Input Disturbances Research Articles

A novel control strategy for PWM rectifier based on underactuated characteristics

In this paper, a double closed loop controller based on equivalent input disturbances (EID) error perturbation is proposed to solve the problem of abnormal operation of three-phase pulse width modulation (PWM) rectifier caused by load and external conditions. By analysing the buffeting problem and response time problem caused by traditional sliding mode in the current control process, a new current control method of terminal fuzzy sliding mode is designed. The system error is estimated by EID error estimation, and fuzzy control is introduced to improve the accuracy of error estimation, which solves the current buffeting and response problem. In order to solve the problem of response rate and harmonics in the voltage controller design, the extended state observer (ESO) in active disturbance rejection control (ADRC) control is improved, EID error estimation is introduced, the response rate and anti-disturbance ability of the system are further improved, and the harmonics of the system are suppressed. The experimental results show the effectiveness and superiority of the proposed method.

Robust data-driven model-free adaptive control to uncertainties and disturbances for NARMAX systems

This paper introduces an enhancement to the model-free adaptive control (MFAC) method based on a new control input cost function for full-form dynamic linearization (FFDL) for NARMAX systems. The new control cost function includes the one-step-ahead tracking error, OER, and output error integral. The main feature of the approach is that it has a high ability to overcome disturbances in the control input and measured noise in the output. Analytical and extensive simulations have demonstrated that the novel control law exhibits superior response and robustness in comparison to the prototype MFAC. Moreover, it guarantees stability and convergence of the tracking error by enforcing bounded-input bounded-output (BIBO) criteria. In addition, 20 Monte Carlo simulations were conducted to test the initial conditions and random control parameters, and the results demonstrated that the proposed control outperformed the prototype MFAC.

Adaptive Sliding Mode Control for Trajectory Tracking of Quadrotor Unmanned Aerial Vehicles Under Input Saturation and Disturbances

This paper addresses the challenging issue of trajectory tracking for uncertain quadrotor unmanned aerial vehicles (UAVs), particularly under the constraints of input saturation and external disturbances. It introduces adaptive laws for managing uncertainties in mass and inertia moments without requiring prior knowledge, ensuring effective control even with varying system parameters. To counteract the effects of input saturation, the study incorporates an auxiliary system designed to compensate for these limitations. Additionally, a disturbance observer (DO) is utilized to manage and mitigate the impact of time-varying external disturbances. The proposed control strategy integrates a sliding mode adaptive control approach with an inner–outer loop structure, enhancing robustness and adaptability. Numerical simulations demonstrate the effectiveness of the designed control strategy.

Attitude Regulation of Flexible Spacecrafts with Unknown Control Directions and Input Disturbances

Attitude Regulation of Flexible Spacecrafts with Unknown Control Directions and Input Disturbances

Adaptive finite-time event-triggered control for nonlinear systems with quantized input and periodic disturbances

Adaptive finite-time event-triggered control for nonlinear systems with quantized input and periodic disturbances

Networked Control of a Small Drone Resilient to Cyber Attacks

With increasing advances in networked systems and networked control systems in everyday life, the problem of cybersecurity becomes crucial. Moreover, in some applications like small UAVs, the safety and integrity of the system and its surroundings are highly susceptible to cyberattacks. In this context, the current paper proposes a resilient networked control approach. The control structure is split into an inner and an outer loop. The outer position control loop uses measurements from motion cameras connected to a remote computer, while the commands are sent through the network. We consider the resilience problem for two types of cyberattacks: denial of service (DoS), emulated as an increase in the network transmission delay, and man in the middle (MitM), emulated as additive input disturbances. The mitigation for the DoS attack is performed through the help of a reference governor (RG), which uses the delay estimates and the system’s model to predict future safety violations and adapts the reference accordingly. The MitM attack is mitigated by an unknown input disturbance observer (UIDO) together with a RG. Experimental results on a Parrot Mambo drone show that both types of attacks are rejected successfully, ensuring a safe and stable flight.

Dynamic event-triggered finite-horizon robust suboptimal control of multi-player systems with input disturbances

This paper presents an adaptive dynamic event-triggered robust finite-horizon suboptimal control scheme for multi-player nonzero-sum game of nonlinear systems with input disturbances based on dynamic programming (ADP) and integral sliding mode (ISM) control techniques. Firstly, dynamic event-triggered adaptive ISM controllers are designed to handle input disturbances that can force the system state to remain on the sliding manifold and relax the known upper bounds condition of input disturbances. Corresponding event-triggered condition is employed for ISM controller of each player to reduce the update frequency. Then, utilizing the obtained ISM dynamics, we employ ADP-based single critic neural networks to approximate the time-varying solution of the Hamilton–Jacobi equations. Thus, the event-triggered finite-horizon suboptimal controllers can be obtained, and corresponding state-based dynamic event-triggered condition is designed to improve the resource utilization. The stability property of the closed-loop system is demonstrated through the Lyapunov technique. Finally, the effectiveness of the proposed control scheme is confirmed through two simulation examples.

