This paper presents modeling and control of nonlinear hybrid systems using multiple
linearized models. Each linearized model is a local representation of all locations of the …

For implementation of various model based techniques such as in control and fault
diagnosis, data-driven identification is key for enabling cheap and rapid development of …

The mining industry has much potential for automation. A great deal of work has been done
on this subject and is still ongoing. With automation comes the possibility for optimization …

In this paper, we propose a Bernstein polynomial based global optimization algorithm for the
optimal feedback control of nonlinear hybrid systems using a multiple-model approach …

This paper deals with the model predictive control (MPC) of an industrial hybrid process
where continuous and batch units operate jointly: the crystallization section of a sugar …

The current work is motivated by the need of achieving global solution and better
computational efficiency for control of any arbitrary nonlinear hybrid dynamical systems …

This paper presents an efficient optimization algorithm suitable for online solution of mixed
integer nonlinear programs resulting from the model predictive control (MPC) of nonlinear …

This paper deals with a control problem related with a mixed continuous-batch process, in
which some continuous variables must be kept as close as possible at prescribed values …

It is well known that most assembly skills can be regarded as one of the signal-symbol
hybrid dynamical systems, since the interactive dynamics between the end-effector and the …

This paper deals with a control problem related with a mixed continuous-batch process, a
pilot plant of our Lab, where both continuous decisions and scheduling takes place. We tried …