International journal of computer assisted radiology and surgery
May 23, 2022
PURPOSE: The navigation of endovascular guidewires is a dexterous task where physicians and patients can benefit from automation. Machine learning-based controllers are promising to help master this task. However, human-generated training data are sc...
Computational intelligence and neuroscience
May 23, 2022
Multi-intelligent decision-making has a good development at present. Based on a series of technologies such as artificial intelligence, multi-intelligent decision-making is involved in many aspects, and the country also attaches great importance to t...
Autonomous navigation in dynamic environments where people move unpredictably is an essential task for service robots in real-world populated scenarios. Recent works in reinforcement learning (RL) have been applied to autonomous vehicle driving and t...
This paper, with the adaptive backstepping technique, presents a novel fixed-time neural networks leader-follower consensus tracking control scheme for a class of nonaffine nonlinear multiagent systems. The expression of the error system is derived, ...
In this article, the problem of passivity and dissipativity analysis is investigated for a class of fractional-order quaternion-valued fuzzy memristive neural networks. Based on the famous nonlinear scalarizing function, a nonlinear scalarization met...
This article presents an improved guidance law for underactuated marine vessels that compensates cross-track error caused by external disturbances through its sideslip. The proposed guidance law demonstrates improved path-following performance regard...
This article proposes an adaptive neural-network control scheme for a rigid manipulator with input saturation, full-order state constraint, and unmodeled dynamics. An adaptive law is presented to reduce the adverse effect arising from input saturatio...
In this article, direct adaptive actuator failure compensation control is investigated for a class of noncanonical neural-network nonlinear systems whose relative degrees are implicit and parameters are unknown. Both the state tracking and output tra...
This article addresses the adaptive neural tracking control problem for a class of uncertain stochastic nonlinear systems with nonstrict-feedback form and prespecified tracking accuracy. Some radial basis function neural networks (RBF NNs) are used t...
This research first proposes the general expression of Zhang et al. discretization (ZeaD) formulas to provide an effective general framework for finding various ZeaD formulas by the idea of high-order derivative simultaneous elimination. Then, to sol...
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