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We present a nonlinear model predictive control (MPC) scheme for tracking of dynamic target signals. The scheme combines stabilization and dynamic trajectory planning in one layer, thus ensuring constraint satisfaction irrespective of…

Systems and Control · Electrical Eng. & Systems 2020-10-21 Johannes Köhler , Matthias A. Müller , Frank Allgöwer

This paper studies high-speed online planning in dynamic environments. The problem requires finding time-optimal trajectories that conform to system dynamics, meeting computational constraints for real-time adaptation, and accounting for…

Robotics · Computer Science 2025-02-21 Gilhyun Ryou , Lukas Lao Beyer , Sertac Karaman

Trajectory prediction facilitates effective planning and decision-making, while constrained trajectory prediction integrates regulation into prediction. Recent advances in constrained trajectory prediction focus on structured constraints by…

Robotics · Computer Science 2025-03-19 Hao Ma , Zhiqiang Pu , Shijie Wang , Boyin Liu , Huimu Wang , Yanyan Liang , Jianqiang Yi

In many mechatronic applications, controller input costs are negligible and time optimality is of great importance to maximize the productivity by executing fast positioning maneuvers. As a result, the obtained control input has mostly a…

Systems and Control · Electrical Eng. & Systems 2025-01-28 Joe Ismail , Steven Liu

Underwater gliders are increasingly deployed in challenging missions - such as hurricane-season observations and long-endurance environmental monitoring - where strong currents and turbulence pose significant risks to navigation safety. To…

Systems and Control · Electrical Eng. & Systems 2025-12-25 Hanzhi Yang , Nina Mahmoudian

This article proposes an approach for collision avoidance, path following, and anti-grounding of autonomous surface vessels under consideration of environmental forces based on Nonlinear Model Predictive Control (NMPC). Artificial Potential…

Systems and Control · Electrical Eng. & Systems 2024-03-29 Daniel Menges , Trym Tengesdal , Adil Rasheed

In this paper, we propose an adaptive event-triggered reinforcement learning control for continuous-time nonlinear systems, subject to bounded uncertainties, characterized by complex interactions. Specifically, the proposed method is…

Machine Learning · Computer Science 2024-10-01 Umer Siddique , Abhinav Sinha , Yongcan Cao

This paper considers the stabilization of nonlinear continuous-time dynamical systems employing periodic event-triggered control (PETC). Assuming knowledge of a stabilizing feedback law for the continuous-time system with a certain…

Systems and Control · Electrical Eng. & Systems 2019-09-02 Michael Hertneck , Steffen Linsenmayer , Frank Allgöwer

This paper presents a learning-based approach for impromptu trajectory tracking for non-minimum phase systems, i.e., systems with unstable inverse dynamics. Inversion-based feedforward approaches are commonly used for improving tracking…

Robotics · Computer Science 2018-03-08 Siqi Zhou , Mohamed K. Helwa , Angela P. Schoellig

Underactuated systems like sea vessels have degrees of motion that are insufficiently matched by a set of independent actuation forces. In addition, the underlying trajectory-tracking control problems grow in complexity in order to decide…

Systems and Control · Electrical Eng. & Systems 2021-04-02 Mohammed Abouheaf , Wail Gueaieb , Md. Suruz Miah , Davide Spinello

If embedded with command filter properly, the implementation of backstepping design could be dramatically simplified. In this paper, we introduce a command filter with time-varying gain and integrate it with backstepping design, resulting…

Systems and Control · Electrical Eng. & Systems 2022-01-11 Hefu Ye , Yongduan Song

We study tracking control for uncertain nonlinear multi-input, multi-output systems modelled by $r$-th order functional differential equations (encompassing systems with arbitrary strict relative degree) in the presence of input…

Optimization and Control · Mathematics 2023-04-18 Thomas Berger

Control of machine learning models has emerged as an important paradigm for a broad range of robotics applications. In this paper, we present a sampling-based nonlinear model predictive control (NMPC) approach for control of neural network…

Robotics · Computer Science 2022-10-06 Iman Askari , Babak Badnava , Thomas Woodruff , Shen Zeng , Huazhen Fang

Most of the optimal guidance problems can be formulated as nonconvex optimization problems, which can be solved indirectly by relaxation, convexification, or linearization. Although these methods are guaranteed to converge to the global…

Optimization and Control · Mathematics 2024-03-19 Gyubin Park , Jiwoo Choi , Da Hoon Jeong , Jong-Han Kim

Real-time adaptive control of nonlinear systems with unknown dynamics and time-varying disturbances demands precise modeling and robust parameter adaptation. While existing neural network-based strategies struggle with computational…

Systems and Control · Electrical Eng. & Systems 2025-06-17 Mingcong Li

Fixed-wing unmanned aerial vehicles (UAVs) offer significant performance advantages over rotary-wing UAVs in terms of speed, endurance, and efficiency. However, these vehicles have traditionally been severely limited with regards to…

Robotics · Computer Science 2020-01-31 Max Basescu , Joseph Moore

This paper presents a systematic approach for designing robust linear proportional-integral (PI) servo-controllers that effectively manage control input and output constraints in flight control systems. The control design leverages the…

Systems and Control · Electrical Eng. & Systems 2026-03-09 Marcel Menner , Eugene Lavretsky

This paper presents a nonlinear control algorithm for speed control of a permanent magnet motor. The idea relies on a feedback linearization technique which also ensures adherence to current and voltage bounds. These bounds arise from…

Systems and Control · Electrical Eng. & Systems 2019-11-27 Shravan Mohan

Previous results reported in the robotics literature show the relationship between time-delay control (TDC) and proportional-integral-derivative control (PID). In this paper, we show that incremental nonlinear dynamic inversion (INDI) -…

Systems and Control · Computer Science 2021-12-06 Paul Acquatella B. , Wim van Ekeren , Qi Ping Chu

In this article we present a novel discrete-time design approach which reduces the deteriorating effects of sampling on stability and performance in digitally controlled nonlinear mechanical systems. The method is motivated by recent…

Systems and Control · Electrical Eng. & Systems 2021-04-30 Paul Kotyczka , Tobias Thoma