In this paper, we investigate strategies to enhance turbine energy capture and mitigate fatigue loads using pulsed light detection and ranging (LIDAR) system-enabled torque control strategies. To enhance energy capture when a turbine is operating below rated wind speed, three advanced LIDAR-enabled torque controllers are proposed: the disturbance tracking control (DTC) augmented with LIDAR, the optimally tracking rotor (OTR) control augmented with LIDAR, and LIDAR-based preview control. The DTC with LIDAR and LIDAR-based preview control is combined with a linear quadratic regulator in the feedback path, while OTR is a strategy adapted from a quadratic <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> Ω <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> torque feedback control. These control strategies are simulated in turbulent wind files and their performance is compared against the baseline <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> Ω <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> control scheme. We also consider the effects of different LIDAR update rates and range gates. It is shown that LIDAR-enabled controllers have only a small effect on energy capture at the cost of increased control action and low-speed shaft torque load. However, when considering a combination of fatigue load mitigation, power capture enhancement, and control authority requirements, the LIDAR-enabled preview controller outperforms the baseline <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> Ω <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> controller.