Evaluating the use of grey-box system identification for digital twins in manufacturing automation

ABSTRACT A key element of any digital twin is the digital replica, or model, of its physical counterpart. When applied to industrial automation systems, it is important to consider the trade-off between model fidelity and computational complexity when developing this model. In this paper, we investigate the use of grey-box system identification as a means for producing digital twin models, as the approach reduces computational complexity while maintaining model fidelity. Using a three-link robotic manipulator, we evaluate the ability the digital twin’s system identification module to produce a high-fidelity model while under the influence of input disturbances. We then expand these results by evaluating the ability of the determined model to accurately emulate the robotic manipulator for tasks given to digital twins through the system simulation and monitoring modules. The results of this testing demonstrate that the grey-box system identification module is prone to error and sensitive to input disturbances; however, it produces models that are still able to accurately predict the dynamic response of the robotic manipulator. Furthermore, the tests demonstrate the determined models can be used by the digital twin for simulation and monitoring applications with certain limitations.

A model free adaptive control method based on self-adjusting PID algorithm in pH neutralization process

In this paper, a new model free adaptive control method based on self-adjusting PID Algorithm (MFAC-SA-PID) is proposed to solve the problem that the pH process with strong nonlinearity is difficult to control near the neutralization point. The MFAC-SA-PID method also solves the problem that the parameters of the model free adaptive control (MFAC) method are not easy to be adjusted and the effect is not obvious by introducing a fuzzy self-adjusting algorithm to adjust the controller parameters. Then the convergence and stability of the MFAC-SA-PID method are proved in this paper. In the simulation study, the control performance of the MFAC-SA-PID method proposed in this paper is compared with the traditional MFAC method and the improved model free adaptive control (IMFAC) method, respectively. The results show that the proposed MFAC-SA-PID method has better control effect on the pH neutralization process. The MFAC-SA-PID control performance also outperforms the traditional MFAC method and IMFAC method when step input disturbances are added, which indicates that the MFAC-SA-PID method has better robustness and stability.

High benthic community respiration and ecosystem response to phytodetrital input in a subpolar fjord on the West Antarctic Peninsula

AbstractGlaciomarine fjords dominate the coastal margin of the West Antarctic Peninsula. Studies in similar habitats in the Arctic have shown that benthic biodiversity and ecosystem functioning in inner and middle fjord basins are reduced by turbidity and sedimentation disturbance caused by climate warming–enhanced glacial melting. In contrast, the inner and middle fjord basins along the West Antarctic Peninsula are characterized as productivity and biodiversity hotspots, but benthic ecosystem functions remain unevaluated. In 2015–2016, we conducted sediment respiration and 13C pulse‐chase experiments to assess benthic ecosystem functions along a five‐station transect at ~ 500–600 m depths from the inner Andvord Bay fjord, through to Gerlache Strait, and onto the open continental shelf. Incubation samples from the inner and middle basins of Andvord Bay showed peaks in background seafloor respiration, benthic biomass, and uptake of labeled algal biomass compared to more outlying stations; the continental shelf exhibited the lowest levels of these variables, as well as dissolved inorganic carbon production. Macrofaunal community uptake was responsible for most of the C processing in the inner and middle parts of the fjord (> 45%) while dissolved inorganic carbon was the dominant repository of processed C near the fjord mouth and on the continental shelf (> 80%). The inner parts of Andvord Bay are hotspots of benthic C‐cycling and metabolism, in addition to biodiversity. Ongoing climate warming is likely to negatively impact these inner‐fjord hotspots by increasing meltwater input and sedimentation disturbance, yielding a reduction in the input and recycling of labile detritus at the seafloor in the inner‐middle fjord.

Improved Control Strategy for Dual-PWM Converter Based on Equivalent Input Disturbance

Aiming at the problems of jittering waveforms and poor power quality caused by external disturbances during the operation of a dual-pulse-width-modulation (PWM) converter, an improved terminal sliding mode control and an improved active disturbance rejection control (ADRC) are investigated. The method is based on mathematical models of grid-side and machine-side converters to design the controllers separately, and the balance between the two sides is maintained by the capacitor voltage. An improved terminal fuzzy sliding mode control and equivalent input disturbance (EID)-error-estimation-based active disturbance rejection control are presented on the grid side to improve the voltage response rate, and an improved support vector modulation (SVM)–direct torque control (DTC)–ADRC method is developed on the motor side to improve the robustness against disturbances. Finally, theoretical simulation experiments are built in MATLAB R2023a/Simulink to verify the effectiveness and superiority of this method.

