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Flutter suppression of wind turbine blade section based on two types of model prediction control (MPC) algorithms is investigated. The pre-twist blade, exhibiting displacements of flap-wise bending and lead-lag bending, employs 2D airfoil analysis method, and is subjected to destructive divergent instability displacements. Dynamic modelling of two-dimensional (2D) blade section is based on data analysis characterized by data fitting. The MPC methods including standard MPC and terminal-weight MPC are used to realize flutter suppression for divergent instability. Vibration control and control effects of terminal-weight MPC on divergent instability are analyzed in detail, with different parameters of prediction horizon and control horizon discussed. The superiority of terminal-weight MPC can be apparently demonstrated by comparison of standard MPC and sliding mode control with disturbance observer (SMCDO). The feasibility of hardware implementation of MPC algorithm is discussed by human-computer interaction platform. The performance improvement method of the terminal-weight MPC based on offset control has been refined from the point of view of practical application, with its remarkable effect compared with the original terminal-weight MPC. [ABSTRACT FROM AUTHOR]

Piezo-actuated micro-/nanopositioning systems have been widely employed in diverse high-precision positioning applications. However, the inherent hysteresis nonlinearity seriously deteriorates the tracking performance of piezo-actuated stages. This paper presents the design, analysis, and validation of a novel control scheme termed model prediction control (MPC) with real-time modified reference based on disturbance observer (DOB) to suppress the hysteresis nonlinearity and model uncertainty, in which the nonlinear effects are treated as an unknown disturbance to the system. In order to remove the most of the interference and diminish the effect of noise, a DOB is designed for the non-minimum phase (NMP) system. Then the difference between the actual displacement and the output of the nominal model termed the residual error is estimated and used to modify the reference in real time for a better performance. By the proposed method, the model of the inherent hysteresis is not required and the controller is established based on the identified nominal model. Its effectiveness is validated through experimental investigations on a commercial nanopositioner. Experimental results show that the proposed method can improve the tracking performance of the piezo-actuated stage, as compared with the traditional MPC and DOB-based MPC. [ABSTRACT FROM AUTHOR]

An adaptive-prediction-horizon model prediction control-based path tracking controller for a four-wheel independent control electric vehicle is designed. Unlike traditional model prediction control with fixed prediction horizon, this paper devotes to satisfy the varied path tracking demand by adjusting online the prediction horizon of model prediction control according to its effect on vehicle dynamic characteristics. Vehicle dynamic stability quantized with the vehicle sideslip-feature phase plane is preferentially considered in the prediction horizon adjustment. For stability during switching prediction horizon and for robustness during path tracking, the numerical problem inherent in the adaptive-prediction-horizon model prediction control is analysed and solved by introducing exponentially decreasing weight. Subsequently, the desired motion for path tracking with the four-wheel independent control electric vehicle is realized with a hierarchical control structure. Simulation results finally illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]