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A common approach when applying reinforcement learning to address control problems is that of first learning a policy based on an approximated model of the plant, whose behavior can be quickly and safely explored in simulation; and then implementing the obtained policy to control the actual plant. Here we follow this approach to learn to engage a(More)
This paper presents an overview of model-based (Iterative Learning Control, Model Predictive Control and Iterative Optimization) and non-model-based (Genetic-based Machine Learning and Reinforcement Learning) learning strategies for the control of wet clutches. Based on theoretical considerations and a validation on an experimental test bench containing wet(More)
We present a Mechatronics design approach and related technologies for a badminton playing robot, as a first stage of a multi-year project. The robot is using non-modified shuttles and rackets, which are detected and localized using purely visual information. The robot subsystems are presented: mechanical design, visual detection of the shuttle, shuttle(More)
Modeling of hydraulic clutch transmissions are not straightforward because of their hard nonlinearities. Therefore a model-free optimizer is used to tune the input parameters for desired operation, thereby generating optimal reference trajectory. However these machines suffer from time varying dynamics, hence a feedback predictive control is used to track(More)
This paper discusses energy optimal point-to-point motion control for linear time-invariant (LTI) systems using energy-optimal Model Predictive Control (EOMPC). The developed EOMPC, which is based on time-optimal MPC, aims at performing energy-optimal point-to-point motions within a required motion time. Energy optimality is achieved by setting the object(More)
It is well known that universal approximators can be used for adaptive control and estimation. In this paper, the problem of adaptive state observation of a large class of nonlinear uncertain systems is considered and it is shown that splines have some special properties, which can lead to simplified observer structure. In particular, the observer filter(More)