Adaptive neural optimal control via command filter for nonlinear multi‐agent systems including time‐varying output constraints

Zhang, Tianping; Liu, Tao

doi:10.1002/rnc.6380

Cited by 9 publications

(9 citation statements)

References 42 publications

(67 reference statements)

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“…The simulation results are shown in Figures 7,8,9,10,11,and 12. As can be seen from Figure 7, the result of better tracking performance is achieved, and the output does not violate the constraint condition.…”

Section: F I G U R Ementioning

confidence: 90%

Finite‐time optimal control for uncertain strict‐feedback nonlinear systems with input saturation and output constraints

Xia,

Li,

Zhang

et al. 2023

Adaptive Control & Signal

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SummaryIn this paper, a finite‐time optimal control (FTOC) strategy is proposed for output constrained uncertain nonlinear systems with input saturation. The controller adopts a feed‐forward and optimal feedback control structure. The second‐order command filter and the auxiliary error compensation system are designed in the feed‐forward controller, which can eliminate the influence of filtering error on system performance while avoiding the singularity problem of finite‐time control. A new critic weight updating law is proposed in the design of the optimal feedback controller, in which a neural network is utilized to approximate the relevant cost function. The control scheme can ensure that all signals in the optimize system are semi‐global practical finite‐time stable (SGPFS), and the cost function is also minimized. The effectiveness of the algorithm is validated through simulation examples.

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Section: F I G U R Ementioning

confidence: 90%

Finite‐time optimal control for uncertain strict‐feedback nonlinear systems with input saturation and output constraints

Xia,

Li,

Zhang

et al. 2023

Adaptive Control & Signal

Self Cite

View full text Add to dashboard Cite

show abstract

“…As in previous works, [10][11][12] the CNN can be employed to approximate the optimal value function…”

Section: Nn-based Critic Approximatormentioning

confidence: 99%

“…As a valid method of solving optimal consensus problems for MAS, the ADP technique contains two neural networks in general, in which the optimal controllers and the optimal value functions are estimated by using the actor network and the CNN, respectively. Inspired by previous works, [10][11][12] this article uses the single network ADP scheme to estimate optimal value functions and distributed optimal controllers. The removal of the actor network saves the computational burden and simplifies approximate architectures.…”

Section: Nn-based Critic Approximatormentioning

confidence: 99%

“…10 Then, this single network ADP scheme is used to solve optimal control issues for various control systems. 11,12 In recent years, plentiful and substantial results have been reported in the research of unmanned aerial vehicles (UAVs). A mathematical model of the UAV and a corresponding simulation program are presented to investigate the UAV steering problem when the control system is operated under various flight conditions and different operating modes.…”

Section: Introductionmentioning

confidence: 99%

“…10 Then, this single network ADP scheme is used to solve optimal control issues for various control systems. 11,12…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Neural network–based optimal fault compensation control of the nonlinear multi-agent system and its application to UAVs formation flight

Duan

Liu

Dai³

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article investigates the optimal consensus problem for unmanned aerial vehicle formation systems with actuator faults based on nonlinear multi-agent systems. Initially, for fault-free multi-agent system, the distributed optimal controllers are constructed based on the adaptive dynamic programming technique. A critic neural network is applied to approximate the solution of the nonlinear Hamilton–Jacobi–Bellman equations, in which the weight updating laws are built to guarantee the weight vectors of the critic neural network convergence. Second, the fault compensators and corresponding tuning laws are proposed to compensate for actuator faults. Through a combination of optimal controllers and fault compensators, the distributed optimal fault-tolerant controllers are obtained. Then, according to Lyapunov extension theorem, some stability criteria for ensuring the stability of the aircraft and the normal flight of the unmanned aerial vehicle formation are established in the event of an actuator failure. Finally, an example of an unmanned aerial vehicle formation system is introduced to verify the efficiency and reliability of the designed optimal fault-tolerant control scheme.

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Observer‐based critically damped feedback systems for nonlinear roll‐to‐roll printing machine applications under decentralized strategy

Kim,

Ahn

2024

Intl J Robust & Nonlinear

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SummaryThis article exhibits an advanced observer‐based single‐loop feedback system for roll‐to‐roll (R2R) machine tension control applications by treating the nonlinearities, parameter uncertainties, and closed‐loop performance inconsistency as the main challenges. The proposed solution provides the three features as follows: (a) a critically damped web velocity feedback system governed by double integral control with active damping terms and a disturbance observer (DOB) through first‐order pole–zero cancellation (PZC); (b) a model‐free second‐order PZC observer enabling feedback for the tension derivative information; (c) a combination of a proportional–integral (PI) controller, nonlinearly structured PI gains, active damping terms, and a DOB to assign critical damping performance to each tension loop through first‐order PZC. The simulation results numerically validate the feasibility of the proposed solution.

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Adaptive neural optimal control via command filter for nonlinear multi‐agent systems including time‐varying output constraints

Cited by 9 publications

References 42 publications

Finite‐time optimal control for uncertain strict‐feedback nonlinear systems with input saturation and output constraints

Finite‐time optimal control for uncertain strict‐feedback nonlinear systems with input saturation and output constraints

Neural network–based optimal fault compensation control of the nonlinear multi-agent system and its application to UAVs formation flight

Observer‐based critically damped feedback systems for nonlinear roll‐to‐roll printing machine applications under decentralized strategy

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