Data-driven nonlinear MPC using dynamic response surface methodology

For many complex processes, it is desirable to use a nonlinear model in the MPC design, and the recently proposed Dynamic Response Surface Methodology (DRSM) is capable of accurately modeling nonlinear continuous processes over semi-infinite time horizons. We exploit the DRSM to identify nonlinear data-driven dynamic models that are used in an NMPC. We demonstrate the ability and effectiveness of the DRSM data-driven model to be used as the prediction model for a nonlinear MPC regulator. This DRSM model is efficiently used to solve a non-equally-spaced finite-horizon optimal control problem so that the number of decision variables is reduced. The proposed DRSM-based NMPC is tested on a representative nonlinear process, an isothermal CSTR in which a second-order irreversible reaction is taking place. It is shown that the obtained quadratic data-driven model accurately represents the open-loop process dynamics and that DRSM-based NMPC is an effective data-driven implementation of nonlinear MPC

Offset-free economic mpc based on modifier adaptation: Investigation of several gradient-estimation techniques

Various offset-free economic model predictive control schemes that include a disturbance model and the modifier-adaptation principle have been proposed in recent years. These schemes are able to reach plant optimality asymptotically even in the presence of plant–model mismatch. All schemes are affected by a major issue that is common to all modifier-adaptation formulations, namely, plant optimality (note that convergence per se does not require perfect plant gradients) requires perfect knowledge of static plant gradients, which is a piece of information not known in most practical applications. To address this issue, we present two gradient-estimation techniques, one based on Broyden’s update and the other one on linear regression. We apply these techniques for the estimation of either the plant gradients or the modifiers directly. The resulting economic MPC schemes are tested in a simulation and compared on two benchmark examples of different complexity with respect to both convergence speed and robustness to measurement noise

Validación del Índice Funcional para Osteoartritis de Manos (FIHOA) en pacientes con artritis reumatoidea

El FIHOA fue desarrollado para evaluar la capacidad funcional de pacientes con OA de manos. Objetivo: validar FIHOA en pacientes con AR. Métodos: estudio analítico, observacional prospectivo de corte transversal. Se incluyeron pacientes consecutivos con diagnóstico de AR (ACR/EULAR 2010). Se consignaron datos demográficos y características de la enfermedad. Todos los pacientes completaron los siguientes cuestionarios autoadministrados: FIHOA, HAQ-A, HAQ-UP-A y Quick DASH. En un subgrupo de pacientes, una terapista ocupacional valoró la capacidad funcional de la mano por medio del test de SODA-A. Se evaluó la reproducibilidad de FIHOA. Análisis estadístico: estadística descriptiva. Confiabilidad con test de Cronbach. Validez de constructo con correlación de Spearman. Reproducibilidad test re-test. Modelo de regresión lineal