Self-Triggered Scheme Design for Takagi-Sugeno Fuzzy Model Based on Mismatch Premise Variable With Time-Varying Delay

Over the last 20 years, numerous experts in the manufacturing companies have become interested in controlling flexible joint robots. The control design process using a networked framework has played a significant role in the industrial sector. This research addresses the self-triggered control problem for Takagi-Sugeno (T-S) fuzzy systems based on time delay is established in this research. A new self-triggered mechanism determines when the plant state is transmitted. Instead of continuously tracking predefined triggering conditions, the self-triggered system determines the next triggering instant based on the most recently triggered state information. The self-triggered mechanism relying on T-S fuzzy controller is then created using the triggered state, allowing for flexible configuration of its fuzzy rules and membership operations (MOs) that are not dependent on the controlled fuzzy system. Furthermore, it precisely demonstrates the interaction between the triggered condition and the plant state under the constraint of mismatched premise variables. To ensure system stability and performance, delay-dependent requirements are derived using a novel Lyapunov-Krasovskii functional based on fuzzy concepts to develop the fuzzy control design. The presence of the required controller is then shown under LMI-based conditions. Lastly, a simulation of a flexible robotic arm example is provided along with an evaluation of other triggered methods. Note to Practitioners—Flexible joint robots are widely used in robotics, automation, medicine, and other areas where they are unable to do certain tasks. This project aims to develop innovative solutions to significant issues in industrial robotic manipulators by enhancing flexibility, improving control techniques, alleviating stability conditions, and encouraging human-robot collaboration. This research proposes a fuzzy control technique that can handle time-delays signal and mismatch premise variables to preserve system stability in networked control systems and achieve related control goals. Among the advantages of this method that facilitate engineering applications are simpler architectures, reduced tuning factors, and enhanced control behaviors. Finally, a simulation that employs a realistic approach is shown to support the theoretical claims.