In this paper, a novel Virtual State-feedback Reference Feedback Tuning (VSFRT) and Approximate Iterative Value Iteration Reinforcement Learning (AI-VIRL) are applied for learning linear reference model output (LRMO) tracking control of observable sy...
This paper proposes the combination of two data-driven techniques, namely virtual reference feedback tuning (VRFT) and model-Free Control (MFC) in terms of the VRFT of MFC algorithms dedicated to servo systems. VRFT ensures the automatic optimal comp...
Microalgae are photosynthetic microorganisms capable of fixing CO2 to produce O2 and a wide variety of metabolites of interest. Attempts have been made to describe their growth dynamics using mathematical models; however, these models fail to fully r...
Data-driven controller synthesis methods use input/output information to find the coefficients of a proposed control architecture. Virtual Reference Feedback Tuning (VRFT) is one of the most popular frameworks due to its simplicity and one-shoot synt...
This paper focuses on validating a model-free Value Iteration Reinforcement Learning (MFVI-RL) control solution on a visual servo tracking system in a comprehensive manner starting from theoretical convergence analysis to detailed hardware and softwa...
This paper proposes a neural network (NN)-based control scheme in an Adaptive Actor-Critic (AAC) learning framework designed for output reference model tracking, as a representative deep-learning application. The control learning scheme is model-free...
Closed-loop control is desirable in direct energy deposition (DED) to stabilize the process and improve the fabrication quality. Most existing DED controllers require system identifications by experiments to obtain plant models or layer-dependent ada...
A hierarchical learning control framework (HLF) has been validated on two affordable control laboratories: an active temperature control system (ATCS) and an electrical rheostatic braking system (EBS). The proposed HLF is data-driven and model-free,...
This article is concerned with digital, multimodal feedback that supports learning and assessment within education. Drawing on the research literature alongside a case study from a postgraduate program in digital education, I argue that approaching f...
The aim of this study is to develop an adaptive automatic control method for solving the trajectory tracking problem for a biped robotic device (BRD) and taking into account that each articulation is mobilized by a linear actuator. Each extremity of...