17,421 research outputs found
Terminal sliding mode control strategy design for second-order nonlinear system
This study mainly focuses on the terminal sliding mode control (TSMC) strategy design, including an adaptive terminal sliding mode control (ATSMC) and an exact-estimator-based terminal sliding mode control (ETSMC) for second-order nonlinear dynamical systems. In the ATSMC system, an adaptive bound estimation for the lump uncertainty is proposed to ensure the system stability. On the other hand, an exact estimator is designed for exact estimating system uncertainties to solve the trouble of chattering phenomena caused by a sign function in ATSMC law in despite of the utilization of a fixed value or an adaptive tuning algorithm for the lumped uncertainty bound. The effectiveness of the proposed control schemes can be verified in numerical simulations.<br /
Regression on manifolds: Estimation of the exterior derivative
Collinearity and near-collinearity of predictors cause difficulties when
doing regression. In these cases, variable selection becomes untenable because
of mathematical issues concerning the existence and numerical stability of the
regression coefficients, and interpretation of the coefficients is ambiguous
because gradients are not defined. Using a differential geometric
interpretation, in which the regression coefficients are interpreted as
estimates of the exterior derivative of a function, we develop a new method to
do regression in the presence of collinearities. Our regularization scheme can
improve estimation error, and it can be easily modified to include lasso-type
regularization. These estimators also have simple extensions to the "large ,
small " context.Comment: Published in at http://dx.doi.org/10.1214/10-AOS823 the Annals of
Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Active actuator fault-tolerant control of a wind turbine benchmark model
This paper describes the design of an active fault-tolerant control scheme that is applied to the actuator of a
wind turbine benchmark. The methodology is based on adaptive filters obtained via the nonlinear geometric
approach, which allows to obtain interesting decoupling property with respect to uncertainty affecting the
wind turbine system. The controller accommodation scheme exploits the on-line estimate of the actuator
fault signal generated by the adaptive filters. The nonlinearity of the wind turbine model is described by the
mapping to the power conversion ratio from tip-speed ratio and blade pitch angles. This mapping represents
the aerodynamic uncertainty, and usually is not known in analytical form, but in general represented by
approximated two-dimensional maps (i.e. look-up tables). Therefore, this paper suggests a scheme to
estimate this power conversion ratio in an analytical form by means of a two-dimensional polynomial, which
is subsequently used for designing the active fault-tolerant control scheme. The wind turbine power generating
unit of a grid is considered as a benchmark to show the design procedure, including the aspects of
the nonlinear disturbance decoupling method, as well as the viability of the proposed approach. Extensive
simulations of the benchmark process are practical tools for assessing experimentally the features of the
developed actuator fault-tolerant control scheme, in the presence of modelling and measurement errors.
Comparisons with different fault-tolerant schemes serve to highlight the advantages and drawbacks of the
proposed methodology
Active fault tolerant control for nonlinear systems with simultaneous actuator and sensor faults
The goal of this paper is to describe a novel fault tolerant tracking control (FTTC) strategy based on robust fault estimation and compensation of simultaneous actuator and sensor faults. Within the framework of fault tolerant control (FTC) the challenge is to develop an FTTC design strategy for nonlinear systems to tolerate simultaneous actuator and sensor faults that have bounded first time derivatives. The main contribution of this paper is the proposal of a new architecture based on a combination of actuator and sensor Takagi-Sugeno (T-S) proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators together with a T-S dynamic output feedback control (TSDOFC) capable of time-varying reference tracking. Within this architecture the design freedom for each of the T-S estimators and the control system are available separately with an important consequence on robust Lâ‚‚ norm fault estimation and robust Lâ‚‚ norm closed-loop tracking performance. The FTTC strategy is illustrated using a nonlinear inverted pendulum example with time-varying tracking of a moving linear position reference. Keyword
Active sensor fault tolerant output feedback tracking control for wind turbine systems via T-S model
This paper presents a new approach to active sensor fault tolerant tracking control (FTTC) for offshore wind turbine (OWT) described via Takagi–Sugeno (T–S) multiple models. The FTTC strategy is designed in such way that aims to maintain nominal wind turbine controller without any change in both fault and fault-free cases. This is achieved by inserting T–S proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators to be capable to estimate different generators and rotor speed sensors fault for compensation purposes. Due to the dependency of the FTTC strategy on the fault estimation the designed observer has the capability to estimate a wide range of time varying fault signals. Moreover, the robustness of the observer against the difference between the anemometer wind speed measurement and the immeasurable effective wind speed signal has been taken into account. The corrected measurements fed to a T–S fuzzy dynamic output feedback controller (TSDOFC) designed to track the desired trajectory. The stability proof with H∞ performance and D-stability constraints is formulated as a Linear Matrix Inequality (LMI) problem. The strategy is illustrated using a non-linear benchmark system model of a wind turbine offered within a competition led by the companies Mathworks and KK-Electronic
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