Stabilization control of rotary inverted pendulum using a novel EKF-based fuzzy adaptive sliding-mode controller: design and experimental validation

This article methodically develops an improved self-regulating fuzzy-adaptive Sliding Mode Controller (SMC) that strengthens the disturbance compensation capacity of the nonlinear rotary pendulum systems while effectively attenuating the chattering content and curbing the control energy consumption. The article contributes to augmenting the SMC with online adaptation tools to achieve the said objectives. It employs the conventional Gao’s power-rate reaching law as the baseline. The scaling gain and the power rate of the said reaching law are adaptively modulated via a pre-calibrated two-input state-error-driven fuzzy nonlinear function. Additionally, the sign function in the law is also replaced with an odd-symmetric nonlinear fuzzy function to address the hard limits imposed by the former. Finally, the membership functions of the fuzzy function are self-regulated using the Extended-Kalman-Filter to improve the compensator’s adaptability in handling the system’s rapidly changing control requirements under exogenous disturbances. The aforementioned propositions are verified by performing customized and reliable hardware-in-loop experiments on the Quanser single-link rotary pendulum platform. As compared to baseline SMC law, the proposed control procedure contributes a ∼45.2%, ∼48.5%, and ∼34.8% reduction in position-regulation errors, control energy consumption, and peak overshoots, respectively. The experimental assessment validates the proposed control system’s enhanced robustness and chattering-suppression capability.</p

Fig 5 -

AFTCS performance for AFR control of IC engine (a) at 300 r/min (b) at 600 r/min.</p

Fig 4 -

Line fit plot for throttle estimation (a) 300 r/min (b) 600 r/min.</p

Flowchart of proposed FTCS.

Flowchart of proposed FTCS.</p

Percentage error comparison for throttle estimation in proposed, LR, and GA.

Percentage error comparison for throttle estimation in proposed, LR, and GA.</p

Values of unknown constants for MAP estimation.

Values of unknown constants for MAP estimation.</p

Percentage error comparison for MAP estimation in proposed, LR, and GA.

Percentage error comparison for MAP estimation in proposed, LR, and GA.</p

Throttle angle and MAP values at 300 and 600 r/min [32].

Throttle angle and MAP values at 300 and 600 r/min [32].</p

Architecture of Air-fuel system of SI IC engine [35].

Architecture of Air-fuel system of SI IC engine [35].</p

List of symbols and their description.

List of symbols and their description.</p