This paper presents a novel method to address the actuator saturation for nonlinear hybrid
systems by directly incorporating user-defined input bounds in a controller design. In …

Learning optimal feedback control laws capable of executing optimal trajectories is essential
for many robotic applications. Such policies can be learned using reinforcement learning or …

One approach to obtain the optimal control inputs that maximize the reward, is to solve the
equation, as this differential equation expresses a sufficient and necessary condition for …

Wind farm power control is key to reliable large-scale wind integration. The design of a
sophisticated wind farm controller, however, is challenging partly because there is a lack of …

The Wiener process has provided a lot of practically useful mathematical tools to model
stochastic noise in many applications. However, this framework is not enough for modeling …

This paper considers feedback systems with asymmetric (ie, non-odd functions) nonlinear
actuators and sensors. While the stability of such systems can be investigated using the …

Augmenting feedback control systems with disturbance observer (DOB) is a widely used
technique in system design to compensate for the effect of exogenous disturbances as well …

Linear quadratic tracker (LQT) is usually employed to solve unconstrained tracking problems
but falls short when dealing with systems exhibiting actuator saturation. This paper presents …

Quasilinear control (QLC) theory provides a set of methods intended for the analysis and
design of stochastic feedback systems with static nonlinearities. QLC leverages the method …

Quasilinear Control (QLC) is a set of methods for analysis and design of systems with
nonlinear actuators and sensors. The approach of QLC is based on the method of stochastic …