Predictive Optimal Management Method for the control of polygeneration systems
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Recent results have suggested that online Model Predictive Control (MPC) can be computed quickly enough to control fast sampled systems. High-speed applications impose a hard real-time constraint on the solution of the MPC problem, which generally prevents ...
The purpose of this article (...) is to derive an algorithm for solving stochastic linear quadratic control problems over infinite time horizon using a primal-dual semidefinite programming approach. ...
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 ...
The algorithm based on nonlinear optimisation as presented in this paper is applicable to the control of complex processes. The systematic approach is doing without the formulation of rules. In case of competing control targets a weighting in the sense of ...
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 ...
La consommation des ressources energetiques est actuellement un enjeu primordial, notamment dans le secteur du batiment, qui represente à lui seul 42 % de l’energie consommee en France. La mixite energetique, renouvelable et fossile, ainsi qu’une meilleure ...
A linear quadratic model predictive controller (MPC) can be written as a parametric quadratic optimization problem whose solution is a piecewise affine (PWA) map from the state to the optimal input. While this `explicit solution' can offer several orders o ...
This paper describes how an undergraduate control course is enhanced with Sysquake interactive applications. Basic concepts in control theory, different ways to assess performance and robustness of a controlled system, and limits of closed-loop systems are ...
In this paper a combination of brain emotional learning based intelligent controllers (BELBICs) is employed to control an unidentified practical overhead crane. The proposed controller is a model free controller and has the capability to deal with multi-ob ...
In many control problems the measurement instances might not be available in a periodically-equally-distributed way and/or the same might occur to the control signals. Moreover, due to the sensor evaluation time, calibration of actuators and sensors, or re ...