to control the motion of hip and knee joints for rehabilitated patients who wearing the exoskeleton device. The key of ADRC approach is to use extended state observer (ESO) for estimating the total uncertainties of the system and to compensate them in feedback-based control law. The proposed control scheme has been designed to reduce the coupling effect due to the cross coupling of upper and lower legs. The stability of ADRC-based system has been proven based on Lyapunov method. The effectiveness of proposed ADRC for hip and joint rehabilitated device has been verified via numerical simulations within MATLAB environment. The tests have been conducted including load and no-load exertion. As compared to proportional derivative controller, the numerical results revealed that the proposed ADRC gives better tracking performance and higher precision while maintaining appropriate control torque.

Deep-learning-based design of active fault-tolerant control for automated manufacturing systems subjected to faulty sensors

This research paper proposes a new implementation of a long short-term memory network for active fault-tolerant control subjected to single and multiple undiagnosable sensor faults. There are two networks used: the first performs as a diagnosis for automated manufacturing systems and can identify faulty sensors, while the second acts as an inverse model of these systems and is used to determine the reconfigured control action to take when sensors are not functioning as expected. The Factory I/O simulator is interfaced with MATLAB to simulate and verify the proposed approach for automated material handling case study with faultless and multiple fault sensors. Four sensors of the case study out of six are tolerated.