Abstract
In this study, an omnidirectional inverted pendulum (ODIP) is controlled based on a dual Takagi–Sugeno (TS) fuzzy control scheme. The ODIP is a handmade system. It contains two subsystems. The lower mechanism system includes a brushless rim motor, a system platform, batteries, and an encoder. The upper mechanism system is mainly composed of a circuit system, a motor fixed platform, a motor, and a flywheel. The proposed controller combines two fuzzy control approaches for ODIP system control with disturbances and uncertainties. The core of the ODIP operating system is an embedded controller, which executes real-world control processes. Moreover, to address the coupling problem, the shafts of the two motors are oriented in orthogonal directions. Then, the two fuzzy controllers can be designed independently without coupling. In the proposed controller, the Takagi–Sugeno fuzzy model is adopted for fuzzy modeling of the ODIP. The conception of parallel distributed compensation (PDC) is utilized to develop fuzzy control from TS fuzzy models. The format of linear matrix inequalities (LMIs) can formulate sufficient conditions. The main contributions of this study are (1) the implementation of an ODIP and (2) the application of the proposed dual Takagi–Sugeno (TS) fuzzy control scheme for real-time control of the ODIP. Finally, the efficiency of the proposed control scheme is illustrated by the experimental results presented in this study.
Highlights
Modern control systems are characterized by actions that require high speed and precision
Point P is the center of mass of the omnidirectional inverted pendulum (ODIP) body, which is considered an inverted pendulum system (IPS)
HARDWARE ARCHITECTURE This section introduces the ODIP hardware design based on an open-source embedded controller
Summary
Modern control systems are characterized by actions that require high speed and precision. A nonlinear system can be transformed into a TS fuzzy model, and a parallel distributed compensation (PDC) fuzzy controller design is accomplished using linear matrix inequality (LMI) approaches [18]. A nonlinear system can be transformed into a TS fuzzy model, and the PDC fuzzy controller design is accomplished using linear matrix inequality approaches They can be solved efficiently by convex programming techniques for LMIs. Recently, the MATLAB LMI Control Toolbox has been used to refine the asymptotically stable feedback gain value. Because of the physical structure, controller design is even more difficult To overcome this hard control problem, according to the two DC motors mounting in orthogonal directions [13], [25], [26], a dual TS model-based approach for an ODIP control system is suggested. From the experimental results, the effectiveness of the proposed intelligent controller is verified by ODIP real-world implementation
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