Active disturbance rejection control: Applications in aerospace

Talole, S. E.

doi:10.1007/s11768-018-8114-1

Cited by 20 publications

(6 citation statements)

References 51 publications

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“…Several engineering control application tasks have been effectively fixed in the last two decades, via the effective implementation of ADRC. These include flexible-joint manipulator control [33], omnidirectional mobile robot control [34], aerospace [35], temperature control [36], DC-DC power converters [37], speed control of permanent magnet DC motor [38], control of power output of wind turbines [39], Energy Storage Grid-Connected Inverter [40], Lower Limb Exoskeleton in Swing Phase [41], Ship Dynamic Positioning Systems [42], Vibration Suppression in Position Servo Systems [43], speed control of Differential drive mobile robot [44], Hydraulic Valve-Controlled Hydraulic Motor [45], the applications of ADRC on unmanned aerial vehicles are highlighted in [46][47][48][49].…”

Section: Resultsmentioning

confidence: 99%

“…In the case of the IADRC, a better output tracking has been obtained as compared to CADRC configuration, explicitly during the transient time response, where the two setups have totally constricted the impact of the state coupling for every subsystem, the exogenous disturbances w 1 and w 2 , and the time-varying input gains b 1,1 , b 1,2 , b 2,1 , and b 2,2 on the output of each channel. The transient response of the outputs y 1 and y 2 due to the desired inputs r 1 and r 2 successively imposed to (35) are displayed in Figures 7 and 8. It can be concluded that the decoupling necessity expressed in the statement of the problem is totally fulfilled with a flat output for every output subsystem.…”

Section: The Results Of the Proposed Schemementioning

confidence: 99%

“…T , i ∈ {1, 2} are the estimated states and ω o, i , i ∈ {1, 2} is the LESO bandwidth of the ith sub-system. The IADRC is the second configuration, which involves of a conventional TD (35), a fal-based control law (36), and an NHOESO proposed as,…”

Section: Numerical Simulationsmentioning

confidence: 99%

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Anti-Disturbance Compensation-Based Nonlinear Control for a Class of MIMO Uncertain Nonlinear Systems

Abdul-Adheem

Alkhayyat

Mhdawi

et al. 2021

Entropy

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Multi-Inputs-Multi-Outputs (MIMO) systems are recognized mainly in industrial applications with both input and state couplings, and uncertainties. The essential principle to deal with such difficulties is to eliminate the input couplings, then estimate the remaining issues in real-time, followed by an elimination process from the input channels. These difficulties are resolved in this research paper, where a decentralized control scheme is suggested using an Improved Active Disturbance Rejection Control (IADRC) configuration. A theoretical analysis using a state-space eigenvalue test followed by numerical simulations on a general uncertain nonlinear highly coupled MIMO system validated the effectiveness of the proposed control scheme in controlling such MIMO systems. Time-domain comparisons with the Conventional Active Disturbance Rejection Control (CADRC)-based decentralizing control scheme are also included.

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Section: Resultsmentioning

confidence: 99%

Section: The Results Of the Proposed Schemementioning

confidence: 99%

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Anti-Disturbance Compensation-Based Nonlinear Control for a Class of MIMO Uncertain Nonlinear Systems

Abdul-Adheem

Alkhayyat

Mhdawi

et al. 2021

Entropy

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“…Motivated by the huge potential, the simplicity of the design procedure, and the wide immergence of ESO based robust control paradigm in simulation and engineering applications, readers can refer to the literature [45][46][47][48][49]. In this paper, we attempt to illustrate how to use the ESO for improving the nonlinear multivariable decoupled control robustness in a simple and clear manner.…”

Section: Introductionmentioning

confidence: 99%

Extended State Observer Based Robust Feedback Linearization Control Applied to an Industrial CSTR

Medjebouri

2024

JAMRIS

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In the chemical and petrochemical industries, the Continuous Stirred Tank Reactor (CSTR) is, without doubt, one of the most popular processes. From a control point of view, the mathematical model describing the temporal evolution of the CSTR has a strongly nonlinear cross-coupled character. Moreover, modeling errors such as external disturbances, neglected dynamics, and parameter variations or uncertainties make its control task a very difficult challenge. This problem has been the subject of a wide number of control strategies. This article attempts to propose a viable, robust nonlinear decoupling control scheme. The idea behind the proposed approach lies in the design of two nested control loops. The inner loop is responsible for the compensation of the nominal model's nonlinear cross-coupled terms via a static nonlinear feedback; while the outer loop, designed around an Extended State Observer (ESO), which the additional state gathers the global effect of modeling errors, is charged with instantaneously estimating and then compensating the ESO extended state. This way, the CSTR complex dynamics are reduced to a series of decoupled linear subsystems easily controllable using a simple Proportional-Integral (PI) linear control to ensure the robust pursuit of reference signals respecting the desired performance. The presented control validation was performed numerically by an objective comparison to a classical PID controller.

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“…Nevertheless, the required perpetual stability and sensitive preciseness of the reference voltage value necessitate optimal design and the application of controllers for the MEMS voltage references or TCs. The recent control methods demonstrate that efficient control techniques are employed for MEMS and other mechatronic systems to reduce error and enhance performance: Adaptive Sliding Mode Control (ASMC) with application to MEMS gyroscope [12], control of uncertain systems [29], disturbance rejection control with application to aerospace engineering [40], Artificial Neural Network (ANN) based adaptive control [38] and fuzzy adaptive control [37]. In particular, fuzzy control has gained a lot of interests in performance enhancement for MEMS device drive and operation.…”

Section: Introductionmentioning

confidence: 99%

Design of a fuzzy PID controller for a MEMS tunable capacitor for noise reduction in a voltage reference source

et al. 2021

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This study presents a conventional Ziegler-Nichols (ZN) Proportional Integral Derivative (PID) controller, having reviewed the mathematical modeling of the Micro Electro Mechanical Systems (MEMS) Tunable Capacitors (TCs), and also proposes a fuzzy PID controller which demonstrates a better tracking performance in the presence of measurement noise, in comparison with conventional ZN-based PID controllers. Referring to importance and impact of this research, the proposed controller takes advantage of fuzzy control properties such as robustness against noise. TCs are responsible for regulating the reference voltage when integrated into Alternating Current (AC) Voltage Reference Sources (VRS). Capacitance regulation for tunable capacitors in VRS is carried out by modulating the distance of a movable plate. A successful modulation depends on maintaining the stability around the pull-in point. This distance regulation can be achieved by the proposed controller which guarantees the tracking performance of the movable plate in moving towards the pull-in point, and remaining in this critical position. The simulation results of the tracking performance and capacitance tuning are very promising, subjected to measurement noise. Article Highlights This article deals with MEMS tunable capacitor dynamics and modeling, considering measurement noise. It designs and applies fuzzy PID control system for regulating MEMS voltage reference output. This paper contributes to robustness increase in pull-in performance of the tunable capacitor.

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Active disturbance rejection control: Applications in aerospace

Cited by 20 publications

References 51 publications

Anti-Disturbance Compensation-Based Nonlinear Control for a Class of MIMO Uncertain Nonlinear Systems

Anti-Disturbance Compensation-Based Nonlinear Control for a Class of MIMO Uncertain Nonlinear Systems

Extended State Observer Based Robust Feedback Linearization Control Applied to an Industrial CSTR

Design of a fuzzy PID controller for a MEMS tunable capacitor for noise reduction in a voltage reference source

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