The archived-based genetic programming for optimal design of linear/non-linear controllers

Mohammadi, Adel; Nariman-Zadeh, N.; Jamali, Ali

doi:10.1177/0142331219891551

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…The choice of basic elements for the function set is driven by the main objective of these algorithms, which is to find a suitable mathematical expression that can solve the problem and provide an idea on how to deal with similar scenarios. Research in [ 46 ] is a good example for this trend, where authors are looking for the generation of optimal controllers for linear and non-linear plants. In this case, a variant of GP, known as archived-based GP, is used as an evolutionary strategy.…”

Section: State Of the Artmentioning

confidence: 99%

Revisiting Classical Controller Design and Tuning with Genetic Programming

García,

Velasco,

Angulo

et al. 2023

Sensors

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This paper introduces the application of a genetic programming (GP)-based method for the automated design and tuning of process controllers, representing a noteworthy advancement in artificial intelligence (AI) within the realm of control engineering. In contrast to already existing work, our GP-based approach operates exclusively in the time domain, incorporating differential operations such as derivatives and integrals without necessitating intermediate inverse Laplace transformations. This unique feature not only simplifies the design process but also ensures the practical implementability of the generated controllers within physical systems. Notably, the GP’s functional set extends beyond basic arithmetic operators to include a rich repertoire of mathematical operations, encompassing trigonometric, exponential, and logarithmic functions. This broad set of operations enhances the flexibility and adaptability of the GP-based approach in controller design. To rigorously assess the efficacy of our GP-based approach, we conducted an extensive series of tests to determine its limits and capabilities. In summary, our research establishes the GP-based approach as a promising solution for automating the controller design process, offering a transformative tool to address a spectrum of control problems across various engineering applications.

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Section: State Of the Artmentioning

confidence: 99%

Revisiting Classical Controller Design and Tuning with Genetic Programming

García,

Velasco,

Angulo

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…In evolutionary algorithms (EAs), genetic programming is defined as an extension to genetic algorithms (GAs) in which the structures undergoing adaptation are not strings but are hierarchical computer programs of dynamically varying shape and size. Recent research works that set the stage for current GP research topics and applications is various, and includes topology optimization of structures, 32,33 optimal modeling of complex systems, 34 controller design, 35 image processing, 36 object detection, 37 data mining, 38 control of robots, 39 and so on.…”

Section: Introductionmentioning

confidence: 99%

Optimal synthesis of crank-rocker mechanisms with optimum transmission angle for desired stroke and time-ratio using genetic programming

Ahmadi

2022

Advances in Mechanical Engineering

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Dimensional synthesis of crank-rocker mechanisms applied to provide some desired values of stroke and time ratio, is of utmost importance for designing an efficient mechanism. In the synthesis and manufacturing of crank-rocker mechanisms, the designers are further challenged by other design criteria, such as quality of motion. In this study, a novel approach based on genetic programming (GP) is proposed for dimensional synthesis of planar crank-rocker mechanisms with optimum transmission angle over the desired stroke and time-ratio. An analytical approach is elaborated which leads to an interesting relationship of length of the coupler and rocker links. It is, therefore, advised that by adopting equal lengths for coupler link and rocker link, one can guarantee the optimality of the transmission angle’s deviation ([Formula: see text]), ensuring the Grashof condition. Consequently, through an inverse modeling approach, GP method is utilized to construct some explicitly mathematical formulas to represent all the sizes and dimensions of the crank-rocker mechanism based on the any desired values of both stroke and time-ratio. In this way, an input-output data set consisting of all the dimensions and the sizes of the links as the input variables and both the stroke and time-ratio as output variables is first constructed using the pertinent mathematical equations. Indeed, such approach of inverse modeling using GP simplifies greatly the synthesis of the crack-rocker mechanisms for any desired values of both stroke and time-ratio. The proposed approach has been applied for kinematic synthesis of a crank-rocker mechanism. A comparison between the obtained results of this work and the analytic method, clearly illustrates the efficiency of the proposed approach.

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