Linear parameter varying (LPV) modeling and control have been investigated extensively in the last two decades. However, a plethora of research work in both theory and application of LPV systems is still under study. The core idea in this dissertation is to explore state-of-the-art applications of LPV systems in controlling nonlinear plants and comparing the closed-loop performance with conventional control methods. Nonlinear systems can be cast into LPV framework and well-established LPV controller synthesis techniques are applied to them using linear matrix inequalities (LMI) which can be solved efficiently using polynomial-time algorithms.

We investigate the stability and performance analysis of micro-electromechanical system (MEMS) actuators, smart base isolation of structures using magneto-rheological (MR) dampers and multi-input-multi-output (MIMO) control of large-scale horizontal axis wind turbines. Different approaches are proposed to stabilize and control the nonlinear unstable dynamics of a gap-closing MEMS actuator. An integrated approach of parameter identification and control of MR dampers based on Bouc-Wen hysteresis model is developed and simulated. Two modified Bingham and LuGre-based models are proposed to capture the static friction (stiction) and force-flattening properties of a sponge-type MR damper and their hardware-in-the-loop parameter identification. An H_∞ inverse controller based on the modified LuGre model and a dynamic output-feedback LPV controller based on the modified Bingham model are proposed and experimented for seismic protection of a two-story model building. A lumped model is developed for wind turbines and validated in time and frequency domains using FAST code. LPV controllers are designed and simulated for full operating region of a wind turbine using the FAST nonlinear model. The closed-loop responses of the LPV controller and a traditional PI-scheduled controller for the NREL 5MW baseline wind turbine are compared. In the end, a novel approach toward integrated structure and LPV controller design of wind turbines is formulated and solved by iterative LMI problems to improve the closed-loop performance in terms of minimizing structural fatigue loads and maximizing power capture.