Robust recurrent-neural-network sliding-mode control for the X-Y table of a CNC machine

Lin, Faa-Jeng; Shieh, Po-Huang; Shen, Po-Hung

doi:10.1049/ip-cta:20045032

Cited by 27 publications

(19 citation statements)

References 21 publications

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“…In [9], Lin et al presented "a Robust Recurrent-Neural-Network (RRNN) sliding-mode control for a biaxial motion mechanism to allow reference contour tracking. The biaxial motion mechanism is an XY table of a computer numerical control machine that is driven by two field-oriented control permanent-magnet synchronous motors".…”

Section: Related Existing Workmentioning

confidence: 99%

Rapidly-implementable optimizely-sizable fuzzy controller architectures: A performance analysis for semiconductor packaging two axes table

Karam¹,

Ghintab²,

Hasan³

2019

PEN

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The tendency of miniaturizing semiconductor products towards nano-size transistor in integrated chips has motivated this work on the semiconductor package. Consequently, Four Fuzzy PID controller architectures based on type 2 FLC are developed; the Interval Type-2 Fuzzy Logic PID, IT2FLC PID MOALO-based, IT2FLC PI-PD, and IT2FLC PI-PD MOALO controllers. These architectures are improved to overcome the inherent nonlinearity in X-Y table models and capacitate the uncertainties of the parameters and the disturbances. Both controllers are designed to improve the desired position specification at minimum settling time (Ts), rise time (Tr), overshoot through minimization of oscillation and friction rejection during tracking the desired position trajectory. The ant lion optimization (ALO) algorithm has been efficiently solved optimization problems with minimum parameters and execution time. Hence, Multi-Objective Ant Lion Optimizer (MOALO) has been implemented to size the gains of the proposed controllers to get the desired position trajectory according to the required specification. A comparison with a related existing work shows minimal numerical values of improved transient specification response of Tr, Mp% and Ts for the MOALO-Based developed IT2 FLC PID and IT2 FLC PI-PD architectures. Observation of a higher Maximum Percentage of Enhancement settling time is noticed in both axes within the IT2FLC PI-PD architecture. Accordingly, transient performances of the four architectures have been significantly improved. The improvement is noticeable within the response of IT2FLC PI-PD architecture. The Maximum Percentage of Enhancement in the X-axis and Y-axis has been improved more than eight-fold and six-fold respectively using IT2FLC PI-PD architecture.

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Section: Related Existing Workmentioning

confidence: 99%

Rapidly-implementable optimizely-sizable fuzzy controller architectures: A performance analysis for semiconductor packaging two axes table

Karam¹,

Ghintab²,

Hasan³

2019

PEN

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“…Planning. The circular, window, star, and helical circular motion trajectories are typically used [18] as the performance evaluation of the motion controller for XYZ table.…”

Section: Motion Trajectorymentioning

confidence: 99%

ModelSim/Simulink Cosimulation and FPGA Realization of a Multiaxis Motion Controller

Kung

Lin

Chen

et al. 2015

Mathematical Problems in Engineering

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This paper is to implement a multiaxis servo controller and a motion trajectory planning within one chip. At first, SoPC (system on a programmable chip) technology which is composed of an Altera FPGA (field programmable gate arrays) chip and an embedded soft-core Nios II processor is taken as the development of a multiaxis motion control IC. The multiaxis motion control IC has two modules. The first module is Nios II processor which realizes the motion trajectory planning by software. It includes the step, circular, window, star, and helical motion trajectory. The second module presents a function of the multiaxis position/speed/current controller IP (intellectual property) by hardware. And VHDL (VHSIC Hardware Description Language) is applied to describe the multiaxis servo controller behavior. Before the FPGA realization, a cosimulation work by ModelSim/Simulink is applied to test the VHDL code. Then, this IP combined by Nios II processor will be downloaded to FPGA. Therefore, a fully digital multiaxis motion controller can be realized by a single FPGA chip. Finally, to verify the effectiveness and correctness of the proposed multiaxis motion control IP, a three-axis motion platform (XYZ table) is constructed and some experimental results are presented.

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“…Sliding-mode control techniques are robust methods for controlling non-linear systems and X-Y stage applications [7][8][9][10][11]. They use the desired sliding surface in the state space and generate a switched control command according to the plant input-output behaviour and the boundary of the modelling uncertainties and unknown disturbances.…”

Section: Introductionmentioning

confidence: 99%

Indirect fuzzy contour tracking for X – Y PMSM actuated motion system applications

Mao

Suprapto

2017

IET Electric Power Applications

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In this study, the authors present a control method for the permanent magnet synchronous motor (PMSM) driven X-Y motion system for application in industrial and manufacturing apparatus. Backlash and friction effects in ball-screw actuated systems are common obstacles to achieve high-accuracy control. The authors investigate the indirect fuzzy controller to demonstrate the feasibility of reference trajectory tracking and derive an adaptive law in the error state space to deal with parameter uncertainties and external disturbances. The authors adjust the fuzzy parameters online, based on the Lyapunov stability theorem, such that the asymptotic stability of the whole system and error convergence can be guaranteed. In the authors' experiments, this indirect fuzzy control approach compensated for the non-linear friction and disturbance variation of the biaxial linear stage following the application of four contour shapes, i.e. square, triangular, star, and circular reference contours. Both the authors' simulation and experimental results demonstrate substantial improvement in contour tracking performance in terms of average tracking error and tracking error standard deviation, as well as robustness against platform uncertainties.

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Robust recurrent-neural-network sliding-mode control for the X-Y table of a CNC machine

Cited by 27 publications

References 21 publications

Rapidly-implementable optimizely-sizable fuzzy controller architectures: A performance analysis for semiconductor packaging two axes table

Rapidly-implementable optimizely-sizable fuzzy controller architectures: A performance analysis for semiconductor packaging two axes table

ModelSim/Simulink Cosimulation and FPGA Realization of a Multiaxis Motion Controller

Indirect fuzzy contour tracking for X – Y PMSM actuated motion system applications

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