Simple Adaptive Control‐Based Reconfiguration Design of Cabin Pressure Control System

Zhang, Zhao; Yang, Zhong; Xiong, Si; Chen, Shuang; Liu, Shuchang; Zhang, Xiaokai

doi:10.1155/2021/6635571

Cited by 11 publications

(5 citation statements)

References 42 publications

(47 reference statements)

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“…Adaptive control is used as a feedback controller and MPC as a feedforward controller for tackling the unknown uncertainties 11 A Simple Adaptive Control (SAC)-based reconfiguration approach [116] Tackling the faults of sensors and actuators in the CPCS Cabin Pressure Control System (CPCS) e control method capability for controlling the rules online regardless of identifying the system under faults 12 Simple Adaptive Control (SAC) [117] Reduction of the adverse effects of the earthquake on the structures Six-story structure e proposed controller has a striking performance under various seismic excitations.…”

Section: Spacecraft Near Asteroidsmentioning

confidence: 99%

Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller

Sabetahd

Ghasemi

Poursorkhabi

et al. 2022

Computational Intelligence and Neuroscience

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The present study aims to design a robust adaptive controller employed in the active tuned mass damper (ATMD) system to overcome undesirable vibrations in multistory buildings under seismic excitations. We propose a novel adaptive type-2 neural-fuzzy controller (AT2NF). All system parameters are taken as unknowns. The MLP neural network is used to extract the Jacobian and estimate the structural model; then, the estimated model is applied to the controller online. To tune the control force applied to the ATMD and achieve the control targets, the controller parameters are adaptively trained using the extended Kalman Filter (EKF) and the error back-propagation algorithm. A PID controller is also included in this method to increase the stability and robustness of the adaptive type-2 neural-fuzzy controller against seismic vibrations. An online simple adaptive controller (OSAC) is studied to demonstrate the suggested controller’s superiority. The OSAC is based on adaptive control of the implicit reference model. In this proposed method, the EKF is used to tune the controller parameters online as a novel feature. The uncertainty associated with identifying the mechanical properties of structures, such as mass and stiffness, is one of the primary challenges in the real-time control of structures. This paper investigates how both controllers cope with parametric uncertainties under far-field and near-field seismic excitation. According to numerical results, the AT2NF controller outperforms OSAC in minimizing the dynamic responses of the structure during an earthquake and accomplishing control objectives when the structure’s characteristics change.

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Section: Spacecraft Near Asteroidsmentioning

confidence: 99%

Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller

Sabetahd

Ghasemi

Poursorkhabi

et al. 2022

Computational Intelligence and Neuroscience

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“…The PID controller outputs are used in hovercraft motion to analyze the surge, sway, and steering yaw control responses. Zhang et al [33] present a reconfigurable adaptive control technique for a cabin pressure control system (CPCS). The control technique is used to compensate for the faults in sensors and actuators in CPCS.…”

Section: Introductionmentioning

confidence: 99%

Hybrid controller design using gain scheduling approach for compressor systems

Narasimhaiah

Narayanappa²,

Lakshmaiah

2022

IJECE

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<span>The automatic control system plays a crucial role in industries for controlling the process operations. The automatic control system provides a safe and proper controlling mechanism to avoid environmental and quality problems. The control system controls pressure flow, mass flow, speed control, and other process metrics and solves robustness and stability issues. In this manuscript, The Hybrid controller approach like proportional integral (PI) and proportional derivative (PD) based fuzzy logic controller (FLC) using with and without gain scheduling approach is modeled for the compressor to improve the robustness and error response control mechanism. The PI/PD-based FLC system includes step input function, the PI/PD controller, FLC with a closed-loop mechanism, and gain scheduler. The error signals and control response outputs are analyzed in detail for PI/PD-based FLC’s and compared with conventional PD/PID controllers. The PD-based FLC with the Gain scheduling approach consumes less overshoot time of 74% than the PD-based FLC without gain scheduling approach. The PD-based FLC with the gain scheduling approach produces less error response in terms of 7.9% in integral time absolute error (ITAE), 7.4% in integral absolute error (IAE), and 16% in integral square error (ISE) than PD based FLC without gain scheduling approach.</span>

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“…Considering [10], the cabin pressure control system (CPCS) is an essential part that guarantees the aircraft structure and the crew's safety; however, the CPCS shows potential flaws in sensors and actuators. Consequently, authors in [10] suggest a reconfiguration method based on simple adaptive control in compensation for these adverse effects.…”

Section: Introductionmentioning

confidence: 99%

Filling Control of a Conical Tank Using a Compact Neuro‐Fuzzy Adaptive Control System

2022

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This document describes the implementation of a conical tank control system using an adaptive neurofuzzy system. For implementation, an indirect approach is used where the controller is optimized using the model obtained during the plant identification carried out using data obtained during the system operation. Furthermore, implementation includes training of neuro fuzzy-systems and application to control a conical tank. Regarding plant identification, preliminary training takes place using data obtained for different input values. The controller configuration is established considering the analogy with a discrete-time linear system. The simulation shows that the control system manages to approach the desired response given by the considered reference model.

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Simple Adaptive Control‐Based Reconfiguration Design of Cabin Pressure Control System

Cited by 11 publications

References 42 publications

Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller

Response Attenuation of a Structure Equipped with ATMD under Seismic Excitations Using Methods of Online Simple Adaptive Controller and Online Adaptive Type-2 Neural-Fuzzy Controller

Hybrid controller design using gain scheduling approach for compressor systems

Filling Control of a Conical Tank Using a Compact Neuro‐Fuzzy Adaptive Control System

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