Sensory data have becoming widely available in large volume and variety due to the
increasing presence and adoption of the Internet of Things. Such data can be tremendously …

In this paper, we present a new adaptive dynamic programming approach by integrating a
reference network that provides an internal goal representation to help the systems learning …

Tracking maneuvering target in real time autonomously and accurately in an uncertain
environment is one of the challenging missions for unmanned aerial vehicles (UAVs). In this …

In this study, we investigate the accelerated learning control schemes for point-to-point
tracking systems (PTSs) with measurement noise. The asymptotic convergence of the …

In this article, a model-free-learning algorithm is proposed to solve the tracking problem of
linear discrete-time systems with completely unknown system dynamics. To eliminate …

Frequent state monitoring and controller updates can enhance the precision of tracking
control, while simultaneously overburdening the communication network transmission. In …

With the increase of urbanization rate, the problem of water shortage and pollution is more
and more serious. It is important to improve the efficiency of wastewater treatment to protect …

In this paper, we proposed a new nonlinear tracking controller based on heuristic dynamic
programming (HDP) with the tracking filter. Specifically, we integrate a goal network into the …

An intelligent data-driven predictive control strategy is proposed in this paper. The predictive
controller is designed by combining predictive control and local weighted projection …

Path tracking has a significant impact on the success of long-term autonomous underwater
vehicle (AUV) missions in terms of safety, energy-saving, and efficiency. However, it is a …