This paper presents an active safety system for avoiding obstacles and preventing road departures by means of assistance in steering and braking. A Nonlinear Model Predictive Controller (NMPC) is designed with the goal of using the minimum control intervention to keep the driver safe. The NMPC uses a nonlinear vehicle and driver steering model to predict a collision or a roadway departure. The ...

In the past decade the field of nonlinear model predictive control (NMPC) has witnessed steadily increasing attention from control practitioners. Its popularity comes from the fact that today’s processes need to be operated under much tighter performance specifications while at the same time more and more constraints, stemming for example from environmental and safety considerations, need to be...

A recurrent neural network-based nonlinear model predictive control (NMPC) scheme in parallel with PI control loops is developed for a simulation model of an industrial-scale five-stage evaporator. Input-output data from system identification experiments are used in training the network using the Levenberg-Marquardt algorithm with automatic differentiation. The same optimization algorithm is us...

The purpose of this paper is twofold. In the first part we give a review on the current state of nonlinear model predictive control (NMPC). After a brief presentation of the basic principle of predictive control we outline some of the theoretical, computational, and implementational aspects of this control strategy. Most of the theoretical developments in the area of NMPC are based on the assum...

This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of ...

We develop a state-of-the-art nonlinear model predictive controller (NMPC) for periodic unstable systems, and apply the method to a dual line kite that shall fly loops. The kite is described by a nonlinear unstable ODE system (which we freely distribute), and the aim is to let the kite fly a periodic figure. Our NMPC approach is based on the “infinite horizon closed loop costing” scheme to ensu...

Nonlinear Model Predictive Control (NMPC) algorithms are based on various nonlinear models. A number of on-line optimization approaches for outputfeedback NMPC based on various black-box models can be found in the literature. However, NMPC involving on-line optimization is computationally very demanding. On the other hand, an explicit solution to the NMPC problem would allow efficient on-line c...

In this paper, we present a nonlinear model predictive control (NMPC) for multiple autonomous helicopters in a complex.environment. The NMPC provides a framework to solve optimal discrete control problems for a nonlinear system under state constraints and input saturation. Our approach combines stabilization of vehicle dynamics and decentralized trajectory generation, by including a potential f...

Set Membership function estimation methodologies under the Nearest Point approach are employed to compute an approximating function for a nonlinear model predictive controller (NMPC). The method is based on the off-line computation of a finite number ν of exact NMPC control solutions. The obtained approximating functions fulfill input constraints, have computational time which is independent on...

In this paper, we develop an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) for a complete spray drying plant with multiple stages. In the E-NMPC the initial state is estimated by an extended Kalman Filter (EKF) with noise covariances estimated by an autocovariance least squares method (ALS). We present a model for the spray drying plant and use this model for simulation...