Mixed sensitivity H-infinity control of an adaptive optics system

Song, Dingan; Li, Xinyang; Peng, Zhenming

doi:10.1117/1.oe.55.9.094106

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…The control system's specification involves tracking a desired signal, as illustrated in the block diagram with the input-output scheme depicted in Fig 7 . The objective of the designed control system is to ensure that its output closely follows the predetermined signal. Given the nature of the nonlinear system, it is imperative to employ efficient optimization techniques, as discussed in [43,44].…”

Section: H 1 Model-based Mixed Optimizationmentioning

confidence: 99%

A flexible mixed-optimization with H∞ control for coupled twin rotor MIMO system based on the method of inequality (MOI)- An experimental study

Abbas,

Liu,

Iqbal

2024

PLoS ONE

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This article introduces a cutting-edge H∞ model-based control method for uncertain Multi Input Multi Output (MIMO) systems, specifically focusing on UAVs, through a flexible mixed-optimization framework using the Method of Inequality (MOI). The proposed approach adaptively addresses crucial challenges such as unmodeled dynamics, noise interference, and parameter variations. Central to the design is a two-step controller development process. The first step involves Nonlinear Dynamic Inversion (NDI) and system decoupling for simplification, while the second step integrates H∞ control with MOI for optimal response tuning. This strategy is distinguished by its adaptability and focus on balancing robust stability and performance, effectively managing the intricate cross-coupling dynamics in UAV systems. The effectiveness of the proposed approach is validated through simulations conducted in MATLAB/Simulink environment. Results demonstrated the efficiency of the proposed robust control approach as evidenced by reduced steady-state error, diminished overshoot, and faster system response times, thus significantly outperforming traditional control methods.

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Section: H 1 Model-based Mixed Optimizationmentioning

confidence: 99%

A flexible mixed-optimization with H∞ control for coupled twin rotor MIMO system based on the method of inequality (MOI)- An experimental study

Abbas,

Liu,

Iqbal

2024

PLoS ONE

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“…The output of the designed control system should follow the preselected signal. According to the behavior of the nonlinear system, we must have a H ∞ model-based controller rather than other controllers as discussed in [28,29]. By this technique, two controllers are designed one is the robust stability, internal stability, and the rejection of disturbance represented in figure 11, while the other controller is designed for the minimization of error between the reference signal and the actual response of the model.…”

Section: H ∞ Model Based Control With 2dofmentioning

confidence: 99%

H∞ Model Based Control via Mixed Sensitivity for 2DOF Control of Twin Rotor MIMO System With Experimental Validation

Abbas

Zar

Raheem

et al. 2022

Preprint

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This article provides a comprehensive study about optimization and real-time implementation of H∞ model-based controller for uncertain systems (having external perturbations) using robust control methods. The complicated air vehicle modeling is quite difficult because of highly nonlinear behavior, un-modeled states, and cross-coupling effect. The helicopter flight control also depends on two rotors generating continuous thrust simultaneously in two different directions. Simple linear feedback controllers cannot ensure the stability of highly nonlinear systems like a helicopter. The controllability and observability full rank matrix output ensure the credibility of the system before a controller design. The design of a robust controller for the desired flight control, demands the availability of all its states and varying parameters for real-time robust feedback control. However, its prototype, Twin-rotor MIMO System (TRMS) facilitates the researchers and control engineers in terms of the real-time environment of a helicopter flight control. Various control strategies are presented to elaborate the behavior of the MIMO system and the limitations of robust control methods. Each control strategy has been comprehensively discussed with the stability analysis and the design requirements. The considered control techniques, such as the loop-shaping control and H∞ model-based control augmented with mixed sensitivity control function, make use of control in such a way that robust stability and robust performance are ensured for highly nonlinear systems. Model-based H∞ optimization technique elaborates the robustness and stability of the system by reducing tracking error of all its states towards origin and thereafter system becomes stable for an infinite period. The loop-shaping control performance as compared to H∞ model-based control has some limitations to ensure closed-loop robustness and real-time implementation under perturbations. The performance evaluation is done at the end which shows that the H∞ model-based control gives optimal robust performance including perturbations and coupling effect. The real-time implementation on MATLAB/Simulation via personal computer validates the worth of the optimization method in the presence of uncertainties (matched, unmatched, coupling effect) of a linearized state-space model of the TRMS system.

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“…To address this, AO systems with predictive control methods are an active area of interest. Some methods which use the statistical models of atmospheric turbulence, with some assumptions on its structure, have been proposed [6], [7]. Controllers designed by first estimating the dynamics of the disturbance either online using recursive optimisation [8], or using subspace identification [9] have been proposed.…”

Section: Introductionmentioning

confidence: 99%

Direct Data-Driven Vibration Control for Adaptive Optics

Gupta,

Karimi,

Wildi

et al. 2023

2023 62nd IEEE Conference on Decision and Control (CDC)

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Adaptive optics (AO) systems are used in groundbased telescopes to improve image resolutions, especially for long-exposure photography, by compensating for the effects of atmospheric turbulence and internal vibrations. Most current AO systems are based on simple control laws that either neglect the temporal correlation in atmospheric turbulence, use a simplified system model, or both. This paper presents a direct data-driven control scheme to compute an optimal controller using the frequency-domain representation of the disturbance and the system model. Numerical simulations of the AO system demonstrate performance improvement compared to standard AO control schemes, and resilience to the variance in atmospheric turbulence and internal vibrations.

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Mixed sensitivity H-infinity control of an adaptive optics system

Cited by 9 publications

References 5 publications

A flexible mixed-optimization with H∞ control for coupled twin rotor MIMO system based on the method of inequality (MOI)- An experimental study

A flexible mixed-optimization with H∞ control for coupled twin rotor MIMO system based on the method of inequality (MOI)- An experimental study

H∞ Model Based Control via Mixed Sensitivity for 2DOF Control of Twin Rotor MIMO System With Experimental Validation

Direct Data-Driven Vibration Control for Adaptive Optics

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