Anti Wind‐Up and Robust Data‐Driven Model‐Free Adaptive Control for MIMO Nonlinear Discrete‐Time Systems

ABSTRACTThis article addresses a solution to one of the main challenges of online data‐driven control (DDC) methods: reducing the sensitivity of the model‐free adaptive control (MFAC) method to initial conditions and control parameters with the new control cost function and added the output error rate and integral along with a new anti‐wind up strategy for multi‐input multi‐output (MIMO) systems. The parameters introduced to the new control law have been validated using the boundary‐input boundary‐output (BIBO) approach to design and converge the controller. The simulation findings on a nonlinear auto‐regressive moving average model with exogenous inputs (NARMAX) system with triangular control input demonstrate that the proposed control rule will outperform to prototype MFAC. Furthermore, to analyze the sensitivity of the controller to the initial conditions and the uncertainties of the control parameters, 30 Monte Carlo simulations were performed with random initial conditions in the presence of disturbance in the control input, and output noise, and the results were compared with the prototype MFAC and conventional PID controller using standard criteria such as integral time absolute error, standard deviation, steady‐state error, and mean maximum error, which shows a noticeable superiority of proposed controller relative to the prototype MFAC.

Substantial increase of organic carbon storage in Chinese lakes

Previous studies typically assumed a constant total organic carbon (OC) storage in the lake water column, neglecting its significant variability within a changing world. Based on extensive field data and satellite monitoring techniques, we demonstrate considerable spatiotemporal variability in OC concentration and storage for 24,366 Chinese lakes during 1984–2023. Here we show that dissolved OC concentration is high in northwest saline lakes and particulate OC concentration is high in southeast eutrophic lakes. Along with increasing OC concentration and water volume, dissolved and particulate OC storage increase by 44.6% and 33.5%, respectively. Intensified human activities, water input, and wind disturbance are the key drivers for increasing OC storage. Moreover, higher OC storage further leads to an 11.0% increase in nationwide OC burial and a decrease in carbon emissions from 71.1% of northwest lakes. Similar changes are occurring globally, which suggests that lakes are playing an increasingly important role in carbon sequestration.

Ultimate Boundedness of a Stochastic Chemostat Model with Periodic Nutrient Input and Random Disturbance

Ultimate Boundedness of a Stochastic Chemostat Model with Periodic Nutrient Input and Random Disturbance

Variable Structure Controller for Energy Savings in an Underwater Sensor Platform.

This paper introduces a new variable structure controller designed for depth control of an autonomous underwater sensor platform equipped with a variable buoyancy module. To that end, the prototype linear model is presented, and a finite element-based method is used to estimate one of its parameters, the hull deformation due to pressure. To manage potential internal disturbances like hull deformation or external disturbances like weight changes, a disturbance observer is developed. An analysis of the observer steady-state estimation error in relation to input disturbances and system parameter uncertainties is developed. The locations of the observer poles according to its parameters are also identified. The variable structure controller is developed, keeping energy savings in mind. The proposed controller engages when system dynamics are unfavorable, causing the vehicle to deviate from the desired reference, and disengages when dynamics are favorable, guiding the vehicle toward the target reference. A detailed analysis determines the necessary switching control actions to ensure the system reaches the desired reference. Finally, simulations are run to compare the proposed controller's performance with that of PID-based controllers recently developed in the literature, assessing dynamic response and energy consumption under various operating conditions. Both the VBM- and propeller-actuated vehicles were evaluated. The results demonstrate that the proposed controller achieves an average energy consumption reduction of 22% compared to the next most efficient PID-based controller for the VBM-actuated vehicle, though with some impact on control performance.

