Disturbance observer-based nonfragile fuzzy tracking control of a spacecraft

Han, Tae Joon; Kim, Han Sol

doi:10.1016/j.asr.2022.11.043

Cited by 3 publications

(1 citation statement)

References 43 publications

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“…AUVs, operating in unpredictable conditions like ocean currents and water pressure, require controllers capable of tolerating disturbances. The widely adopted H ∞ control attenuates disturbance affecting T-S fuzzy model-based control systems [26][27][28][29]. Thus, there has been active research on H ∞ control; for instance, in [30], H ∞ performance criteria were applied to handle exogenous inputs, and ref.…”

Section: Introductionmentioning

confidence: 99%

Interval Type-2 Fuzzy-Model-Based Sampled-Data Control of an AUV Depth System with Input Saturation

An,

Kim

2024

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This paper proposes a sampled-data fuzzy controller design technique for an autonomous underwater vehicle (AUV) depth system represented by an interval type-2 (IT-2) fuzzy model, considering input saturation. In the Takagi–Sugeno (T–S) fuzzy model of an AUV depth system, surge velocity is chosen as a premise variable. To address the associated uncertainty with this variable, we employ the IT-2 fuzzy modeling technique. Also, the controller proposed in this paper utilizes time-varying gains, ensuring superior exponential stability compared with traditional fixed gain approaches. Furthermore, a membership function-dependent (MFD) H∞ criterion is employed to enhance robustness for each subsystem individually. Taking into account the mentioned aspects, the controller design condition is derived in the form of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed method is validated through simulation examples.

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Section: Introductionmentioning

confidence: 99%

Interval Type-2 Fuzzy-Model-Based Sampled-Data Control of an AUV Depth System with Input Saturation

An,

Kim

2024

Actuators

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Nonlinear model predictive control of a satellite attitude dynamics in SO(3)

Sánchez,

Aldana,

Lungu

et al. 2023

2023 27th International Conference on System Theory, Control and Computing (ICSTCC)

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Non-Fragile Fuzzy Tracking Control for Nonlinear Networked Systems with Dynamic Quantization and Randomly Occurring Gain Variations

Wang

2023

Mathematics

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This paper investigates the observer-based non-fragile output feedback tracking control problem for nonlinear networked systems with randomly occurring gain variations. The considered nonlinear networked systems are represented by a Takagi–Sugeno (T–S) fuzzy model. The dynamical quantization methodology is employed to achieve the reasonable and efficacious utilization of the limited communication resources. The objective is to design the observer-based non-fragile output feedback tracking controller, such that the resulting system is mean-square asymptotically stable with the given H∞ tracking performance. Based on the descriptor representation strategy combined with the S-procedure, sufficient conditions for the existence of the desired dynamic quantizers and observer-based non-fragile tracking controller are proposed in the form of linear matrix inequalities. Finally, simulation results are provided to show the effectiveness of the proposed design method

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Disturbance observer-based nonfragile fuzzy tracking control of a spacecraft

Cited by 3 publications

References 43 publications

Interval Type-2 Fuzzy-Model-Based Sampled-Data Control of an AUV Depth System with Input Saturation

Interval Type-2 Fuzzy-Model-Based Sampled-Data Control of an AUV Depth System with Input Saturation

Nonlinear model predictive control of a satellite attitude dynamics in SO(3)

Non-Fragile Fuzzy Tracking Control for Nonlinear Networked Systems with Dynamic Quantization and Randomly Occurring Gain Variations

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