Robust-optimal control of rotary inverted pendulum control through fuzzy descriptor-based techniques.

Expanding upon the well-established Takagi-Sugeno (T-S) fuzzy model, the T-S fuzzy descriptor model emerges as a robust and flexible framework. This article introduces the development of optimal and robust-optimal controllers grounded in the principles of stability control and fuzzy descriptor systems. By transforming complicated inequalities into linear matrix inequalities (LMI), we establish the essential conditions for controller construction, as delineated in theorems. To substantiate the utility of these controllers, we employ the rotary inverted pendulum as a testbed. Through diverse simulation scenarios, these controllers, rooted in fuzzy descriptor systems, demonstrate their practicality and effectiveness in ensuring the stable control of inverted pendulum systems, even in the presence of uncertainties within the model. This study highlights the adaptability and robustness of fuzzy descriptor-based controllers, paving the way for advanced control strategies in complex and uncertain environments.

Adaptive fuzzy sliding mode control of an actuator powered by two opposing pneumatic artificial muscles.

Pneumatic artificial muscle (PAM) is a potential actuator in human-robot interaction systems, especially rehabilitation systems. However, PAM is a nonlinear actuator with uncertainty and a considerable delay in characteristics, making control challenging. This study presents a discrete-time sliding mode control approach combined with the adaptive fuzzy algorithm (AFSMC) to deal with the unknown disturbance of the PAM-based actuator. The developed fuzzy logic system has parameter vectors of the component rules that are automatically updated by an adaptive law. Consequently, the developed fuzzy logic system can reasonably approximate the system disturbance. When operating the PAM-based system in multi-scenario studies, experimental results confirm the efficiency of the proposed strategy.

Modified Computed Torque Control of a Robotic Orthosis for Gait Rehabilitation.

Rehabilitation robots may help the patient improve their recovery by supporting them to perform repetitive, systematic training sessions. Safety and comfortable feeling of the patients who training with robots is an important issue in not only the steady state but also the transient process. In this research, the trajectory tracking control problems of a two-degrees of freedom (2-DOF) robotic orthosis is discussed. The robotic orthosis is powered by pneumatic artificial muscles (PAMs) in an antagonistic configuration. based on a mathematical model, a modified computed torque control scheme is employed to enhance the tracking performance. The effectiveness of the proposed control strategy is verified by the experiments with the participation of different subjects.