Robust Adaptive Self-Organizing Wavelet Fuzzy CMAC Tracking Control for De-icing Robot Manipulator

Ngo, Thanh-Quyen; Phuong, TaVan

doi:10.15837/ijccc.2015.4.702

Cited by 13 publications

(7 citation statements)

References 15 publications

(8 reference statements)

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“…2 which consists of adaptive S-RWCMAC. The supervisory controller, and the adaptive robust controller with the equation (8).…”

Section: Adaptive S-rwcmac-based Supervisory Control Systemmentioning

confidence: 99%

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Adaptive Single-Input Recurrent WCMAC-Based Supervisory Control for De-icing Robot Manipulator

Ngo,

Le,

Lam

et al. 2023

Journal of Robotics and Control

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The control of any robotic system always faces many great challenges in theory and practice. Because between theory and reality, there is always a huge difference in the uncertainty components in the system. That leads to the accuracy and stability of the system not being guaranteed with the set requirements. This paper presents a novel adaptive single-input recurrent wavelet differentiable cerebellar model articulation controller (S-RWCMAC)-based supervisory control system for an m-link robot manipulator to achieve precision trajectory tracking. This adaptive S-RWCMAC-based supervisory control system consists of a main adaptive S-RWCMAC, a supervisory controller, and an adaptive robust controller. The S-RWCMAC incorporates the advantages of the wavelet decomposition property with a CMAC fast learning ability, dynamic response, and input space dimension of RWCMAC can be simplified; and it is used to control the plant. The supervisory controller is appended to the adaptive S-RWCMAC to force the system states within a predefined constraint set and the adaptive robust controller is developed to dispel the effect of the approximate error. In this scheme, if the adaptive S-RWCMAC can not maintain the system states within the constraint set. Then, the supervisory controller will work to pull the states back to the constraint set and otherwise is idle. The online tuning laws of S-RWCMAC and the robust controller parameters are derived from the gradient-descent learning method and Lyapunov function so that the stability of the system can be guaranteed. The simulation and experimental results of the novel three-link De-icing robot manipulator are provided to verify the effectiveness of the proposed control methodology. The results indicate that the proposed model has superior accuracy compared to that of the Standalone CMAC Controller. The parameters of the average squared error in the S-RWCMAC -based 3 robot joints are lower than those of the Standalone CMAC Controller by 0.023%, 0.029%, and 0.032%, respectively.

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“…2 which consists of adaptive S-RWCMAC. The supervisory controller, and the adaptive robust controller with the equation (8).…”

Section: Adaptive S-rwcmac-based Supervisory Control Systemmentioning

confidence: 99%

“…is a positive constant. By taking the time derivative of ( 13) for 𝑛 = 2 and using (3), (8). We have (14).…”

Section: B On-line Learning Algorithmmentioning

confidence: 99%

Adaptive Single-Input Recurrent WCMAC-Based Supervisory Control for De-icing Robot Manipulator

Ngo,

Le,

Lam

et al. 2023

Journal of Robotics and Control

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“…To improve the learning ability of the NNs in real-time, the Recurrent Cerebellar Model Articulation Controllers (RCMAC) have been developed and applied for uncertain, non-model, and non-linear systems [18,19]. The effectiveness of the RCMAC in controlling practical applications have achieved good responses [20,21].…”

Section: Introductionmentioning

confidence: 99%

An Innovative Approach for Water Distribution Systems

Ta¹,

Truong²,

Nhan³

2022

Intelligent Automation &Amp; Soft Computing

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Water Distribution System (WDS) is one of the important phases of the Water Treatment Plant (WTP) and plays a crucial role in plant, animal, and human life. The WDS aims not only to supply a continuous, stable water amount but also to reduce energy consumption as little as possible during operation. To keep the continuous, stable water amount, the water pressure in the pipe network of the WDS must be maintained at desired set points under the effecting of uncertainties, disturbances, and noises. For saving the energy requirement, a Variable Frequency Driver (VFD) was utilized to control the speed of the Water Boost Pump (WBP) as speed as the WDS requires and a Recurrent Cerebellar Model Articulation Control System (RCMACS) was proposed to keep the water pressure at desired reference under abnormal events. Furthermore, to adapt to the industrial environment, the RCMACS was implemented on the Allen-Bradly Programmable Logic Controller (PLC), and industrial networks were also proposed to connect and transfer data between control stations and field devices.

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“…In recent decades, the Cerebellar Model Articulation Controller (CMAC) has been developed and adopted for the complex non-linear MIMO systems due to it has superior properties to NNs [14][15][16][17]. To improve learning capability and dynamic response of the CMAC, the wavelet function and recurrent technique were incorporated into the CMAC to improve the performance of the system [18].…”

Section: Introductionmentioning

confidence: 99%

Robust Recurrent Cerebellar Model Articulation Controller for Non-Linear MIMO Systems

Dang¹,

Ta²

2019

ijacsa

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This research proposes a H  robust recurrent cerebellar model articulation control system (RRCMACS) for MIMO non-linear systems to achieve the robustness of the system during operation. In this system, the superior properties of the recurrent cerebellar model articulation controller (RCMAC) are incorporated to imitate an ideal sliding mode controller. The H  robust controller efficiently attenuates the effects of uncertainties, external disturbances, and noises to maintain the robustness of the system. The parameters of the controller were updated in the sense of the Lyapunov-like Lemma theory. Therefore, the stability and robustness of the system were guaranteed. The simulation results for the micromotion stage system are given to prove the effectiveness and applicability of the proposed control system for model-free nonlinear systems.

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Robust Adaptive Self-Organizing Wavelet Fuzzy CMAC Tracking Control for De-icing Robot Manipulator

Cited by 13 publications

References 15 publications

Adaptive Single-Input Recurrent WCMAC-Based Supervisory Control for De-icing Robot Manipulator

Adaptive Single-Input Recurrent WCMAC-Based Supervisory Control for De-icing Robot Manipulator

An Innovative Approach for Water Distribution Systems

Robust Recurrent Cerebellar Model Articulation Controller for Non-Linear MIMO Systems

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