In recent years, human being assistant transportation systems have received much attention. Based on a microprocessor, a bicycle robot (BR) is designed and implemented in this work. In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with an adaptive output recurrent Takagi-Sugeno-Kang type cerebellar model articulation controller (AORTSKCMAC) and a robust controller for BRs is implementation. The bicycle robot can keep balance with disturbance and go forward. The proposed RIBTC is proposed to control the lean angle of the BR. The BRs can stably stand even with external disturbance. The development of proposed controller is combined with the backstepping technique, adaptive output recurrent TSKCMAC and robust control method. The adaptive output recurrent TSKCMAC is used to mimic the ideal backstepping controller (IBC), because the accurate mathematical model of the system is hard to obtain. In General, the optimal values of system parameters can be calculated based on system dynamics when the system model is always known. However, the exact system dynamics is not always known. The parameters of the adaptive output recurrent TSKCMAC are tune online in this study. The robust controller is designed to attenuate the effect of the residual approximation errors. Moreover, the Lyapunov function is using to prove the stability and convergence of the controller. The main contributions of this work include: (1) the successful design and implementation of a BR hardware, and (2) the successful realization of the proposed RIBTC control scheme to control the BR. Finally, experiment results demonstrate the effectiveness of the proposed control scheme for bicycle robot systems with unknown dynamic functions.

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.

In this study, a novelty dual Takagi-Sugeno (TS) fuzzy control scheme (DTSFCS) is proposed for real world system control. We propose using a ball robot (BR) system control problem, where the BR has the ability to move omnidirectionally. The proposed control scheme combines two fuzzy control approaches for a BR. In this fuzzy control approach, the TS fuzzy model was adopted for the fuzzy modeling of the BR. The concept of parallel distributed compensation (PDC) was utilized to develop a fuzzy control scheme from the TS fuzzy models. The linear matrix inequalities (LMIs) can formulate sufficient conditions. Moreover, in this study, the motors of the BR were mounted on two orthogonal axes. Then, the dual TS fuzzy controller was designed to independently operate without coupling. Finally, the efficiency of the proposed control scheme is illustrated by the experimental and simulation results that are presented in this study.