Adaptive fuzzy controller with self-tuning fuzzy sliding-mode compensation for position control of an electro-hydraulic displacement-controlled system

2014 ◽  
Vol 26 (2) ◽  
pp. 815-830 ◽  
Author(s):  
Mao-Hsiung Chiang ◽  
Lian-Wang Lee ◽  
Hsien-Hsush Liu
Author(s):  
Md Meftahul Ferdaus ◽  
Sreenatha G. Anavatti ◽  
Matthew A. Garratt ◽  
Mahardhika Pratama

Abstract Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous MAVs. Some desiring features of the FW MAV are quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability contrasted with similar-sized fixed and rotary wing MAVs. Inspired by the FW MAV’s advanced features, a four-wing Nature-inspired (NI) FW MAV is modelled and controlled in this work. The Fuzzy C-Means (FCM) clustering algorithm is utilized to construct the data-driven NIFW MAV model. Being model free, it does not depend on the system dynamics and can incorporate various uncertainties like sensor error, wind gust etc. Furthermore, a Takagi-Sugeno (T-S) fuzzy structure based adaptive fuzzy controller is proposed. The proposed adaptive controller can tune its antecedent and consequent parameters using FCM clustering technique. This controller is employed to control the altitude of the NIFW MAV, and compared with a standalone Proportional Integral Derivative (PID) controller, and a Sliding Mode Control (SMC) theory based advanced controller. Parameter adaptation of the proposed controller helps to outperform it static PID counterpart. Performance of our controller is also comparable with its advanced and complex counterpart namely SMC-Fuzzy controller.


Author(s):  
Chung-Chun Kung ◽  
Kuo-Ho Su

A novel adaptive fuzzy sliding-mode control (AFSMC) system for high-precision position control of a perturbed electrical servo drive is developed in this paper. The proposed AFSMC system is designed via the approximation ability of a fuzzy system to mimic the good behaviour of a total sliding-mode control (TSMC) system, which is designed without the reaching phase of a conventional sliding-mode control (SMC). In the developed system, a priori knowledge of the system information is not required. Moreover, the gradually increasing estimate upper bound, which may induce the control effort into saturation and excite unstable system dynamics in some conditions, would not exist. In the proposed controller, the adaptive tuning algorithms are developed in the sense of the Lyapunov stability theorem, so that system-tracking stability can be guaranteed. Finally, the effectiveness of the proposed control scheme is verified via the experimental results of a field-oriented control permanent magnet (PM) synchronous motor.


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