A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses dynamic integrated system optimisation and parameter estimation (DISOPE) which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimisation procedure. A new method for approximating some Jacobian trajectories required by the algorithm is introduced. It is shown that the iterative procedure associated with the algorithm naturally suits applications to batch chemical processes
The input profiles (trajectories) that are implemented during the operation of a semi-batch process ...
A novel optimising controller is designed that leads a slow process from a sub-optimal operational c...
In the batch process industry, the available models carry a large amount of uncertainty and can seld...
A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality di...
For the optimization of dynamic systems, it is customary to use measurements to combat the effect of...
A novel threefold optimization algorithm is proposed to simultaneously solve the nonlinear model pre...
An algorithm for solving nonlinear discrete time optimal control problems with model-reality differe...
DISOPE is a technique for solving optimal control problems where there are differences in structure ...
Dynamic optimization of batch processes has attracted more attention in recent years since, in the f...
A batch process is characterized by the repetition of time-varying operations of finite duration. Du...
The optimization of batch processes has attracted attention in recent years because, in the face of ...
Batch processes are usually complex and highly nonlinear systems. Modeling error can be the cause of...
This thesis is focused on the development and application of innovative methods and algorithms for t...
Batch processes are common in the pharmaceuticals, specialty and fine chemicals industries. Unlike c...
Dynamic models describe many operations and processes that take place in several disciplines, includ...
The input profiles (trajectories) that are implemented during the operation of a semi-batch process ...
A novel optimising controller is designed that leads a slow process from a sub-optimal operational c...
In the batch process industry, the available models carry a large amount of uncertainty and can seld...
A novel algorithm for solving nonlinear discrete time optimal control problems with model-reality di...
For the optimization of dynamic systems, it is customary to use measurements to combat the effect of...
A novel threefold optimization algorithm is proposed to simultaneously solve the nonlinear model pre...
An algorithm for solving nonlinear discrete time optimal control problems with model-reality differe...
DISOPE is a technique for solving optimal control problems where there are differences in structure ...
Dynamic optimization of batch processes has attracted more attention in recent years since, in the f...
A batch process is characterized by the repetition of time-varying operations of finite duration. Du...
The optimization of batch processes has attracted attention in recent years because, in the face of ...
Batch processes are usually complex and highly nonlinear systems. Modeling error can be the cause of...
This thesis is focused on the development and application of innovative methods and algorithms for t...
Batch processes are common in the pharmaceuticals, specialty and fine chemicals industries. Unlike c...
Dynamic models describe many operations and processes that take place in several disciplines, includ...
The input profiles (trajectories) that are implemented during the operation of a semi-batch process ...
A novel optimising controller is designed that leads a slow process from a sub-optimal operational c...
In the batch process industry, the available models carry a large amount of uncertainty and can seld...