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A standard model predictive controller (MPC) can be written as a parametric optimization problem whose solution is a piecewise affine (PWA) map from the measured state to the optimal control input. The primary limitation of this optimal `explicit solution ...
Limits on the storage space or the computation time restrict the applicability of model predictive controllers (MPC) in many real problems. Currently available methods either compute the optimal controller online or derive an explicit control law. In this ...
This presentation show the successful usage of LabVIEW on the Mac with a specific focus on control solutions. First, 15 years of control solutions with LabVIEW on the Mac are reviewed. Then it presents current DAQmx base solutions, using as an example a Sp ...
Model predictive control (MPC) is a very effective approach to control nonlinear systems, especially when the systems are high dimensional and/or constrained. MPC formulates the problem of input trajectory generation as an optimization problem. However, du ...
In the past, computational motor control has been approached from at least two major frameworks: the dynamic systems approach and the viewpoint of optimal control. The dynamic system approach emphasizes motor control as a process of self-organization betwe ...
In industrial polymerization processes, several grades of polymer are frequently produced in the same plant by changing the operating conditions. Transitions between the different grades are rather slow and result in the production of a considerable amount ...
This thesis deals with dynamic optimization of batch processes, i.e. processes that are characterized by a finite time of operation and the frequent repetition of batches. The objective is to maximize the quantity of the desired product at final time while ...
We consider an optimization problem arising in the design of controllers for OLED displays. Our objective is to minimize the amplitude of the electrical current flowing through the diodes which has a direct impact on the lifetime of such a display. The opt ...
In the batch process industry, the available models carry a large amount of uncertainty and can seldom be used to directly optimize real processes. Several measurement-based optimization methods have been proposed to deal with model mismatch and process di ...
In the framework of real-time optimization, measurements are used to compensate for effects of uncertainty. The main approach uses measurements to update the parameters of a process model. In contrast, the constraint-adaptation scheme uses the measurements ...