Zero-sum game-based neuro-optimal control of modular robot manipulators with uncertain disturbance using critic only policy iteration

Dong, Bo; An, Tianjiao; Zhu, Xinye; Liu, Keping

doi:10.1016/j.neucom.2021.04.032

Cited by 35 publications

(11 citation statements)

References 30 publications

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“…The research on business model innovation is mainly on the innovation driving force, including the decision-making ability of the executives and the overall level of the enterprise technology. Dong et al found that the decision-making of enterprise executives plays a crucial role in the innovation of business model, and some studies made clear that enterprise technology exerts a fundamental impact on business model innovation [ 10 ]. Premananda et al evaluated the overall level of enterprises and found that the four elements of the business model need to be integrated for effective innovation: core resources, value proposition, profit model, and important process [ 11 ].…”

Section: Review and Analysis Of Related Researchmentioning

confidence: 99%

Construction of Internet Business Innovation Network Model and Data Image Research under the Background of Game Theory

Bai

2022

Computational Intelligence and Neuroscience

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Facing the fierce market competition, enterprises not only need a deeper understanding and concept renewal in marketing theory but also need a set of standardized, practical, and efficient technical means and methods. Therefore, it is urgent to develop advanced marketing analysis tools and marketing decision-making methods. Based on game theory and neural network model, this study simplifies the existing research methods. By introducing different models, an image analysis and decision-making model based on game theory and neural network is constructed. It mainly aims at enterprise decision-making. The method used is to simulate various decision-making processes of enterprises by establishing neural network model and game model. At the same time, the image simulation of the model is carried out. The results show that the highest market share of the selected products is 36.1%, and the highest brand awareness is 9 points. The product with the second market share has better quality, 8 brand awareness points, and the highest dealer fee (2.3 yuan). Market share is less affected by product price and dealer expenses. The accuracy of the designed market share neural network model is 93%. This shows that the increase of market share is not realized simply by reducing the price but by increasing the profits of distributors and improving the brand image. Market leaders have the greatest revenue and profits. There is a positive correlation between the efforts of managers and the results achieved. Internet employees’ work effort is positively correlated with their basic salary. Different decisions have different effects on business models. The research of this paper provides a new idea for the innovation and development of Internet enterprise business model.

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Section: Review and Analysis Of Related Researchmentioning

confidence: 99%

Construction of Internet Business Innovation Network Model and Data Image Research under the Background of Game Theory

Bai

2022

Computational Intelligence and Neuroscience

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“…where k 1 is a positive feedback gain. ESO deals with modeling uncertainty in feedback linearization control [38]. First, (10) is now described as:…”

Section: B Design Of Active Disturbance Rejection Controllermentioning

confidence: 99%

Decentralized Robust Active Disturbance Rejection Control of Modular Robot Manipulators: An Experimental Investigation With Emotional pHRI

et al. 2022

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This paper presents an active disturbance rejection control (ADRC) method for modular robot manipulators (MRMs) based on extended state observer (ESO), which solves the problem of trajectory tracking when modular robot manipulators facing the emotional physical human-robot interaction (pHRI). The dynamic model of MRMs is formulated via joint torque feedback (JTF) technique that is deployed for each joint module to design the model compensation controller. ESO is used to estimate the interconnected dynamic coupling (IDC) term and the interference term caused by emotional pHRI. An uncertainty decomposition-based robust control is developed to compensate the friction term. The terminal sliding mode control (TSMC) algorithm is introduced to the controller to provide faster convergence and higher precision control effect. Based on the Lyapunov theory, the tracking error is proved to be ultimately uniformly bounded (UUB). Finally, experiments demonstrate advantages of the proposed method.INDEX TERMS Modular robot manipulators, extended state observer, terminal sliding mode, emotional pHRI, active disturbance rejection control.

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“…Jiang et al [36] used the ADP algorithm to overcome the difficulty of accurately finding the analytic solution of Hamilton-Jacobi-Isaacs (HJI) equation for the multi-player zero-sum differential game problem, and adopted the form of single network to reduce the structural complexity. Dong et al [37] elaborated a zero-sum differential game based on ADP for the optimal tracking problem of MRMs system with uncertain disturbance, and successfully solved the optimal control strategy by using the single critic NN. For nonzero-sum differential game, there is both competition and cooperation among players, and each player expects to select strategy to minimize their performance index function.…”

Section: Introductionmentioning

confidence: 99%

Event-triggered-based cooperative game optimal tracking control for modular robot manipulator with constrained input

Wei

et al. 2022

Nonlinear Dyn

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In this paper, a cooperative game optimal tracking control method based on event-triggered mechanism for constrained input modular robot manipulators (MRMs) system is introduced. According to the joint torque feedback (JTF) technique, the dynamics model of the constrained input subsystem is established and the global state space equation is derived. The control inputs of n joints in the MRM system with constrained input are taken as n participants of cooperative game, the tracking control problem of the manipulator system is transformed into the optimal control problem based on the cooperative game. Next, a fusion function containing position and velocity errors is defined to construct the performance index function. In order to improve the control performance and robustness of the manipulator system, part of the known model information is used to devise controller, the model uncertainty is dealt by the neural network (NN) observer, and the

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Zero-sum game-based neuro-optimal control of modular robot manipulators with uncertain disturbance using critic only policy iteration

Cited by 35 publications

References 30 publications

Construction of Internet Business Innovation Network Model and Data Image Research under the Background of Game Theory

Construction of Internet Business Innovation Network Model and Data Image Research under the Background of Game Theory

Decentralized Robust Active Disturbance Rejection Control of Modular Robot Manipulators: An Experimental Investigation With Emotional pHRI

Event-triggered-based cooperative game optimal tracking control for modular robot manipulator with constrained input

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