Stabilizing of Ball and Plate System Using an Approximate Model

Yıldız, Hüseyin; Goren-Sumer, Leyla

doi:10.1016/j.ifacol.2017.08.1688

Cited by 5 publications

(3 citation statements)

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“…In fact, the ball and plate is a perfect candidate since it's unstable by default and tricky to control 4 . This plant gives space to apply many control methods and results in different behaviors which are interesting to be analyzed and compared 5,6 . There exist many forms of the ball‐plate plant which differ by the number of degrees of freedom as shown in Figures 1 and 2.…”

Section: Introductionmentioning

confidence: 99%

“…13 The point stability and trajectory tracking concerns are graphically demonstrated in the ball on plate systems. Several studies [6][7][8][9] examine these issues using modeling methods that ignore the system's nonlinear behavior, particularly the relationships between motor and plate angles. The settling time and overshoot of the ball on the plate system (BOPS) are increased when the nonlinear part of the relationship between the ball's angle and the plate's angle is ignored.…”

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confidence: 99%

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Real‐time control design and implementation of ball balancer system based on machine learning and machine vision

Elshamy

Abozalam

Sayed

et al. 2022

Concurrency and Computation

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Summary This article addresses a hybrid pseudo‐PD/machine learning controller algorithm to improve the stabilization and trajectory tracking of the ball on the plate system (BOPS). The proposed controller design depends on a machine learning algorithm that detect the angle of the servo motor required to correct the position of the ball on the plate also the parameters of the PD controller is changed online using the fuzzy logic to enhance the performance of the trajectory and point tracking of the system. This article offers three different machine learning techniques for predicting servo motor angle that obtain higher accuracies of 99.95%, 99.908%, and 99.998% for support vector regression, decision tree regression, and random forest regression, respectively. The proposed scheme has greatly improved the system's settling time and overshoot, according to simulation and practical results. The Lagrangian formulation may be used to obtain the mathematical formulation, and a practical identification experiment can be used to determine the servo motor parameter. Simulation and practical results on a BOPS dynamic model are both demonstrated to justify the validation of the proposed design scheme. The experimental practical results justify the feasibility and effectiveness of the proposed controller design strategy.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Real‐time control design and implementation of ball balancer system based on machine learning and machine vision

Elshamy

Abozalam

Sayed

et al. 2022

Concurrency and Computation

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“…A nonlinear control via inputoutput linearization is demonstrated in [7]. In more detail, the work in [8] considers the stabilization problem of the plate and ball system by an approximate solution of the matching conditions to derive a stabilizing control law. A sliding mode controller is used and compared with a linear quadratic control for the plate and ball system in [9].…”

Section: Introductionmentioning

confidence: 99%

Dynamic output-feedback H_∞ control design for ball and plate system

Coşkun

2020

Cumhuriyet Science Journal

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Ball and plate system is a nonlinear and unstable system, thus introducing great challenges to control scientists and it resembles many complicated real-time systems in several perspectives. There has been a good number of efforts to design a stabilizing controller for this system. This paper presents a dynamic output-feedback ∞ control strategy for the plate and ball system based on the solution of linear matrix inequalities (LMIs). The discussion involves deriving the equations of motion of the system by using the Lagrange method, linearizing the nonlinear equations, and designing an ∞ controller to achieve required tracking specifications on the position of the ball. The intent is to show the specified trajectory tracking performance outcomes in time domain via simulation studies conducted using MATLAB/Simulink. A circular and square trajectory following of the designed controller is compared with a baseline PID controller. It is revealed that the proposed controller exhibits an improved tracking performance to following the reference trajectories.

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