Cooperative game-oriented optimal design in constraint-following control of mechanical systems

Sun, Qinqin; Yang, Guolai; Yang, Guolai; Chen, Ye‐Hwa

doi:10.1007/s11071-020-05800-6

Cited by 14 publications

(7 citation statements)

References 26 publications

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“…Both players in a game take the other's decisions into consideration and aim to maximize their own interests. Game theory has been widely used in all aspects of life (Mu et al, 2020;Nazari et al, 2020;Rayati et al, 2020), especially for resource allocation (Mooselu et al, 2020;Sun et al, 2020) and risk assessment (Wang et al, 2021).…”

Section: Game Theorymentioning

confidence: 99%

Research on product target image cognition based on complex network theory and game theory

Qiu

Zhang

et al. 2022

JAMDSM

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Customer knowledge of a target image is an important and primary research topic related to the product design and development process. This paper presents research on product target image reasoning based on complex network theory and game theory. First, through an evaluation of the correlations among images, a complex network structure diagram with image words as nodes is constructed, and the network attributes of node degree, betweenness and closeness to the centre of the network are calculated. Then, based on the related methods of game theory, the weights of the three network attributes are evaluated, and a comprehensive calculation is carried out on the image to obtain the target image. Finally, an image entropy algorithm is used to validate the results. Taking a scooter as an example, a complex network of 12 image words is constructed by collecting the evaluations of a total of 12 subjects from different professional fields on 8 scooter samples; thus, the verification of the case is completed. This paper provides a more efficient and accurate target image evaluation method for product design or development, which is a new proposal for the product intelligent design process.

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Section: Game Theorymentioning

confidence: 99%

Research on product target image cognition based on complex network theory and game theory

Qiu

Zhang

et al. 2022

JAMDSM

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“…It is difficult to control ACs to robustly achieve trajectory tracking while guaranteeing the DDCP in the presence of (possibly rapid and irregular) time-variant uncertainty with unknown bounds. No solution has been reported regarding this, to the best of our knowledge [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 95%

“…Sun et al [28] designed a leakage-type adaptive CBC for uncertain underactuated systems. Sun et al [29] proposed a similar control for systems with high nonlinearity and optimized the control parameters to improve performance. These CBC studies demonstrated modest control input, rigorous control design processes, and the steady-state convergence of controlled systems.…”

Section: Introductionmentioning

confidence: 99%

Constraint-based adaptive robust tracking control of uncertain articulating crane guaranteeing desired dynamic control performance

Zhang

Yin

2023

Nonlinear Dyn

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Articulating crane (AC), a widely used crane, plays an essential role in various industrial activities. Owing to its strong nonlinearity and uncertainty, its tracking control remains challenging, particularly for precise dynamic tracking control. This paper proposes an adaptive diffeomorphism-constraint-based control (ADCBC) for a nonlinear AC to robustly achieve trajectory tracking while guaranteeing desired dynamic control performance (DDCP), considering (possibly rapid and irregular) time-variant uncertainty with unknown bounds. A user-definable hard-limiting function was used to guarantee the DDCP, including the requirement for steady-state tracking error and dynamic convergence speed. The desired trajectories and DDCP were formulated as equality and inequality servo constraints, respectively. A diffeomorphism approach was adopted to incorporate inequality servo constraints into equality servo constraints, yielding new equality servo constraints. Thus, the control task was converted to enable the transformed AC to follow the new equality servo constraints and was completed by a constraint-based control (CBC) scheme, where an adaptive law was established for the estimation of online uncertainty bounds to compensate for uncertainty. No approximations or linearizations were invoked. The effectiveness and robustness of the proposed ADCBC were confirmed through rigorous proofs and simulation results. To the best of our knowledge, this is the first endeavor in tracking control while guaranteeing the DDCP for uncertain AC-like systems.

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“…By the nature of the problem, the most fitting and realistic way of choosing the optimal parameters is via the Stackelberg game, which is a leader-follower game. In this game competition, the three players (three parameters) are selected sequentially via backward induction, rather than simultaneously (as in Nash or Pareto) [20][21][22][23]. This consideration allows a full communication (as opposed to no communication, such as in Nash or Pareto) between the players (the parameters) for their choices, which in turn should enhance the system performance.…”

Section: Introductionmentioning

confidence: 99%

Optimal parameter selection for constraint-following control for mechanical systems based on Stackelberg game

et al. 2022

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Cooperative game-oriented optimal design in constraint-following control of mechanical systems

Cited by 14 publications

References 26 publications

Research on product target image cognition based on complex network theory and game theory

Research on product target image cognition based on complex network theory and game theory

Constraint-based adaptive robust tracking control of uncertain articulating crane guaranteeing desired dynamic control performance

Optimal parameter selection for constraint-following control for mechanical systems based on Stackelberg game

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