Prescribed Performance Formation Tracking Control for Underactuated AUVs under Time-Varying Communication Delays

Achieving formation tracking control of underactuated autonomous underwater vehicles (AUVs) under communication delays presents a significant challenge. To address this challenge, a distributed prescribed performance control protocol based on a real-time state information online predictor (RSIOP) is proposed in this paper. First, we innovatively designed an RSIOP to achieve active compensation for the delayed state information of neighboring AUVs. Next, considering formation performance and safety, a low-complexity and practical nonlinear mapping function was used to implement prescribed performance tracking control for the AUV formation. Additionally, the adverse effects of external disturbance uncertainties and input saturation are also considered. Finally, the simulation tests demonstrated that the proposed formation control protocol can successfully achieve the predetermined formation tracking tasks in the presence of time-varying communication delays and external disturbances, while also enabling real-time changes in formation configuration during the process. Throughout, the protocol maintains input saturation limits, and the actual control inputs remain smooth, with no significant oscillations. Furthermore, comparative simulation tests verified the necessity of the RSIOP developed in this study and quantitatively demonstrated that the proposed control method exhibits superior performance in terms of formation control accuracy, error convergence speed, and transient-state constraints.

TRAJECTORY TRACKING CONTROL OF A TWO WHEELED SELF-BALANCING ROBOT BY USING SLIDING MODE CONTROL

Two-Wheeled Self-Balancing Robots are widely used in various fields today. These systems have a highly unstable nature due to their underactuated structures. On the other hand, parameter uncertainties and external disturbances significantly affect their control performance. The best way to deal with parameter uncertainties that can easily lead controllers to instability is to use robust control methods. Dealing with these uncertainties is particularly crucial in control of underactuated and unstable systems such as Two-Wheeled Self-Balancing Robots. In this study, trajectory tracking control of a two wheeled self-balancing robot by using Sliding Mode Control (SMC) was realized. The chattering problem inherent in the SMC method was eliminated by employing tangent hyperbolic (tanh) switching function instead of signum function. The performance of the SMC controller has been examined under five different cases including external disturbance and various parameter uncertainties and compared with PID and LQR methods. The results showed that the SMC method is much more insensitive to parameter changes than the PID and LQR methods. It has also been observed that all three controllers maintain their stability against disturbance inputs, but the SMC method offers a better control performance.

Power quality disturbances categorization using Identity Feature Vector and Extreme Learning Machine

Power quality disturbances are variations or anomalies in the voltage, current, or frequency of electrical power that can affect the proper operation of electrical equipment. These disturbances are usually classified into different categories based on their attributes and effects. This article presents an intelligent technique based on an Identity Feature Vector and an Extreme Learning Machine (ELM). This study first derives a constant length vector for each disturbance signal. A wavelet transform is applied to derive attributes from the input disturbance signal, and the identity vector is formed using the approximation coefficients. After the required normalization procedures, the normalized identity vector is classified using an ELM. To assess the productivity of the suggested approach, 12 types of disturbances, single and combined, are generated, and the system's efficiency is studied. The results indicate that ten out of 12 combinations, including Harmonic, Sag, and Flicker, were detected with 100% accuracy. Additionally, the combination "Harmonic + Swell" exhibited the lowest accuracy, identified with 98% accuracy. The total average accuracy of this method is 99.75%. The outcomes demonstrate the highly favorable performance of this approach. This study evaluated the analyzed algorithm under noisy conditions with three different noise levels: 30 dB, 40 dB, and 50 dB, respectively. The average prediction accuracy for these three noise levels is 99.16%, 99.25%, and 98.91%. The outcomes demonstrate that the evaluated algorithm accurately detects power quality disturbances across various noisy conditions.

An improved two‐degree‐of‐freedom ADRC for asynchronous motor vector system

AbstractThis paper proposes an improved two‐degree‐of‐freedom active disturbance rejection controller for the coupling problem of asynchronous motor vector system. To simplify the analysis process and accommodate observers of different types, a unified expression based on different controllers for the system output is developed. The closed‐loop transfer function generated by the reference input and load disturbance is given. For the coupling problem of motor output speed and immunity, the structure of a higher‐order extended state observer is reconstructed. The extended state observer estimates both the output speed and the total system disturbance, which serve as feedback and feed‐forward compensation quantities. Compared to the PI controller and traditional active disturbance rejection controller, the proposed controller achieves decoupling of output response speed and immunity, simplifies the process of parameter tuning. Finally, simulation and experiment results verify the feasibility and effectiveness of the algorithm in this paper.

Improved delay-dependent stability analysis of digital filters with generalized overflow arithmetic

This paper introduces a new set of conditions that establish Input-to-State Stability (ISS) for digital filters with external disturbance input and time-varying delays, all within the context of generalized overflow arithmetic. A unique augmented Lyapunov function and a novel summation inequality are applied to formulate a new criterion for ISS. This criterion assesses the ISS of digital filters in the presence of external disturbance, enabling the identification of asymptotic stability even in the absence of such disturbance. The criteria are developed using linear matrix inequalities (LMIs). The efficacy of the results is demonstrated through three numerical examples, highlighting that the proposed criteria are less conservative than some recent results.