Decentralized RBFNN Type-2 Fuzzy Sliding Mode Controller for Robot Manipulator Driven by Artificial Muscles (original) (raw)
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Fuzzy Logic Controller for a Pneumatic Artificial Muscle Robot based on Sliding Mode Control
2009
Fuzzy Logic Control (FLC) has been successfully established in control systems engineering in the recent years, in other hand, Sliding Mode Control (SMC) is an active area in control research. The combination of this tow fields called Fuzzy Sliding Mode Control (FSMC) techniques to exploit the superior sides of these two controllers have drawn the attention of the scientific community. In this work, we proposed fuzzy logic controller based on the sliding mode theory to control the robot arm actuated by the pneumatics artificial muscles. Using bang-bang motion generation law, the objective of the control is the position and the velocity tracking by the robot. Simulations results demonstrate the feasibility and the advantages of our proposed research work.
International Journal of Advanced Robotic Systems, 2018
A new enhanced adaptive fuzzy sliding mode control approach is proposed in this article with its good availability for application in control of a highly uncertain nonlinear two-link pneumatic artificial muscle manipulator. Stability demonstration of the robust convergence of the closed-loop pneumatic artificial muscle manipulator system based on a novel enhanced adaptive fuzzy sliding mode control is experimentally proved using Lyapunov stability theorem. Obtained result confirms that the new enhanced adaptive fuzzy sliding mode control method, applied to the two-link uncertain nonlinear pneumatic artificial muscle manipulator system, is fully investigated with better robustness and precision than the standard sliding mode control and fuzzy sliding mode control techniques.
Active force with fuzzy logic control of a two-link arm driven by pneumatic artificial muscles
Journal of Bionic Engineering, 2011
In this paper, the practicality and feasibility of Active Force Control (AFC) integrated with Fuzzy Logic(AFCAFL) applied to a two link planar arm actuated by a pair of Pneumatic Artificial Muscle (PAM) is investigated. The study emphasizes on the application and control of PAM actuators which may be considered as the new generation of actuators comprising fluidic muscle that has high-tension force, high power to weight ratio and high strength in spite of its drawbacks in the form of high nonlinearity behaviour, high hysteresis and time varying parameters. Fuzzy Logic (FL) is used as a technique to estimate the best value of the inertia matrix of robot arm essential for the AFC mechanism that is complemented with a conventional Proportional-Integral-Derivative (PID) control at the outermost loop. A simulation study was first performed followed by an experimental investigation for validation. The experimental study was based on the independent joint tracking control and coordinated motion control of the arm in Cartesian or task space. In the former, the PAM actuated arm is commanded to track the prescribed trajectories due to harmonic excitations at the joints for a given frequency, whereas for the latter, two sets of trajectories with different loadings were considered. A practical rig utilizing a Hardware-In-The-Loop Simulation (HILS) configuration was developed and a number of experiments were carried out. The results of the experiment and the simulation works were in good agreement, which verified the effectiveness and robustness of the proposed AFCAFL scheme actuated by PAM.
International Journal of Computational Intelligence Systems, 2021
This paper introduces an enhanced fuzzy sliding mode control (EFSMC) algorithm used for controlling the uncertain pneumatic artificial muscle (PAM) robot arm containing external disturbances. The nonlinear features of investigated PAM robot arm system are approximated using fuzzy logic. Moreover, the coefficients of fuzzy model are optimum selected by evolutionary differential eveloution (DE) technique. The new EFSMC algorithm is designed based on the traditional sliding mode controller in which the adaptive fuzzy rule is developed based on the Lyapunov stability theory and is fuzzified with Mandani fuzzy scheme. As a consequent, the closed-loop stability of nonlinear uncertain PAM robot arm system is guaranteed to follow the global asymptotic stability. Experimental results are shown. It is evident that the proposed adaptive fuzzy rule suitable with the EFSMC controller which ensures an outperforming method in comparison with other advanced control approaches.
Interval Fuzzy Type-2 Sliding Mode Control Design of Six-DOF Robotic Manipulator
Mathematics
The remarkable features of hybrid SMC assisted with fuzzy systems supplying parameters of the controller have led to significant success of these control approaches, especially in the control of multi-input and multi-output nonlinear systems. The development of type-1 fuzzy systems to type-2 fuzzy systems has improved the performance of fuzzy systems due to the ability to model uncertainties in the expression of expert knowledge. Accordingly, in this paper, the basic approach of designing and implementing the interval type-2 fuzzy sliding mode control was proposed. According to the introduced systematic design procedure, complete optimal design of a type-2 fuzzy system structure was presented in providing sliding mode control parameters by minimizing tracking error and control energy. Based on the proposed method, the need for expert knowledge as the main challenge in designing fuzzy systems was eliminated. In addition, the possibility to limit the control outputs to deal with actua...
Online RBF and fuzzy based sliding mode control of robot manipulator
2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), 2012
The aim of this work is the combination of radial basis function networks (RBF) and fuzzy techniques to enhance the sliding mode controllers. In fact, three RBFs networks were used to estimate the model parameters and to respond to model variation and disturbances, a sequential training algorithm based on Kalman filter was implemented, and to eliminate the chattering effect, a fuzzy controller was designed. The hybrid sliding mode controller had shown a strong ability to get over noise and uncertainties. The former controller was used to control a two degree of freedom robot manipulator.
Robust Interval Type-2 Fuzzy Sliding Mode Control Design for Robot Manipulators
Robotics
This paper develops a new robust tracking control design for n-link robot manipulators with dynamic uncertainties, and unknown disturbances. The procedure is conducted by designing two adaptive interval type-2 fuzzy logic systems (AIT2-FLSs) to better approximate the parametric uncertainties on the system nominal. Then, in order to achieve the best tracking control performance and to enhance the system robustness against approximation errors and unknown disturbances, a new control algorithm, which uses a new synthesized AIT2 fuzzy sliding mode control (AIT2-FSMC) law, has been proposed. To deal with the chattering phenomenon without deteriorating the system robustness, the AIT2-FSMC has been designed so as to generate three adaptive control laws that provide the optimal gains value of the global control law. The adaptation laws have been designed in the sense of the Lyapunov stability theorem. Mathematical proof shows that the closed loop control system is globally asymptotically st...
Type-2 Fuzzy Logic Control of a Flexible-Joint Manipulator
Journal of Intelligent and Robotic Systems, 2008
A type-2 fuzzy logic controller (FLC) is proposed in this article for robot manipulators with joint elasticity and structured and unstructured dynamical uncertainties. The proposed controller is based on a sliding mode control strategy. To enhance its real-time performance, simplified interval fuzzy sets are used. The efficiency of the control scheme is further enhanced by using computationally inexpensive input signals independently of the noisy torque and acceleration signals, and by adopting a trade off strategy between the manipulator's position and the actuators' internal stability. The controller is validated through a set of numerical experiments and by comparing it against its type-1 counterpart. It is shown through these experiments the higher performance of the type-2 FLC in compensating for larger magnitudes of uncertainties with severe nonlinearities.