Learning a feasible and stabilizing explicit model predictive control law by robust optimization
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J. V. Kadam, W. Marquardt Lehrstuhl für Prozesstechnik, RWTH Aachen University, Turmstr. 46, 52064 Aachen, Germany B. Srinivasan, D. Bonvin Laboratoire d’Automatique, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland Optimization of T ...
This paper is concerned with input adaptation in dynamic processes in order to guarantee feasible and optimal operation despite the presence of uncertainty. For optimal control problems having mixed control-state constraints, two sets of directions can be ...
This paper addresses a question raised by a leading expert in the identification of multivariable systems: “Is it necessary to excite all reference signals for the identification of a multivariable system operating in closed loop with a linear time-invaria ...
The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic importance. However, optimal operation is particularly difficult to achieve when the process model used in the optimizat ...
We propose a model predictive control approach to path-following problems of constrained nonlinear systems. We directly consider input and state constraints. Furthermore, we introduce an extended corridor path-following problem, which allows to add spatial ...
In this thesis, a new framework to design controllers in the frequency domain is proposed. The method is based on the shaping of the open-loop transfer function in the Nyquist diagram. A line representing a lower approximation for the crossover frequency a ...
Data-driven controller tuning for model reference control problem is investigated. A new controller tuning scheme for linear time-invariant single- input single-output systems is proposed. The method, which is based on the correlation approach, uses a sing ...
In a recent work, a frequency method based on linear programming is proposed to design fixed-order linearly parameterized controllers for stable linear multi- model SISO systems. The method is based on the shaping of the open-loop transfer functions in the ...
Optimization arises naturally when process performance needs improvement. This is often the case in industry because of competition – the product has to be proposed at the lowest possible cost. From the point of view of control, optimization consists in de ...
We analyze properties of closed-loop systems based on explicit model predictive control (MPC) when parameters of the controllers are changing. Formulation of the problem in the framework of MPC with a cost based on piecewise linear norms leads to the gener ...