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The recent surge in biosignal-based control signifies a profound paradigm shift in biomedical engineering. This innovative approach has injected new life into control theory, ushering in advancements in human-body interaction and control. Surface Electromyography (sEMG) emerges as a pivotal biosignal, attracting considerable attention for its wide-ranging applications across medicine, science, and engineering, particularly in the domain of functional rehabilitation. This study delves into the use of sEMG signals for controlling a robotic arm, with the overarching aim of improving the quality of life for people with disabilities in Vietnam. Raw sEMG signals are acquired via appropriate sensors and subjected to a robust processing methodology involving analog-to-digital conversion, band-pass and low-pass filtering, and envelope detection. To demonstrate the efficacy of the processed sEMG signals, this study introduces a robotic arm model capable of mimicking intricate human finger movements. Employing a fuzzy logic control strategy, the robotic arm demonstrates successful operation in experimental trials, characterized by swift response times, thereby positioning it as a valuable assistive device for people with disabilities. This investigation not only validates the feasibility of sEMG-based control for robotic arms, but also underscores its potential to significantly improve the lives of individuals with disabilities, a demographic that represents a substantial portion (approximately 8%) of the Vietnamese population. [ABSTRACT FROM AUTHOR]

In an electric power grid, Load-Frequency Control (LFC) plays a crucial role as it aims to maintain the system frequency at a nominal value, 50 or 60 Hz, by minimizing the effects of load changes. However, a modern power system is currently characterized by a huge number of nonlinearities and uncertainties, making control methodologies much more challenging. Among them, the nonlinear features of Governor Dead-Band (GDB) and Generation Rate Constraint (GRC) strongly affect the accuracy and performance of LFC applied to a power network. This study focused on designing an applicable and efficient LFC by proposing a novel Sliding-Mode Control (SMC) scheme. The traditional SMC can successfully solve several nonlinear control problems, and in case of having a reasonable adjustment, it is completely suitable to design the LFC strategy. The modified SMC, integrated with an effective optimization technique, i.e., Particle Swarm Optimization (PSO), can dramatically improve the performance of LFC. This paper presents numerical simulation results implemented in MATLAB/Simulink to demonstrate the feasibility and effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]