Pareto optimum control of a 2-DOF inverted pendulum using approximate feedback linearization and sliding mode control

Sahnehsaraei, Morteza Andalib; Mahmoodabadi, Mohammad Javad; Bagheri, Ahmad

doi:10.1177/0142331213504946

Cited by 20 publications

(29 citation statements)

References 27 publications

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“…The inverted pendulum linear state feedback controllers are mainly designed using the multi-objective uniform diversity GA and periodic multi-object PSO. In this case, an inverted pendulum system control mechanism is face-forward neural network novel fused controller and encoding of its parameters are done into real chromosomes values for GA [34].…”

Section: Issn: 2088-8708 mentioning

confidence: 99%

Robust pole placement using firefly algorithm

Sababha¹,

Zohdy²,

Kafafy³

2019

IJECE

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In this paper, the new automatic tool that is based on the firefly algorithm whose purpose is optimization of pole location in the control of state feedback has been presented. The aim is satisfying specifications of performance like settling and rise time, steady state as well as overshoot error. Utilization of Firefly algorithm has demonstrated the benefits of controllers based on this kind of time domain over controllers based on the frequency domain like Proportional-Integral Derivative (PID). The presented method is more particular for the multi-input multi-output (MIMO) systems that have substantial state numbers. The simulation results indicated that the proposed method had superior performance in providing solution to the problems that involved stabilization of helicopter under the Rationalized Model of helicopter/ Moreover, it demonstrates the Firefly algorithm effectiveness with regards to, the state observer design and feedback controller and auto-tuning.

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Section: Issn: 2088-8708 mentioning

confidence: 99%

Robust pole placement using firefly algorithm

Sababha¹,

Zohdy²,

Kafafy³

2019

IJECE

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“…By taking Laplace transform of equations (17) and (18), cart position (x) to input force (F) and pendulum angle (u) to input force (F) transfer functions are determined. These are given in equations (19) and (20), respectively…”

Section: Dynamics Of Cipsmentioning

confidence: 99%

Design and implementation of adaptive control logic for cart-inverted pendulum system

Hanwate

Hote

Budhraja

2018

Proceedings of the Institution of Mechanical Engineers, Part I:

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In this article, an adaptive control logic is proposed to serve as a supervisory control system sufficient to curb the adverse effects due to modelling uncertainties and external disturbances. The control logic belongs to the class of adaptive control methodologies. The attractive attribute of this technique is that only the superior features of each individual candidate controller are obtained by applying appropriate weight to these controllers. In order to prove its effectiveness and applicability, the benchmark problem for stabilization of cart-inverted pendulum system is carried out using this technique. The system performance is tried against that with each individual candidate controllers existing techniques. In addition, the simulation-based analysis is strengthened by analysing the performance of a real-time cart-inverted pendulum system setup, stabilized using the proposed control logic.

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“…Suppose the governing equations are according to Equations (1) [7,13]. If the conditions are satisfied, It is ensured that 1 ( ) is finite if Equation (8) holds.…”

Section: Feedback Linearization (Fbl)mentioning

confidence: 99%

“…For implementation of FBL methods, first, the following nonlinear transformation is considered [1]: Dynamical equations are expressed as follows:…”

Section: Cart-polementioning

confidence: 99%

See 1 more Smart Citation

A Hybrid Optimal Controller Based on Robust Decoupled Sliding Mode and Ddaptive Feedback Linearization

Mahmoodabadi

Soleimani

Sahnehsaraei

2018

ITC

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In this paper, a robust adaptive control method for a class of fourth-order systems is proposed. The used structure for this controller is a combination of decoupled sliding mode approach and feedback linearization technique. The decoupled sliding mode is applied to guarantee the sliding condition, and by applying the feedback linearization method, a linear control law with adaptive coefficients is employed. The final control effort is defined as the weighting summation of the decoupled sliding mode and feedback linearization controllers. Then, the controller coefficients are optimized using the multi-objective genetic algorithm. Finally, to show effectiveness of the proposed approach, it is applied to handle the cart-pole, ball-beam, and ball-wheel systems and the results are compared with those reported in the literature.

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Pareto optimum control of a 2-DOF inverted pendulum using approximate feedback linearization and sliding mode control

Cited by 20 publications

References 27 publications

Robust pole placement using firefly algorithm

Robust pole placement using firefly algorithm

Design and implementation of adaptive control logic for cart-inverted pendulum system

A Hybrid Optimal Controller Based on Robust Decoupled Sliding Mode and Ddaptive Feedback Linearization

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