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

Fuzzy Virtual Reference Model Sensorless Tracking Control for Linear Induction Motors

Accepted[[abstract]]This paper introduces a fuzzy virtual reference model (FVRM) synthesis method for linear induction motor (LIM) speed sensorless tracking control. First, we represent the LIM as a T-S fuzzy model. Second, we estimate the immeasurable mover speed and secondary flux by a fuzzy observer. Third, to convert the speed tracking control into a stabilization problem, we define the internal desired states for state tracking via an FVRM. Finally, by solving a set of linear matrix inequalities (LMIs), we obtain the observer gains and the control gains where exponential convergence is guaranteed. The contributions of the approach in this paper are three folds: i) simplified approach -- speed tracking problem converted to stabilization problem; ii) omit need of actual reference model -- fuzzy virtual reference model generates internal desired states; and iii) unification of controller and observer design -- control objectives are formulated into LMI problem where powerful numerical toolboxes solve controller and observer gains. Finally, experiments are carried out to verify the theoretical results and show satisfactory performance both in transient response and robustness.[[notice]]補正完畢[[journaltype]]國外[[incitationindex]]SCI[[incitationindex]]EI[[ispeerreviewed]]Y[[booktype]]紙本[[booktype]]電子版[[countrycodes]]US

Robust observer-based output feedback control for fuzzy descriptor systems

[[abstract]]This paper proposes a robust observer-based output feedback control for fuzzy descriptor systems. First, we represent singular nonlinear dynamic system into Takagi–Sugeno (T–S) fuzzy descriptor model which have a tighter representation for a wider class of nonlinear systems in comparison to general state-space models. To achieve the control objective, we design a fuzzy controller and observer in a unified and systematic manner. The stability analysis of the overall closed-loop fuzzy system leads to formulation of linear matrix inequalities (LMIs). The advantages of the approach are three fold. First, we consider conditions of immeasurable states which allows a practical design of sensorless control systems. Secondly, we address the robustness issue in the system which avoids control performance deterioration or instability due to disturbance or approximation errors in the system. Third, we formulate the overall control problem into LMIs. Using the observer and controller gains by solving LMIs, we carry out numerical simulations which verify theoretical statements.[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Chatter mitigation in milling process using discrete time sliding mode control with type 2-fuzzy logic system

In order to achieve a high-quality machining process with superior productivity, it is very important to tackle the phenomenon of chatter in an effective manner. The problems like tool wear and improper surface finish affect the milling process and are caused by self-induced vibration termed as chatter. A strategy to control chatter vibration actively in the milling process is presented. The mathematical modeling of the process is carried out initially. In this paper, an innovative technique of discrete time sliding mode control (DSMC) is blended with the type-2 fuzzy logic system. The proposed active controller results in a significantly high mitigation of vibration. The DSMC is linked to the time-varying gain which is an innovative approach to mitigate chattering. The theorem is laid down which validates that the system states are bounded in the case of DSMC-type-2 fuzzy. Stability analysis is carried out using Lyapunov candidate. The nonlinearities linked with the cutting forces and damper friction are handled effectively by using the type-2 fuzzy logic system. The performance of the DSMC-type-2 fuzzy concept is compared with the discrete time PID (D-PID) and discrete time sliding mode control for validating the effectiveness of the controller. The better performance of DSMC-type-2 fuzzy over D-PID and DSMC-T1 fuzzy in the minimization of milling chatter are validated by a numerical analysis approach

Output Feedback Control of Fuzzy Descriptor Systems with Interval Time-Varying Delay.

[[abstract]]This paper proposes output feedback control for fuzzy descriptor systems with interval time-varying delay. First, singular nonlinear dynamic systems with interval time-varying delay are taken into consideration. Then using a Takagi-Sugeno (T-S) fuzzy model, we design a fuzzy representation of the original nonlinear system. This fuzzy representation consists of local linear descriptor systems. To achieve the control objective, a fuzzy controller and observer is designed in a systematic manner. The stability analysis of the overall closed-loop fuzzy system leads to formulation of linear matrix inequalities. Using the observer and controller gains by solving LMIs, we carry out numerical simulations which verify theoretical statements.[[iscallforpapers]]