This study discusses vehicle stability control based on explicit nonlinear model predictive (NMPC) and investigates the influence of prediction fidelity controller performance. The solutions are generated through an algorithm using multiparametric quadratic programming (mp-QP) approximations (mp-NLP) problems. Controllers with different models assessed objective indicators in sine-with-dwell te...

Lately, nonlinear model predictive control (NMPC) has been successfully applied to (semi-) autonomous driving problems and proven be a very promising technique. However, accurate models for real vehicles could require costly time-demanding specific measurements. To address this problem, the exploitation of system data complement or derive prediction NMPC explored, employing <italic xmlns:mml="h...

Nonlinear Model Predictive Control (NMPC) formulations through quasi-Linear Parameter Varying (qLPV) embeddings have been brought to focus in recent literature. The qLPV realisation of the nonlinear dynamics yields linear predictions at each sampling instant. Thereby, these strategies generate online programs with reduced numerical burden, much faster solve than Programs generated regular NMPC....

We consider the problem of controlling continuous-time sector bounded Lur’e systems subject to state and input constraints. First, we derive a linear static feedback law which stabilizes Lur’e systems with uncertain nonlinearities. The approach is then used to calculate the terminal region and the terminal penalty term for quasi-infinite horizon nonlinear model predictive control (NMPC). The re...

Polymorphism, a phenomenon in which a substance can have more than one crystal form, is a frequently encountered phenomenon in pharmaceutical compounds. Different polymorphs can have very different physical properties such as crystal shape, solubility, hardness, color, melting point, and chemical reactivity, so that it is important to ensure consistent production of the desired polymorph. In th...

This paper presents a novel Nonlinear Model Predictive Control (NMPC) scheme for underwater robotic vehicles operating in a constrained workspace including static obstacles. The purpose of the controller is to guide the vehicle towards specific way points with guaranteed input and state constraints (i.e obstacle avoidance, workspace boundaries). The proposed scheme incorporates the full dynamic...

In this paper, a real-time capable Nonlinear Model Predictive Controller (NMPC) is implemented for the attitude control of an upper stage launch vehicle with liquid propellant. A mass spring model is used as an analogy to simulate the disturbance generated by the sloshing propellant. For the implementation of the NMPC, an optimal control problem (OCP) is defined with finite time horizon. The ob...

Mobile medical robots have been widely used in various structured scenarios, such as hospital drug delivery, public area disinfection, and examinations. Considering the challenge of environment modeling controller design, how to achieve information from human demonstration a directly arouse our interests. Learning skills is powerful way that can reduce complexity algorithm searching space. This...

This work is focused on the position control of an underactuated brachiation mobile robot with 3 links. We present the modeling of the dynamics of the robot and introduce the application of the nonlinear model-based predictive control (NMPC) to such a system. The robot has 3 revolute joints but only one of them is actuated, i. e., the robot has less control inputs than degrees of freedom. The i...