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@article{WOS:001616300100001,
title = {Geometry Analysis and Experimental Study for Vibration Damping of
Rectangular Plate},
author = {Haining Sun and Shuzhi Sam Ge},
doi = {10.1109/TMECH.2025.3626951},
times_cited = {0},
issn = {1083-4435},
year = {2025},
date = {2025-11-01},
journal = {IEEE-ASME TRANSACTIONS ON MECHATRONICS},
publisher = {IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC},
address = {445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA},
abstract = {The effectiveness of vibration damping in rectangular plates depends not
only on the control strategy but also on the geometric layout of the
actuators. This study proposes a control-integrated geometry selection
strategy that directly incorporates closed-loop control behavior. The
geometry of cable-driven robots is analyzed by determining the number of
cables required and identifying the positions of anchor points on the
plate. A performance evaluation index is introduced, which
simultaneously considers stabilization time, maximum cable force, and
the number of cables. The selection strategy can provide optimized
results tailored to diverse objectives, such as shorter stabilization
time, reduced cable force, or fewer cables. Drawing on the patterns of
the control input of the designed deep reinforcement learning-based
controller, a new control law with customizable functions is developed,
allowing for flexible output force modulation. It addresses the highly
irregular nature of reinforcement learning-based control inputs and
enhances the practicality in real-world applications. By combining the
proposed control law with the geometry selection strategy, this study
examines the effect of different geometric layouts on vibration damping
in a rectangular plate under two distinct boundary conditions. A
six-meter-scale experimental platform is constructed to assess sixteen
geometric layouts under these two boundary conditions. Simulation and
experimental results validate the practical feasibility of the geometry
selection strategy for improving the vibration-damping effect in
rectangular plates.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{WOS:001329005900001,
title = {Compliant Tracking Control and Force Redistribution for a Portable
Cable-Driven Robot},
author = {Haining Sun and Xiaoqiang Tang and Shuzhi Sam Ge},
doi = {10.1109/TMECH.2024.3457890},
times_cited = {1},
issn = {1083-4435},
year = {2025},
date = {2025-08-01},
journal = {IEEE-ASME TRANSACTIONS ON MECHATRONICS},
volume = {30},
number = {4},
pages = {2710-2721},
publisher = {IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC},
address = {445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA},
abstract = {This study introduces the development of a portable cable-driven robot
with a compliant trajectory tracking method that incorporates real-time
and continuous positive force redistribution. Based on the dynamic model
of the robot, a rapid-convergence tracking controller exhibiting
variable compliance to external disturbances is designed to ensure
stable trajectory tracking. A real-time, continuous positive force
redistribution process is seamlessly integrated into the tracking
controller to ensure that cable forces remain positive and continuous
throughout the motion. Low compliance allows the robot to resist
external disturbances and maintain accurate trajectory tracking.
Conversely, high compliance permits the robot to temporarily sacrifice
some tracking accuracy for safety and then resume tracking once the
disturbance subsides. Lyapunov stability analysis is utilized to
validate the stability of the control system. Experiments are conducted
on the designed robot to evaluate the practical applicability of the
control method. Results demonstrate the feasibility of the force
redistribution without compromising trajectory tracking performance.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{WOS:001371956200001,
title = {Tracking Control With Adjustable Trajectory Envelope for Cable-Driven
Robots},
author = {Haining Sun and Rongqiao Zhang and Ruihang Ji and Xiaoqiang Tang and Shuzhi Sam Ge},
doi = {10.1109/TIE.2024.3503591},
times_cited = {0},
issn = {0278-0046},
year = {2025},
date = {2025-07-01},
journal = {IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS},
volume = {72},
number = {7},
pages = {7128-7138},
publisher = {IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC},
address = {445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA},
abstract = {In industrial applications, insufficient motor torque and overload
issues can limit the control force in cable-driven robots (CDRs),
affecting the stability and robustness of trajectory tracking control.
This work presents a specialized tracking controller to achieve stable
trajectory tracking under constrained control forces. The controller
incorporates a trajectory envelope system that actively adjusts the
permissible range of the actual trajectory. When control forces approach
their upper limits, the envelope automatically expands and reduces the
precision requirement for trajectory tracking. The controller then
ensures that the actual trajectory remains within the designated
permissible boundaries, thereby maintaining controllable trajectory
tracking. The stability of the control system is validated using the
Lyapunov method. Experimental validations on CDRs with one, two, and
four cables are conducted. Both simulations and experiments confirm the
effectiveness of the proposed tracking controller under conditions of
constrained motor output torque.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{WOS:001466201200001,
title = {Adaptive fault tolerant cooperative control for hybrid nonlinear
multiagent systems via switching functional},
author = {Huaying Li and Qinmin Yang and Meng Zhang and Zhengguang Wu and Shuzhi Sam Ge},
doi = {10.1016/j.automatica.2025.112298},
times_cited = {3},
issn = {0005-1098},
year = {2025},
date = {2025-07-01},
journal = {AUTOMATICA},
volume = {177},
publisher = {PERGAMON-ELSEVIER SCIENCE LTD},
address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND},
abstract = {This paper investigates the fault tolerant cooperative control of
strict-feedback hybrid multiagent systems with unknown nonlinear
dynamics. The hybrid multiagent systems consist of both continuous-time
and discrete-time agents, which suffer from potential multiple actuator
faults. To deal with the sampled neighborhood information for
continuous-time agents and to generate n-step prediction for
discrete-time agents, hybrid distributed estimators are developed to
estimate the state of the leader. To mitigate the impact by faulty
actuators, a unified learning-based switching functional is introduced
to select different sets of actuators automatically and locate the
healthy set. By this means, the requirement for fault identification or
fault detection and isolation mechanisms is relaxed. The controllers for
continuous-time and discrete-time agents are designed separately for
accommodating the difference between their dynamics. Through Lyapunov
analysis, it is shown that the followers' output can track the leader's
output and all the signals in the closed-loop are bounded. The numerical
studies verify the effectiveness of the proposed scheme. (c) 2025
Elsevier Ltd. All rights are reserved, including those for text and data
mining, AI training, and similar technologies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}

@article{WOS:001470759100001,
title = {Reinforcement Learning-Based Fault-Tolerant Control of Uncertain
Strict-Feedback Nonlinear Systems With Intermittent Actuator Faults},
author = {Qinmin Yang and Huaying Li and Zhengwei Ruan and Bo Fan and Shuzhi Sam Ge},
doi = {10.1109/TNNLS.2025.3550527},
times_cited = {3},
issn = {2162-237X},
year = {2025},
date = {2025-06-01},
journal = {IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS},
volume = {36},
number = {6},
pages = {10464-10478},
publisher = {IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC},
address = {445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA},
abstract = {In this work, a novel reinforcement learning-based adaptive
fault-tolerant control (FTC) scheme with actuator redundancy is
presented for a nonlinear strict-feedback system with nonlinear dynamics
and uncertainties. A learning-based switching function technique is
established to steer different groups of actuators automatically and
successively to mitigate the impact of faulty actuators by observing a
switching performance index. The optimal tracking control problem (OTCP)
of strict-feedback nonlinear systems is transformed into an equivalent
optimal regulation problem of each affine subsystem via adaptive
feedforward controllers. Subsequently, the designed objective functions
associated with Hamilton-Jacobi-Bellman (HJB) estimate errors caused by
neural network (NN) approximations can be minimized by the reinforcement
learning algorithm without value or policy iterations. It is proved that
the tracking objective can be achieved and all signals in the
closed-loop system can be guaranteed to be bounded, as long as the
minimum time interval between two successive failures is bounded.
Theoretical results are verified by simulations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}