Optimal robust voltage control of electrically driven robot manipulators

Fateh, Mohammad Mehdi; Khorashadizadeh, Saeed

doi:10.1007/s11071-012-0546-4

Cited by 46 publications

(25 citation statements)

References 22 publications

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“…It is worth pointing out that any monotonically-increasing odd activation function φ(·) can be used for the construction of OZND model (4). In addition, the following four basic types of activation functions have been investigated in OZND model (4) [20,21]:…”

Section: Oznd Modelmentioning

confidence: 99%

“…• 1) If the linear activation function is used, the exponential convergence with rate γ is achieved for ZND model (4).…”

Section: Lemmamentioning

confidence: 99%

“…When we want to understand the physical mechanism of phenomena in nature, exact solutions for the nonlinear equations have to be explored [3,4,5,6]. Thus, considerable attention has been focused to derive exact solutions of nonlinear equations both analytically and numerically [1,2,7,8,9].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A nonlinearly activated neural dynamics and its finite-time solution to time-varying nonlinear equation

Xiao

2016

Neurocomputing

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Section: Oznd Modelmentioning

confidence: 99%

“…• 1) If the linear activation function is used, the exponential convergence with rate γ is achieved for ZND model (4).…”

Section: Lemmamentioning

confidence: 99%

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A nonlinearly activated neural dynamics and its finite-time solution to time-varying nonlinear equation

Xiao

2016

Neurocomputing

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“…Time delay method [10] and uncertainty estimation [11] can be used to control the robot manipulator by estimating the unknown dynamics and disturbances. Uncertainty can be well estimated by a time-delay estimator [12] or an adaptive fuzzy system [13]. The time-delay method was effectively applied to compensate uncertainty in the robust impedance control of a suspension system [12], robust repetitive control of rigid robots [9] and robust control of flexible-joint robots [14].…”

Section: Introductionmentioning

confidence: 99%

Discrete-time repetitive optimal control: Robotic manipulators

Fateh

Baluchzadeh²

2016

JAIDM

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This paper proposes a discrete-time repetitive optimal control of electrically driven robotic manipulators using an uncertainty estimator. The proposed control method can be used for performing repetitive motion, which covers many industrial applications of robotic manipulators. This kind of control law is in the class of torque-based control in which the joint torques are generated by permanent magnet dc motors in the current mode. The motor current is regulated using a proportional-integral controller. The novelty of this paper is a modification in using the discrete-time linear quadratic control for the robot manipulator, which is a nonlinear uncertain system. For this purpose, a novel discrete linear time-variant model is introduced for the robotic system. Then, a time-delay uncertainty estimator is added to the discrete-time linear quadratic control to compensate the nonlinearity and uncertainty associated with the model. The proposed control approach is verified by stability analysis. Simulation results show the superiority of the proposed discrete-time repetitive optimal control over the discrete-time linear quadratic control.

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“…Different adaptive and robust procedures are proposed for robot control that all of them are so complicated in analysis and design [8][9][10][11] . Approaches that have been proposed for robot control are categorized in non-linear methods that are more difficult than linear methods in analysis and implementation [12][13][14] .…”

mentioning

confidence: 99%

Two-link Robot Manipulator using Fractional Order PID Controllers Optimized by Evolutionary Algorithms

Fani¹,

Shahraki²

2016

Biosci., Biotech. Res. Asia

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Fractional order (FO) controllers are highly considered with regard to higher performance and robustness of these controllers in FO systems. According to advantages of PID controllers such as suitable performance, low price and simplicity of design, they are widely used in industry. A FOPID controller is used for two-link robot control in this paper. Considering vast use of evolutionary algorithms and numerical optimization, coefficients of the FO controller are optimized using evolutionary algorithms in this paper. An individual FOPID controller is applied in order to control each link. Three evolutionary optimization algorithms including particle swarm optimization (PSO), genetic algorithm and estimation of distribution algorithm, are compared from optimal coefficients determination point of view. Experimental results indicate that FOPID controller is more applicable according to use of actual model for robot and suitable performance of the PSO algorithm. Key words: Evolutionary algorithms, fractional order controller, PID controller, two-link robotAlong with introduction of fractional order (FO) controllers and their higher performance and robustness on FO systems by Podlubny in 1994, FO systems and their control process are significantly considered 1 . Although PID controllers are introduced long time ago, they are widely used in industry because of their advantages such as low price, design simplicity and suitable performance 2, 3 . While three parameters of design including proportional (K p ), integral (K i ), and derivative (K d ) are available in PID controllers, two more parameters exist in FOPID controllers for adjustment. These parameters are integral fractional order and derivative fractional order 4 . In comparison with PID controllers, FOPID controllers have more flexible design that result in more precise adjustment of closed-loop system 5 . FOPID controllers are defined by FO differential equations. It is possible to tune frequency response of the control system by expanding integral and derivative terms of the PID controller to fractional order case. This characteristic result in a more robust design of control system, but it is not easily possible 6 .According to non-linearity, uncertainty, and confusion behaviors of robot arms, they are highly recommended for experimenting designs of control systems. Despite non-linear behavior of robot arm, it is demonstrable that a linear proportional derivative controller can stabilize the system using Lyapanov 7 . But, classic PD controller itself cannot control robot to reach suitable condition. Several papers and wide researches in optimizing performance of the robot manipulator show the importance of this issue. Different adaptive and robust procedures are proposed for robot control that all of them are so complicated in analysis and design [8][9][10][11] . Approaches that have been proposed for robot control are categorized in non-

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Optimal robust voltage control of electrically driven robot manipulators

Cited by 46 publications

References 22 publications

A nonlinearly activated neural dynamics and its finite-time solution to time-varying nonlinear equation

A nonlinearly activated neural dynamics and its finite-time solution to time-varying nonlinear equation

Discrete-time repetitive optimal control: Robotic manipulators

Two-link Robot Manipulator using Fractional Order PID Controllers Optimized by Evolutionary Algorithms

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