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Go to Editorial ManagerOverhead crane systems are found in many industrial environments; however, controlling their motion in the presence of nonlinear and underactuated dynamics considers as a big challenge. To address this, a nonlinear control method proposed to enable the trolley to track the desired trajectory and quickly eliminate swing. First, feedback linearization is applied to the crane dynamics. Next, an energy-based compensation is implemented to ensure the boundedness of the system trajectories. Then, Particle Swarm Optimization (PSO) is utilized to optimally tune the controller parameters. The optimization relies on a multi-objective cost function formulated to simultaneously minimize steady-state error and overshoot, while improving robustness against model uncertainties and external disturbances. Finally, the robustness and validity of the proposed control method are demonstrated through the simulation of an underactuated crane system in several cases, including reference tracking, robustness against system uncertainty and external disturbances. Simulation results illustrated that the presented control method has minimum rise time, settling time with respect other control methods with zero steady state error.
This paper introduces a new class of adaptive WCCI-based non-inverting step-down/step-up converter that integrates an active Ripple Suppression Engine (RSE) and a dynamic mode-transition controller to simultaneously enhance efficiency and minimize ripple across buck, boost, and buck–boost operating modes. Unlike conventional WCCI ZVT based step-down converters which operate in a single region and rely primarily on passive filtering, the proposed topology employs active current injection and ripple-sensing compensation to reshape the inductor-current waveform and attenuate switching-related conduction losses. With the aid of a dual-threshold window comparator and FSM-based logic, the converter achieves highly stable mode transitions free from ringing, overshoot, or mode oscillation. Simulation results validate the superior performance of the proposed architecture, demonstrating more than a 70% reduction in inductor-current ripple and nearly an 80% decrease in output-voltage ripple compared with the existing work. The converter also exhibits substantially improved transient behavior, achieving faster settling times and significantly lower voltage undershoot during load-step events, all while utilizing smaller passive components. Furthermore, the proposed scheme maintains high efficiency throughout the full 2.5V–8V input range, offering a robust and adaptable alternative to traditional WCCI-based implementations. These findings confirm the suitability of the proposed converter for compact, high-performance power-management applications.
The rapid development of the Internet of Things (IoT) has drawn significant attention from both industry and academia, driven by the integration of cloud computing, big data analytics, machine learning, and cyber-physical systems in manufacturing. Programmable Logic Controllers (PLCs), long central to industrial control systems, have evolved from basic feedback control devices to advanced components capable of networking and data exchange through IoT technologies. The Industrial Internet of Things (IIoT) refers to intelligent automation systems that continuously monitor critical parameters and respond to changes in real time. The integration of IoT with PLCs is transforming industrial automation by enabling remote real-time monitoring, data-driven decision-making, and predictive maintenance through advanced analytics. IIoT technologies enhance manufacturing performance and offer strategic value across sectors. Understanding their impact involves examining current research, including technology assessments and application-based case studies. This study provides an overview of PLC systems evolving into IIoT frameworks, with a focus on implementing proportional-integral (PI) control using the Siemens S7-300. Designed for precise and consistent temperature regulation, this approach enhances process efficiency and product quality, making it highly suitable for industrial and manufacturing environments.