With the development of Internet of Things (IoT), 5 G, and cloud computing technologies, the
amount of data from manufacturing systems has been increasing rapidly. With massive …

The dynamic error of CNC machine tools, which often exceeds the quasi-static error at high-
speed machining, becomes the main reason affecting the machining error of the sculptured …

Ball screw feed-drive system (BSFDS) is the precision transmission mechanism widely used
in micron-scale positioning or motion trajectory control. Its desired specifications including …

Waterflooding optimization in closed-loop management of the oil reservoirs is always
considered as a challenging issue due to the complicated and unpredicted dynamics of the …

A contemporary policy gradient-based optimization scheme is presented for active structural
control by exerting the concept of reinforcement learning (RL). The RL-based control …

An adaptive proportional–integral–derivative (PID) controller based on Q‐learning algorithm
is proposed to balance the cart–pole system in simulation environment. This controller was …

Tuning the seismic control systems in order to achieve optimal performance is a challenging
area due to the system and disturbance uncertainties. Although, model uncertainties …

High-performance position control in machine tools can only be achieved modeling the
dynamic behavior of the mechatronic system composed by the motor, transmission and …

In this paper a reinforcement learning based nonlinear control strategy for control of boost
converters is presented. Control of boost converters is a challenging nonlinear control …

The key issue that prevents application of Reinforcement Learning (RL) methods in complex
control scenarios is lack of convergence to meaningful decision policies (ie policies that …