Abstract. The paper deals with the application of model reference adaptive control to robot impedance control, which is actually a technique of steering the end-effector on a presc...
Detecting and predicting a program’s execution phases are crucial to dynamic optimizations and dynamically adaptable systems. This paper shows that a phase can be associated with...
Jinpyo Kim, Sreekumar V. Kodakara, Wei-Chung Hsu, ...
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Information about instruction criticality can be used to control the application of micro-architectural resources efficiently. To this end, several groups have proposed methods t...
We present an extension of the Dynamics Based Control (DBC) paradigm to environment models based on Predictive State Representations (PSRs). We show an approximate greedy version ...
Ariel Adam, Zinovi Rabinovich, Jeffrey S. Rosensch...