Hybrid fuzzy control of the inverted pendulum via vertical forces

Maravall, Darío; Zhou, Changjiu; Alonso, Javier

doi:10.1002/int.20062

Cited by 34 publications

(18 citation statements)

References 23 publications

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“…It is simple to demonstrate that (18) and (20) are exactly equal for any value of α(t), by substituting respectively equation (19) in (18) and (22) in (20). This implies that the subsystems [Ai Bi; Ci 0] of T-S [2,7] do not change as the value of α(t), and also the criteria of the stability (Stability theorems [29−32] ) do not change.…”

Section: Effect Of α(T) Functions On the Stabilitymentioning

confidence: 98%

New time-varying fuzzy sets based on a PSO midpoint of the universe of discourse

Ziani

2016

Int. J. Autom. Comput.

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The paper presents a robust parallel distributed compensation (PDC) fuzzy controller for a nonlinear and certain system in continuous time described by the Takagi-Sugeno (T-S) fuzzy model. This controller is based on a new type of time-varying fuzzy sets (TVFS). These fuzzy sets are characterized by displacement of the kernels to the right or left of the universe of discourse, and they are directed by a well-defined criterion. In this work, we only focused on the movement of midpoint of the universe. The movements of this midpoint are optimized by particle swarm optimization (PSO) approach.

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Section: Effect Of α(T) Functions On the Stabilitymentioning

confidence: 98%

New time-varying fuzzy sets based on a PSO midpoint of the universe of discourse

Ziani

2016

Int. J. Autom. Comput.

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“…Second, the PID control law is used as the output sets of the fuzzy system. Based on the novel idea of controlling and stabilizing the IP via vertical forces, Maravall et al 176 studied the excellent effects of vertical forces on IP stability. They also demonstrated how the fuzzy control design method could be used to construct a hybrid fuzzy control system.…”

Section: A Fuzzy Pid Composite Controlmentioning

confidence: 99%

“…Fuzzy control Model-based fuzzy control [154][155][156][157][158][159][234][235][236] Model-free fuzzy control [160][161][162]164,[166][167][168][169][170][237][238][239] Hybrid fuzzy control [171][172][173][174] The integration of fuzzy control with other traditional control Fuzzy PID composite control [175][176][177][178][179][180][181][182][240][241][242] Sliding mode variable structure control 205, Backstepping control 186,[276][277][278][279] Adaptive fuzzy control 127,189,190,[280][281][282]…”

Section: Related Studies Primary Classification Secondary Classificationmentioning

confidence: 99%

Underactuated robotics: A review

Wang

Liu

2019

International Journal of Advanced Robotic Systems

146

102

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Underactuated robotics is an emerging research direction in the field of robotics. The control input of the underactuated robot is less than the degree of freedom of the system. It has the advantages of lightweight, low energy consumption, excellent performance, and broad development prospects. This article reviews the state of the art on underactuated robotics. On the basis of previous studies, this article takes the non-holonomic constraint equation as the entry point to classify and summarize underactuated robot and their common mechanisms. The controllability of underactuated robot is further discussed. The control flow of underactuated robot is described based on the open-closed control method. In the closed-loop control, the control method based on the fuzzy system is mainly used. Finally, the difficulties in the current research of underactuated robot are summarized, and the future research directions are prospected.

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“…The structure of inverted pendulum has a lot of kinds, but no matter what kind of structure, the inverted pendulum is a high order, nonlinear, multi variable, strong coupling system, and many techniques already exist for its solution [1][2][3][4][5][6][7][8], for example, PID control, fuzzy control, adaptive control, LQR control, sliding mode variable structure control , and so on.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Controller Design of the Inverted Pendulum System based on Extended State Observer

Du¹,

Cao²

2015

Advances in Intelligent Systems Research

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Abstract. Inverted pendulum system is a kind of widely used physical model. In this paper, we present a nonlinear control scheme of single inverted pendulum system based on extended state observer. First, we establish the dynamic equations of inverted pendulum under a generic horizontal force and then linearize the inverted pendulum around the unstable upright position. Second, linear extended state observer is designed, which can observe the uncertain part of the system and various disturbances. Third, nonlinear feedback controller is designed so that the system has a stronger disturbance rejection capability. The experimental results show that the nonlinear control method based on extended state observer is effective. Because the designed control algorithm is simple, the parameters are easy to be tuning, and control effect is good, it has important reference value for similar control system with the inverted pendulum.

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Hybrid fuzzy control of the inverted pendulum via vertical forces

Cited by 34 publications

References 23 publications

New time-varying fuzzy sets based on a PSO midpoint of the universe of discourse

New time-varying fuzzy sets based on a PSO midpoint of the universe of discourse

Underactuated robotics: A review

Nonlinear Controller Design of the Inverted Pendulum System based on Extended State Observer

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