Nothing Special   »   [go: up one dir, main page]

Soltanpour et al., 2014 - Google Patents

Robust fuzzy sliding mode control for tracking the robot manipulator in joint space and in presence of uncertainties

Soltanpour et al., 2014

Document ID
3205612201853893389
Author
Soltanpour M
Khooban M
Soltani M
Publication year
Publication venue
Robotica

External Links

Snippet

This paper proposes a simple fuzzy sliding mode control to achieve the best trajectory tracking for the robot manipulator. In the core of the proposed method, by applying the feedback linearization technique, the known dynamics of the robot's manipulator is removed; …
Continue reading at www.cambridge.org (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/04—Architectures, e.g. interconnection topology
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B11/00—Automatic controllers
    • G05B11/01—Automatic controllers electric
    • G05B11/32—Automatic controllers electric with inputs from more than one sensing element; with outputs to more than one correcting element

Similar Documents

Publication Publication Date Title
Soltanpour et al. Robust fuzzy sliding mode control for tracking the robot manipulator in joint space and in presence of uncertainties
Soltanpour et al. A particle swarm optimization approach for fuzzy sliding mode control for tracking the robot manipulator
Wai et al. Robust neural-fuzzy-network control for robot manipulator including actuator dynamics
Asl et al. Adaptive neural network control of cable-driven parallel robots with input saturation
Hu et al. A reinforcement learning neural network for robotic manipulator control
Fu et al. Motion tracking control design for a class of nonholonomic mobile robot systems
Pezeshki et al. Control of overhead crane system using adaptive model-free and adaptive fuzzy sliding mode controllers
Wen et al. Unactuated force control of 5-DOF parallel robot based on fuzzy PI
Gholipour et al. Robust control of robotic manipulators in the task-space using an adaptive observer based on Chebyshev polynomials
Jalali et al. Design Parallel Linear PD Compensation by Fuzzy Sliding Compensator for Continuum Robot
Yu et al. Adaptive neural network force tracking control of flexible joint robot with an uncertain environment
Guo et al. A nearly optimal chattering reduction method of sliding mode control with an application to a two-wheeled mobile robot
Hsu et al. Recurrent fuzzy-neural approach for nonlinear control using dynamic structure learning scheme
Mai et al. Adaptive-backstepping force/motion control for mobile-manipulator robot based on fuzzy CMAC neural networks
Piltan et al. Stable fuzzy PD control with parallel sliding mode compensation with application to rigid manipulator
Taherkhorsandi et al. Optimal sliding and decoupled sliding mode tracking control by multi-objective particle swarm optimization and genetic algorithms
Alavandar et al. New hybrid adaptive neuro-fuzzy algorithms for manipulator control with uncertainties–Comparative study
Fateh et al. A precise robust fuzzy control of robots using voltage control strategy
Wu et al. A study on PID intelligent optimization based on radial basis function neural networks
Mehdi Fateh et al. Discrete optimal control for robot manipulators
Hsu Adaptive PI Hermite neural control for MIMO uncertain nonlinear systems
Liu et al. Adaptive neural network position/force hybrid control for constrained reconfigurable manipulators
Mohammed et al. Stabilization of Ball-On-Sphere System with Super Twisting (ST) Sliding Mode Control (SMC) as a Method of Chattering Reduction
Montoya-Cháirez et al. An Input-Output Feedback Linearization Approach to the Motion Control of Flexible Joint Manipulators
Didam et al. Nonlinear control of a single-link flexible joint manipulator using differential flatness