UDE-based robust boundary control for an unstable parabolic PDE with unknown input disturbance

Dai, Jiguo; Ren, Beibei

doi:10.1016/j.automatica.2018.03.080

Cited by 41 publications

(16 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [36], backstepping method are used into a DPS based on wave PDE dynamics with a moving free boundary. In [37], UDE technique was used to develop boundary control for handling the uncertainty and disturbances in an unstable parabolic system. In [35], [38], the authors developed iterative learning control method for stabilizing the distributed parameter systems.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Control of an Offshore Ocean Thermal Energy Conversion System

Liu

et al. 2020

IEEE Trans. Syst. Man Cybern, Syst.

View full text Add to dashboard Cite

Boundary control strategy is developed to analyze the vibration problem of the offshore ocean thermal energy conversion (OTEC) system as well as to constrain the bottom tension and top motion. To provide an accurate dynamic behavior for the OTEC system, this distributed parameter system is modeled and formulated with a governing equation and boundary conditions (PDE-ODEs model). Two robust adaptive boundary controllers are designed and disposed at the endpoints of the system, and the stability of the controlled system under unknown disturbances is achieved. After selecting the relevant parameters appropriately, the offset of the offshore OTEC system can be suppressed to equilibrium position. Finally, the effectiveness of the proposed control is illustrated by simulation.

show abstract

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Control of an Offshore Ocean Thermal Energy Conversion System

Liu

et al. 2020

IEEE Trans. Syst. Man Cybern, Syst.

View full text Add to dashboard Cite

show abstract

“…In recent years, considerable attention has been paid to various PDE systems. For example, 2 investigated disturbance attenuation control for parabolic PDE systems, 3 studied boundary estimation for hyperbolic PDE systems, and Reference 4 considered finite‐time control for delayed reaction–diffusion systems. However, these mentioned results were all reported for linear PDE systems.…”

Section: Introductionmentioning

confidence: 99%

Takagi–Sugeno fuzzy‐model‐based event‐triggered point control for semilinear partial differential equation systems using collocated pointwise measurements

Song

Wang

Zhang

et al. 2020

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This paper addresses event‐triggered point control design for semilinear partial differential equation systems by using pointwise measurements. First, the nonlinear terms existing in the plant are approximated by Takagi–Sugeno fuzzy model, based on which a novel fuzzy controller is constructed. The main novelties of the control strategy are summarized as follows: (1) The one‐dimensional space is divided into L parts, and only a few points need to measure. (2) Event‐triggered communication scheme is introduced to save the limited transmission channel. (3) Pointwise control is considered to reduce the control cost via utilizing limited actuators. Second, the conditions that guarantee the stability of the closed‐loop system are established by using Lyapunov direct method and some inequality techniques including Wirtinger's and Halanay's inequalities, and the controller gains can be obtained via solving linear matrix inequalities. Third, three simulation examples are provided to verify the effectiveness and superiority of the proposed approach.

show abstract

“…In [25], a UDE‐based robust power flow controller is developed for the grid‐connected inverters to achieve accurate power delivery. In addition, the UDE‐based control approaches have been found effective in many other applications, such as the wind turbine [26], robot system [27], piezoelectric stages [28], heat conduction system [29], aircraft [30], electric motor [31] and active magnetic bearing [32].…”

Section: Introductionmentioning

confidence: 99%