Facultad Regional San Francisco

Permanent URI for this communityhttp://48.217.138.120/handle/20.500.12272/109

Browse

Author: search.filters.author.Pipino, HugoSubject: search.filters.subject.Model predictive control

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Nonlinear temperature regulation of solar collectors with a fast adaptive polytopic LPV MPC formulation
    (2020-09-11) Pipino, Hugo; Morato, Marcelo M.; Bernardi, Emanuel; Adam, Eduardo J.; Normey-Rico, Julio E.
    Temperature control in solar collectors is a nonlinear problem: the dynamics of temperature rise vary according to the fluid flowing through the collector and to the temperature gradient along the collector area. In this way, this work investigates the formulation of a Model Predictive Control (MPC) application developed within a Linear Parameter Varying (LPV) formalism, which serves as a model of the solar collector process. The proposed system is an adaptive MPC, developed with terminal set constraints and considering the scheduling polytope of the model. At each instant, two Quadratic Programming (QPs) programs are solved: the first considers a backward horizon of N steps to find a virtual model-process tuning variable that defines the best LTI prediction model, considering the vertices of the polytopic system; then, the second QP uses this LTI model to optimize performances along a forward horizon of N steps. The paper ends with a realistic solar collector simulation results, comparing the proposed MPC to other techniques from the literature (linear MPC and robust tube-MPC). Discussions regarding the results, the design procedure and the computational effort for the three methods are presented. It is shown how the proposed MPC design is able to outrank these other standard methods in terms of reference tracking and disturbance rejection.
  • Thumbnail Image
    Item
    Adaptive multi-model predictive control applied to continuous stirred tank reactor
    (2021-02-06) Pipino, Hugo; Cappelletti, Carlos Alberto; Adam, Eduardo J.
    This paper investigates the design of a Model Predictive Control ( MPC ) formulation for the case of poly- topic multi-model system representation. An adaptive MPC is developed taking into account the schedul- ing parameters in the multi-model and a terminal invariant set for all the systems that are within the system polytope. This proposed method uses a virtual model-process tuning variable, which is optimized to find the best Linear Time Invariant ( LTI ) prediction sequence for the horizon, based on the LTI vertices of the polytopic system. Finally, the proposed adaptive MPC is applied to a continuous stirred tank reac- tor (CSTR) system. Discussions are set upon the a-priori design procedure, the online computational effort and application difficulties.
  • Thumbnail Image
    Item
    Sub-optimal Linear Parameter Varying Model Predictive Control for Solar Collectors
    (IEEE, Institute of Electrical and Electronics Engineers, 2020-02-26) Morato, Marcelo M.; Pipino, Hugo; Bernardi, Emanuel; Ferreyra, Diego M.; Adam, Eduardo J.; Normey-Rico, Julio E.
    This short paper investigates the temperature control of a flat-plate water-heating solar collector. This nonlinear system is modelled via a quasi-linear parameter varying setting. To address this control problem, a model predictive control algorithm is formulated, considering a frozen guess for the evolution of the scheduling parameters, set-sequence constraints and a Lyapunov-decreasing terminal cost. The advantage of this method is that it uses standard quadratic programming problems and does not have to resort to nonlinear optimization. Through simulation, it is demonstrated that it can yield successful performances.