To deploy Micro Aerial Vehicles (MAVs) in real-world applications, there is a need for online methods to cope with uncertainties localization and external disturbances. In this article, we propose set of novel real-time embedded Nonlinear Model Predictive Control (NMPC) Moving Horizon Estimation (NMHE) modules MAV based disturbance rejection. The NMPC NMHE are on the dynamic model MAV, thus, av...

Any proper operation could be translated as a constrained optimization problem inside a WWTP, whose nonlinear behavior renders its control problems quite attractive for performance of multivariable optimization–based control technique algorithms, such as NMPC. The main advantage of this control technique lies in its ability to handle model nonlinearity as well as various types of constraints on...

Agile quadrotor flight in challenging environments has the potential to revolutionize shipping, transportation, and search rescue applications. Nonlinear model predictive control (NMPC) recently shown promising results for agile control, but relies on highly accurate models maximum performance. Hence, uncertainties form of unmodeled complex aerodynamic effects, varying payloads parameter mismat...

This paper starts by reviewing the mathematical model for tumor growth as well as the pharmacokinetics and pharmacodynamics models of the drug, so that the therapy can be as close as possible to reality. A Nonlinear Model Predictive Control algorithm (NMPC ) is used to find the optimal drug dose, in order to reduce the bone marrow tumor density. The Recursive Least Squares algorithm is used to ...

Among the several problems arising in the Airborne Wind Energy paradigm, an essential one is the control of the tethered airfoil trajectory during power generation. Tethered flight is a fast, strongly nonlinear, unstable and constrained process, motivating control approaches based on fast Non-linear Model Predictive Control. In this paper, a computationally efficient model is proposed, based on...

−Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impeded by linear models due to the lack of a similarly accepted nonlinear modeling or databased technique. Aimed at solving this problem, the paper addresses three issues: (i) extending second-order Volterra nonlinear MPC (NMPC) to higher-order for improved prediction ...

Wiener models consist of a linear dynamic element followed by a static non linear element. This paper shows a non linear model predictive control (NMPC) based on a piecewise linear; the Wiener model is applied on an experimental control of pH. The static nonlinear element of the Wiener model is approximated using piecewise linear function. Identification using optimal local linear model is appl...

In this paper we propose a non-linear model predictive controller architecture (NMPC) for trajectory tracking of an omni-directional mobile robot. The controller employs a simplified process model to predict the evolution of the state of the robot which allows for real-time minimization of the cost function using gradient descent methods. The cost function is chosen so as to penalize the positi...

In this paper we present a nonlinear model predictive control (NMPC) strategy that can be used to tackle nonlinear control problems with changing model parameters, unknown disturbance factors and specifications on the rates of change of the inputs. The closed-loop performance of the proposed NMPC strategy is demonstrated by applying it to the problem of blood glucose normalization in critically...

Hybrid electric vehicles (HEVs) are used as a bridge during the transition to battery (BEVs) and make energy consumption more efficient. The main problem in improving efficiency of HEV is torque management. In this study, novel approach based on nonlinear model predictive controller solve reference tracking distribution proposed. That say, order increase distribution, weights control (NMPC) tra...