Broad Learning System Approximation-Based Adaptive Optimal Control for Unknown Discrete-Time Nonlinear Systems

Yuan, Liang'en; Li, Tieshan; Tong, Shaocheng; Xiao, Yang; Shan, Qihe

doi:10.1109/tsmc.2021.3113357

Cited by 20 publications

(4 citation statements)

References 40 publications

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“…For linear systems, if the cost function has a quadratic form in terms of states and control inputs, the standard Riccati equation can be solved to obtain the optimal controller [19]. If the system is nonlinear or the cost function is not quadratic in terms of states and controls, it is necessary to solve the Hamilton-Jacobi-Bellman (HJB) equation to obtain the optimal result [107][108][109][110][111]. However, solving the HJB equation, which is a partial differential equation, is very challenging.…”

Section: Optimal Control Designmentioning

confidence: 99%

Dynamic Positioning Control for Marine Crafts: A Survey and Recent Advances

Gao,

2024

JMSE

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This paper surveys the recent advances in dynamic positioning (DP) control for marine crafts. DP of marine crafts means that a craft can maintain a fixed position and heading, or move along a predetermined trajectory slowly without the anchoring system, using only its own thruster system to counteract ocean disturbances. The survey is by no means exhaustive but provides a survey of some of the major technological advancements in DP controller design over the years of research and development. Firstly, the model of marine crafts and some difficult problems in DP control are introduced including the impact of multiple source disturbance, unavailable velocity measurement information, resource conservation and performance optimization, destabilizing impact of faults and network security and compound multi-constraint restrictions. Then, the DP control schemes in recent years are summarized and classified in detail. Finally, some theoretical and technical problems are proposed, including online data-driven model-free control, man–machine combination intelligent control and composite hierarchical anti-disturbance control to guide future investigations.

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Section: Optimal Control Designmentioning

confidence: 99%

Dynamic Positioning Control for Marine Crafts: A Survey and Recent Advances

Gao,

2024

JMSE

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“…Its core idea is to assume that an unmanned ship moves and is controlled by a resultant force under two virtual forces: a target point has "gravity" on the unmanned ship, and some obstacles have "repulsive force" on the unmanned ship [8,9]. Since this method has the problem of local optimum, many researchers have improved it [10][11][12][13][14]. The traditional APF method usually needs to calculate the resultant force of gravitational and repulsive forces on the ship according to the speed of its own ship, real-time position, and goal position.…”

Section: Introductionmentioning

confidence: 99%

Impacts of GPS Spoofing on Path Planning of Unmanned Surface Ships

Wang

Xiao

et al. 2022

Electronics

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The Artificial Potential Field (APF) method is a classical path planning method for unmanned ships, relying on Global Positioning System (GPS) positioning information for path planning. Unfortunately, once the path planning algorithm uses inaccurate or even fake data, it will lead to ship collision, grounding, or deviation from the course, causing severe economic losses and causing significant security risks to other sailing ships. This paper aims to study the impacts of GPS spoofing on the path planning of unmanned ships. We propose a GPS attack and study GPS spoofing of path planning based on the APF method for an unmanned ship by a low-cost software-defined radio, which causes the unmanned ship to deviate from the course. Our simulation tests show that this method has significant impacts on the path planning results of the APF method.

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“…Due to wide applications of distributed optimization in many fields, model predictive control, [1][2][3] such as smart grid, [4][5][6][7] machine learning, [8][9][10] and resource allocation, [11][12][13][14] a number of scholars are involved in the study of distributed optimization. [15][16][17][18][19][20][21][22][23] They consider a category of optimization problems which defined in a networked multi-agent system:…”

Section: Introductionmentioning

confidence: 99%

“…Due to wide applications of distributed optimization in many fields, model predictive control, 1‐3 such as smart grid, 4‐7 machine learning, 8‐10 and resource allocation, 11‐14 a number of scholars are involved in the study of distributed optimization 15‐23 . They consider a category of optimization problems which defined in a networked multi‐agent system:

\min_{\tilde{x} \in ℝ^{n}} \tilde{f} false(\tilde{x} false) = \frac{1}{m} \sum_{i = 1}^{m} f_{i} false(\tilde{x} false) .

The target of all agents is to work out the global optimization solution

{\tilde{x}}^{*} \in ℝ^{n}

to problem () via local communication with their neighbors.…”

Section: Introductionmentioning

confidence: 99%

A distributed accelerated optimization algorithm over time‐varying directed graphs with uncoordinated step‐sizes

Ran

Wang

Zheng

et al. 2022

Optim Control Appl Methods

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This article proposes a distributed accelerated algorithm for solving distributed optimization problems which are defined in a time-varying directed network. Different from the existing algorithms, by implementing row-and column-stochastic matrices, this work eliminates the conservatism in the related work due to doubly-stochastic matrices, and do not required estimate the Perron eigenvector of a stochastic matrix. Assuming that the global objective function is strongly convex and the gradient of each local objective function is Lipschitz-continuous, it is proved that the algorithm converges linearly to the global optimization solution with proper uncoordinated step-sizes and momentum parameters. The numerical simulations are utilized to verify the correctness of the theoretical results and show the practicability of the proposed algorithm.

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Broad Learning System Approximation-Based Adaptive Optimal Control for Unknown Discrete-Time Nonlinear Systems

Cited by 20 publications

References 40 publications

Dynamic Positioning Control for Marine Crafts: A Survey and Recent Advances

Dynamic Positioning Control for Marine Crafts: A Survey and Recent Advances

Impacts of GPS Spoofing on Path Planning of Unmanned Surface Ships

A distributed accelerated optimization algorithm over time‐varying directed graphs with uncoordinated step‐sizes

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