Abstract
In this paper, an observer-based adaptive fuzzy robust controller is proposed for trajectory tracking control of a bionic mechanical leg (BML) with unmeasured system states, dynamic uncertainties and external disturbances. A high gain observer (HGO) is constructed to estimate the unavailable joint velocities using the joint position feedback signals, while an adaptive fuzzy logic system (AFLS) is employed to address the lumped uncertainties. The nonlinear robust controller is then synthesized via backstepping method to improve the position tracking performance. The stability of the closed loop system is mathematically demonstrated via the Lyapunov’s stability theory. It is proven that under the proposed controller all the closed-loop signals are bounded and the trajectory tracking errors converge to a small neighborhood of the origin with appropriate design parameters. The effectiveness of the proposed control scheme is illustrated by simulation studies.
Highlights
In recent years, with the application of robots spreading to industrial fields, and to many complex and special areas, such as the life service field [1,2], rehabilitation and medical treatment industry [3,4], disaster rescue [5,6], ocean engineering [7,8], and space operation [9,10], bionic robots have attracted substantial attention
The hydrodynamic external force and tidal current [19] will act on the body of the bionic mechanical leg (BML) system when it works in water, which can be seen as unknown external disturbances
These influences are not considered, and we only focus on the influence of different work conditions on the system parameters and the hydrodynamic force and tidal current force impact on the body
Summary
With the application of robots spreading to industrial fields, and to many complex and special areas, such as the life service field [1,2], rehabilitation and medical treatment industry [3,4], disaster rescue [5,6], ocean engineering [7,8], and space operation [9,10], bionic robots have attracted substantial attention. It is significant to design a high-performance trajectory tracking controller for the BML system in the presence of unmeasured system states, dynamic uncertainties and external disturbances. Motivated by the above analysis, a high gain observer-based adaptive fuzzy robust controller (AFRC-HGO) is proposed for the trajectory tracking control of a 3-DOF BML system with the existence of unmeasured system states, dynamic uncertainties and unknown external disturbances. (1) A novel AFRC-HGO controller is developed for high performance trajectory tracking control of a 3-DOF BML system This proposed controller integrates the fast convergence property and celebrated separation principle of the HGO and the universal approximation feature of the FLSs with nonlinear robust control action. Three other control methods (proportional-integral-derivative control (PID), sliding mode control (SMC) and nonlinear extended state observer-based robust control (RC-NESO)) are compared with the proposed AFRC-HGO for trajectory tracking performance evaluations.
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