Nonlinear control for output regulation of ball and plate system

Wang, Hongrui; Tian, Yantao; Fu, Shixin; Sui, Zhen

doi:10.1109/chicc.2008.4605473

Cited by 22 publications

(4 citation statements)

References 4 publications

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“…The proportional-integral-derivative (PID) controller is employed in [3], the sliding mode control is considered in [4,5]. Position of the ball is regulated by a feedback control in [6]. A nonlinear control via inputoutput linearization is demonstrated in [7].…”

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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Section: Introductionmentioning

confidence: 99%

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

Coşkun

2020

Cumhuriyet Science Journal

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“…After that, Bai et al performed a fuzzy controller to control moving of the ball [11]. In 2008, while Hongrui et al designed a non-linear controller [12], Bai et al used an Adaptive Neuro Fuzzy Inference System (ANFIS) controller for the same purpose [13]. Dong et al realized a fuzzy neural network controller optimized by genetic algorithm, then applied the genetic algorithm-based neuro-PID controller to the same system in 2009 [14,15].…”

Section: Introductionmentioning

confidence: 99%

Comparative Analysis of Evolutionary Computation Based Gain Scheduling Control for Ball and Plate Stabilization System

Gözde

2019

Balkan Journal of Electrical and Computer Engineering

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The platform stabilization systems used in marine, airborne or land vehicle applications are controlled with very different control methods basically including linear, nonlinear and artificial intelligence-based design techniques. Nowadays, evolutionary computation based optimization algorithms also provide new opportunities to engineers in order to design a gain scheduling controller. In this study, an evolutionary computation based gain scheduling controller is proposed for a ball and plate system so as to examine its control performances on a stabilization system. For this purpose, the swarm intelligence based algorithms are chosen due to their better performance than the other evolutionary computation algorithms. The results are comparatively investigated by using time domain and frequency domain analysis methods. Additionally, the robustness analysis is also applied to examine the tuning performances of these controllers in case of changing system parameters in the range of ±50%.

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“…Trajectory tracking of the ball in the BP system is carried out using various fuzzy control techniques such as hierarchical fuzzy schemes (Fan et al, 2004), indirect hierarchical fuzzy cerebellar model articulation (Moreno-Armendariz, 2010), fuzzy adaptive integral controllers (Pattanapong and Deelertpaiboon, 2013), and interval type-2 fuzzy controllers (Farooq et al, 2013). Various nonlinear controllers like the back-stepping controller, recursive back-stepping controller, switching-driving Lyapunov function, SMC, and PID-SMC are designed by Ker et al (2007), Hongrui et al (2008), Casagrande et al (2009), Liu and Liang (2010), and Debono and Bugeja (2015), respectively. Likewise, various other control schemes such as stabilisation and control using mechatronic design principles, discrete lead compensator along with rapid prototyping, visual servoing control with an industrial robot manipulator as actuator, iterative control schemes with nilpotent approximation, pneumatic controllers along with touch screen and rotary cylinders, disturbance observer based friction compensation strategies, cascaded PD controllers tuned by particle swarm optimization (PSO), and model predictive controllers are used by Awtar et al (2002), Knuplez et al (2003), Park and Lee (2003), Oriolo and Vendittelli (2005), Yuan and Zhang (2010), Wang et al (2014), Roy et al (2014), and Oravec and Jadlovska (2015), respectively.…”

Section: Introductionmentioning

confidence: 99%

Cascaded fractional order sliding mode control for trajectory control of a ball and plate system

Roy

Das

Roy

2016

Transactions of the Institute of Measurement and Control

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This paper presents a comparative study between a sliding mode controller and a fractional order sliding mode controller applied to the problem of trajectory control of a ball in a ball and plate system. The ball and plate system is a well-known benchmark to test advanced control strategies because of its multivariable nonlinear coupled dynamics, open loop instability, parameter uncertainty, and under actuation. A cascaded sliding mode controller is initially designed to mitigate the problem. Furthermore, to improve the performance, a cascaded fractional order sliding mode controller is proposed. The proposed control strategies are experimentally validated on a ball and plate laboratory setup (Feedback Instruments Model No. 033-240). Simulation and experimental studies reveal that the fractional order sliding mode controller outperforms the sliding mode controller in terms of tracking accuracy, speed of response, chattering effect, and energy efficiency.

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Nonlinear control for output regulation of ball and plate system

Cited by 22 publications

References 4 publications

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

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

Comparative Analysis of Evolutionary Computation Based Gain Scheduling Control for Ball and Plate Stabilization System

Cascaded fractional order sliding mode control for trajectory control of a ball and plate system

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