Modern advances in technology have led to more complex manufacturing processes whose
success centres on the ability to control these processes with a very high level of accuracy …

We introduce a novel inversion-based neurocontroller for solving control problems involving
uncertain nonlinear systems that could also compensate for multi-valued systems. The …

We introduce a technique for quantifying and then exploiting uncertainty in nonlinear
stochastic control systems. The approach is suboptimal though robust and relies upon the …

A set of real-time control experiments applied to a non-linear system is presented. The
system is an overhead crane and the experiments are applied on a low-cost scale model of …

A real-time control laboratory is presented here. The experiments are based on a non-linear
plant and are oriented to undergraduate courses on digital control and intelligent control …

A neuromorphic adaptive generalized predictive control (NAGPC) is presented. This
controller is based on the use of neural networks for the adaptive tuning of the output …

This paper presents a general methodology for estimating and incorporating uncertainty in
the controller and forward models for noisy nonlinear control problems. Conditional …