scholarly journals Adaptive Fuzzy Integral Terminal Sliding Mode Control of a Nonholonomic Wheeled Mobile Robot

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Shuying Peng ◽  
Wuxi Shi
Keyword(s):  
Mobile Robot ◽  
Sliding Mode ◽  
Kinematic Model ◽  
Small Neighborhood ◽  
Wheeled Mobile Robot ◽  
Fuzzy Integral ◽  
Control Input ◽  
Parameter Uncertainties ◽  
Terminal Sliding Mode ◽  
Adaptive Fuzzy

In this paper, the trajectory tracking problem is investigated for a nonholonomic wheeled mobile robot with parameter uncertainties and external disturbances. In this strategy, combining the kinematic model with the dynamic model, the actuator voltage is employed as the control input, and the uncertainties are approximated by a fuzzy logic system. An auxiliary velocity controller is integrated with an adaptive fuzzy integral terminal sliding mode controller, and a robust controller is employed to compensate for the lumped errors. It is proved that all the signals in the closed system are bounded and the auxiliary velocity tracking errors can converge to a small neighborhood of the origin in finite time. As a result, the tracking position errors converge asymptotically to zeros with faster response than other existing controllers. Simulation results demonstrate the effectiveness of the proposed strategy.

scholarly journals Research on predictive sliding mode control strategy for horizontal vibration of ultra-high-speed elevator car system based on adaptive fuzzy

2021 ◽  
Vol 54 (3-4) ◽  
pp. 360-373
Author(s):  
Hong Wang ◽  
Mingqin Zhang ◽  
Ruijun Zhang ◽  
Lixin Liu
Keyword(s):  
Sliding Mode Control ◽  
High Speed ◽  
Sliding Mode ◽  
Mode Switching ◽  
Parameter Uncertainties ◽  
Horizontal Vibration ◽  
Adaptive Fuzzy ◽  
Mode Control ◽  
System A ◽  
Ultra High Speed

In order to effectively suppress horizontal vibration of the ultra-high-speed elevator car system. Firstly, considering the nonlinearity of guide shoe, parameter uncertainties, and uncertain external disturbances of the elevator car system, a more practical active control model for horizontal vibration of the 4-DOF ultra-high-speed elevator car system is constructed and the rationality of the established model is verified by real elevator experiment. Secondly, a predictive sliding mode controller based on adaptive fuzzy (PSMC-AF) is proposed to reduce the horizontal vibration of the car system, the predictive sliding mode control law is achieved by optimizing the predictive sliding mode performance index. Simultaneously, in order to decrease the influence of uncertainty of the car system, a fuzzy logic system (FLS) is designed to approximate the compound uncertain disturbance term (CUDT) on-line. Furthermore, the continuous smooth hyperbolic tangent function (HTF) is introduced into the sliding mode switching term to compensate the fuzzy approximation error. The adaptive laws are designed to estimate the error gain and slope parameter, so as to increase the robustness of the system. Finally, numerical simulations are conducted on some representative guide rail excitations and the results are compared to the existing solution and passive system. The analysis has confirmed the effectiveness and robustness of the proposed control method.

Obstacle avoidance control of a human-in-the-loop mobile robot system using harmonic potential fields

Robotica ◽  
2017 ◽  
Vol 36 (4) ◽  
pp. 463-483 ◽  
Author(s):  
C. Ton ◽  
Z. Kan ◽  
S. S. Mehta
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Sliding Mode ◽  
Harmonic Potential ◽  
Control Allocation ◽  
Control Input ◽  
Continuous Control ◽  
Control Effort ◽  
Human In The Loop ◽  
Allocation Function

SUMMARYThis paper considers applications where a human agent is navigating a semi-autonomous mobile robot in an environment with obstacles. The human input to the robot can be based on a desired navigation objective, which may not be known to the robot. Additionally, the semi-autonomous robot can be programmed to ensure obstacle avoidance as it navigates the environment. A shared control architecture can be used to appropriately fuse the human and the autonomy inputs to obtain a net control input that drives the robot. In this paper, an adaptive, near-continuous control allocation function is included in the shared controller, which continuously varies the control effort exerted by the human and the autonomy based on the position of the robot relative to obstacles. The developed control allocation function facilitates the human to freely navigate the robot when away from obstacles, and it causes the autonomy control input to progressively dominate as the robot approaches obstacles. A harmonic potential field-based non-linear sliding mode controller is developed to obtain the autonomy control input for obstacle avoidance. In addition, a robust feed-forward term is included in the autonomy control input to maintain stability in the presence of adverse human inputs, which can be critical in applications such as to prevent collision or roll-over of smart wheelchairs due to erroneous human inputs. Lyapunov-based stability analysis is presented to guarantee finite-time stability of the developed shared controller, i.e., the autonomy guarantees obstacle avoidance as the human navigates the robot. Experimental results are provided to validate the performance of the developed shared controller.

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