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Your search keyword '"Werner, Herbert"' showing total 196 results
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196 results on '"Werner, Herbert"'

26. Practical model predictive control for a class of nonlinear systems using linear parameter-varying representations

Author

Abbas, Hossam Seddik, Cisneros, Pablo S. G., Männel, Georg, Rostalski, Philipp, Werner, Herbert, Abbas, Hossam Seddik, Cisneros, Pablo S. G., Männel, Georg, Rostalski, Philipp, and Werner, Herbert

Abstract

In this paper, a practical model predictive control (MPC) for tracking desired reference trajectories is demonstrated for controlling a class of nonlinear systems subject to constraints, which comprises diverse mechanical applications. Owing to the linear parameter-varying (LPV) formulation of the associated nonlinear dynamics, the online MPC optimization problem is solvable as a single quadratic programming (QP) problem of complexity similar to that of LTI systems. For offset-free tracking, based on the notion of admissible reference, the controller ensures convergence to any admissible reference while its deviation from the desired reference is penalized in the stage cost of the optimization problem. This mechanism provides a safety feature under the physical limitations of the system. To guarantee stability and recursive feasibility, a terminal cost as a tracking error penalty term and a terminal constraint associated with both the terminal state and the admissible reference are included. We use tube-based concept to deal with the uncertainty of the scheduling parameter over the prediction horizon. Therefore, the online optimization problem is solved for only the nominal system corresponding to the current value of the scheduling parameter and subject to tightened constraint sets. The proposed approach has been implemented successfully in real-time onto a robotic manipulator, the experimental results illustrates its efficiency and practicality.

Published
2021

38. Event-Triggered Fixed-Time Attitude Consensus With Fixed and Switching Topologies.

Author

Jin, Xin, Shi, Yang, Tang, Yang, Werner, Herbert, and Kurths, Jurgen

Subjects
CONFIGURATION space, ALGEBRAIC topology, TIME perception, MULTIAGENT systems, DISTRIBUTED algorithms
Abstract

In this article, event-triggered attitude consensus is considered for multiagent systems with guaranteed fixed-time convergence. Due to the non-Euclidean property of the attitude configuration space, the attitude consensus is more challenging to achieve under the sampled-data setting. An event-triggered attitude consensus protocol and event-triggered condition are proposed based on the axis–angle attitude representation. The fixed-time attitude consensus is reached if the initial attitudes lie in local regions on the attitude configuration space. The theoretical results reveal that the settling time is related to the interevent interval and the algebraic connectivity of the topology graph. We further consider the consensus protocol under a jointly connected graph, and establish the settling time estimation that depends on the switching instants. Numerical simulations are conducted to verify the validity of the theoretical results finally. [ABSTRACT FROM AUTHOR]

Published
2022
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45. A Velocity Algorithm for Nonlinear Model Predictive Control.

Author

Cisneros, Pablo S. G. and Werner, Herbert

Subjects
PREDICTION models, ONLINE algorithms, VELOCITY, ALGORITHMS, MATHEMATICAL optimization
Abstract

This brief presents a velocity-form nonlinear model predictive control (NMPC) scheme via velocity-based linearization. The main features of this approach are built-in offset-free control in the presence of disturbances, tracking of piecewise constant, possibly unreachable, reference signals, and simple implementation, as a parameterization of all equilibria is not necessary. Furthermore, the model in velocity form can be expressed as a quasi-linear parameter-varying (quasi-LPV) model, for which efficient online optimization algorithms exist. The proposed approach is experimentally validated on a 2-degree-of-freedom robotic manipulator, where its capabilities and efficiency are highlighted. [ABSTRACT FROM AUTHOR]

Published
2021
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