The buck converter is frequently introduced in the industry to maintain the stability of the voltage output when having the interference suddenly. In order to promote the robustness of the buck converter, a novel hybrid H₂ model following control (HHMFC) is developed based on digital redesign sliding mode control in this article. First, we design H₂ model following SMC in the continue-time domain. Then, by using the digital redesign approach, the continuous SMC is redesigned to a corresponding discrete-time SMC and the proposed HHMFC is achieved. Finally, we apply the developed HHMFC to realize a robust buck converter. With both the simulation and experiment results, we can conclude that the proposed HHMFC can easily and successfully apply to the practical realization for the buck converter with better robustness performance.

The design of adaptive chattering‐free sliding mode controller (SMC) for chaotic systems with unknown input nonlinearities is studied in this paper. A smooth hyperbolic tangent function is utilized to replace the discontinuous sign function; therefore, the proposed adaptive SMC ensures that not only the chaos phenomenon can be suppressed effectively but also the chattering often appearing in the traditional discontinuous SMC with sign function is eliminated, even when the unknown input nonlinearity is present. A sufficient condition for stability of closed‐loop system is acquired by Lyapunov theory. The numerical simulation results are illustrated to verify the proposed adaptive sliding mode control method.

This study explores innovative designs for the cap of a marker pen, aiming to address the issues of cap loss and ink evaporation during marker pen usage. This study applies intrinsic safety, universal design and TRIZ as research methods. TRIZ has great potential to address most of the Sustainable Development Goals (SDGs) relevant to conflict-oriented problem solving for innovations. The principles of simplification, foolproof design, clarity of states, and tolerance from intrinsic safety were applied to prevent cap loss and minimize the risks associated with ink evaporation. The TRIZ methodology’s contradiction matrix was utilized to identify relevant inventive principles by improving parameters and avoiding worsening parameters, providing a reference basis for product structure design. Lastly, the principles of equitable use, simplicity, intuitiveness, and effortless design from universal design were employed to enhance the marker pen’s usability for the general public. This study creates a SERVQUAL questionnaire to compare the prototype of the designed pen cap with commercially available pen caps. It utilizes the two-dimensional quality model (Kano model) and Importance–Performance Analysis (IPA) for practical design analysis. Finally, the prototype structure is visualized using graphic software. The innovative design features of this study include the following. (1) Concealable pen tip: the sliding seal hides the pen tip inside the pen body when the pen core is slid upwards, preventing cap loss and ink drying. (2) Quick retractable function: using a pressing mechanism, the pen tip can be quickly retracted with a one-handed press and slide motion. (3) Replaceable pen core: the pen core can be replaced by disassembling the pen body, removing the old pen core, and inserting a new one, thereby extending the pen’s lifespan. (4) Satisfaction evaluation of the innovative pen cap design: through questionnaire surveys and cross-analysis using the IPA and the Kano model, this study assesses the product’s manufacturing and mass production value to reduce actual product development costs and time.

In this paper, a novel image encryption algorithm based on chaotic synchronization is proposed. First, a digital-redesign sliding mode controller (SMC) is developed to guarantee the chaos synchronization. The digital redesign method makes it possible to transform a proposed continuous-time SMC to discrete-time SMC whilst maintaining the performance of the robust synchronization. Then, the secret keys are embedded in the state equations of the master chaotic system, such that the secret keys do not appear in the public channel, and utilize the chaotic synchronization to achieve secure communication for transmitting the secret keys from transmitter to receiver. Second, an image encryption algorithm integrating the S-box with chaotic synchronization is established, where the S-box is created by the secret key transmitted from the transmitter. Finally, a detailed analysis of the image encryption algorithm based on chaos synchronization is included to verify the feasibility and effectiveness of this proposed approach.

In recent years, the application of artificial intelligence (AI) in industry has matured, requiring deeper learning and integration of existing technologies. This study started with technical education to improve the professional quality of human resources. The double-triangular fuzzy number and gray area testing methods in the fuzzy Delphi method (FDM) were used to evaluate expert consensus, plan technical capability indicators, and ensure the integrity and appropriateness of teaching materials. Based on these indicators, special subject teaching course units were designed and integrated into existing courses for experimental teaching and evaluation. The teaching module arrangement in this research used a virtual instrument control system with LabVIEW v2021 as the GUI and the myRIO controller. The proposed system integrates an artificial neural network (ANN) AI model built with Python v3.7 for data analysis and prediction, forming an embedded teaching module for a deep learning-oriented intelligent robotic environmental monitoring system. This study evaluated students’ acceptance of deep learning robotics teaching modules and their impact on improving their technical skills. The psychomotor scale established by the scholars was adopted and revised, including this study’s technical ability indicators. The test-retest reliability of the psychomotor scale was high. The results revealed that the post-test scores of the psychomotor scale were significantly better than those of the pre-test, indicating that students’ overall technical abilities improved. Students’ affective attitudes toward the four dimensions of teaching material and equipment, cognitive development, skills performance, and self-exploration were positive. Feedback revealed that students who participated in the teaching experiment responded positively on all levels of the affective scale, indicating increased motivation and willingness to continue learning. This study successfully constructed a teaching module and evaluation model for deep learning robotic environmental sensing and control. The teaching module and evaluation model established through this research contribute to the cultivation and effectiveness evaluation of relevant technical talents.