A review on flexible robotic systems for minimally invasive surgery
OM Omisore, S Han, J Xiong, H Li, Z Li… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Recently, flexible robotic systems are developed to enhance minimally invasive
interventions on internal organs located in confined areas of human body. These surgical …
interventions on internal organs located in confined areas of human body. These surgical …
Robust neurooptimal control for a robot via adaptive dynamic programming
We aim at the optimization of the tracking control of a robot to improve the robustness, under
the effect of unknown nonlinear perturbations. First, an auxiliary system is introduced, and …
the effect of unknown nonlinear perturbations. First, an auxiliary system is introduced, and …
Simultaneously encoding movement and sEMG-based stiffness for robotic skill learning
Transferring human stiffness regulation strategies to robots enables them to effectively and
efficiently acquire adaptive impedance control policies to deal with uncertainties during the …
efficiently acquire adaptive impedance control policies to deal with uncertainties during the …
Adaptive tracking control of state constraint systems based on differential neural networks: A barrier Lyapunov function approach
RQ Fuentes-Aguilar, I Chairez - IEEE transactions on neural …, 2020 - ieeexplore.ieee.org
The aim of this article is to investigate the trajectory tracking problem of systems with
uncertain models and state restrictions using differential neural networks (DNNs). The …
uncertain models and state restrictions using differential neural networks (DNNs). The …
Neural network-based distributed adaptive pre-assigned finite-time consensus of multiple TCP/AQM networks
In this study, a class of finite-time consensus of multiple transmission control protocol/active
queue management (TCP/AQM) networks is investigated on the basis of a design idea of …
queue management (TCP/AQM) networks is investigated on the basis of a design idea of …
Trajectory generation by chance-constrained nonlinear MPC with probabilistic prediction
Continued great efforts have been dedicated toward high-quality trajectory generation
based on optimization methods; however, most of them do not suitably and effectively …
based on optimization methods; however, most of them do not suitably and effectively …
Neural networks-based fixed-time control for a robot with uncertainties and input deadzone
D Zhang, L Kong, S Zhang, Q Li, Q Fu - Neurocomputing, 2020 - Elsevier
In this paper, neural networks-based fixed-time control is presented for a robot with
uncertainties and actuator input deadzone. Model-based fixed-time control for the robot has …
uncertainties and actuator input deadzone. Model-based fixed-time control for the robot has …
Energy saving quadrotor control for field inspections
This article presents a control strategy to improve the energy efficiency of a quadrotor for
field inspections. A power consumption analytical model for a quadrotor is constructed …
field inspections. A power consumption analytical model for a quadrotor is constructed …
Neural learning control of a robotic manipulator with finite-time convergence in the presence of unknown backlash-like hysteresis
A neural learning-based finite-time control policy is presented for a robotic manipulator with
unknown backlash-like hysteresis and system uncertainties. Adaptive neural networks are …
unknown backlash-like hysteresis and system uncertainties. Adaptive neural networks are …
Object transportation with force-sensorless control and event-triggered synchronization for networked uncertain manipulators
This article proposes a distributed control method for networked manipulators to
cooperatively transport an unmodeled object without force measurement. First, we design an …
cooperatively transport an unmodeled object without force measurement. First, we design an …