• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.689-693
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• 1996

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.68-76
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.10
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• pp.1796-1803
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• 2006

This Paper describes a systematic method for designing the $H_{\infty}$ controller for the inverted pendulum which is a nonlinear and single-input double-outputs system. In particular, the open-loop system is conbined with a pre-filter to shape the open-loop transfer function for the sensitivity function ind the complementary sensitivity function to be kept the desirable frequency characteristics. Consequently, the loop shaping technique of the open-loop transfer function reduces the impacts of the model uncertainties, measurement noises and exogenous disterbances on the dynamic characteristics of the inverted pendulum. The results of simulation and experiment show the efficiency of the proposed control method comparing with conventional PID control method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1020-1026
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• 2014

A problem of sliding mode control is chattering because of controle input signal included unknown disturbance and nonlinear input parameters. This paper presents a sliding mode controller design to inverted pendulum system. In this paper, a sliding mode control algorithm to reduce a chattering is proposed. The reduction of chattering is accomplished by smoothing function for nonlinear control input. In this method, the dynamic equations of the inverted pendulum is decoupled by considering nonlinear parameters and external disturbances. Therefore, this study is applied to obtain switching control inputs for sliding mode controller. The proposed technique is tested to the control of inverted pendulum through computer simulations. The result shown reduced chattering in control input.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.2
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• pp.168-175
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• 1999

Unlike a general inverted pendulum system which is moved on the cart the proposed inverted pendulum system in this paper has an inverted pendulum which is moved on the two-degree-of-freedom parallelogram link. The dynamic equation of the pendulum system activated by the DD(Direct Drive)motor includes many nonlinear terms and has the high degree of freedoms. The problem is followed hat the exact mathmatical equations can not be analized by a general linear theory However the neural network trained by a simple learning method can control the dynamic system with hard nonlinearities. Learning procedure is the backpropagation algorithm with super-visory signal. The plant inputs obtained by the designed neural network in this paper can stabilize the pendu-lem and get the servo control. Experiment results have proce the effectiveness of the designed neural network controller.

• Journal of Korea Ship Safrty Technology Authority
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• v.1
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• pp.69-78
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• 1998

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.977-984
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• 2001

In this paper, Genetic-Fuzzy Algorithm for Inverted Pendulum is presented. This Algorithms is combine Fuzzy logic with the Genetic Algorithm. The Fuzzy Logic Controller is only designed to two inputs and one output. After Fuzzy control rules are determined, Genetic Algorithm is applied to tune the membership functions of these rules. To measure of performance of the designed Genetic-Fuzzy controller, Computer simulation is applied to Inverted Pendulum system. In the simulation, In the case of f[0.3, 0.3] Fuzzy controller is measured that maximum undershoot is $-5.0 \times 10^{-2}[rad]$, maximum undershoot is $3.92\times10^{-2}[rad]$ individually however, Designed algorithm is zero. The Steady state time is approximated that Fuzzy controller is 2.12[sec] and designed algorithm is 1.32[sec]. The result of simulation, Resigned algorithm is showed it's efficient and effectiveness for Inverted Pendulum system.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.2
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• pp.383-394
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• 2001

The stabilization control of inverted pendulum (IP) system is difficult because of its nonlinearity and structural unstability. In this paper, an Evolving Neural Network Controller (ENNC) without Error Back Propagation (EBP) is presented. An ENNC is described simply by genetic representation using an encoding strategy for types and slope values of each active functions, biases, weights and so on. By an evolutionary programming which has three genetic operation; selection, crossover and mutation, the predetermine controller is optimally evolved by updating simultaneously the connection patterns and weights of the neural networks. The performances of the proposed ENNC(PENNC)are compared with the one of conventional optimal controller and the conventional evolving neural network controller (CENNC) through the simulation and experimental results. And we showed that the finally optimized PENNC was very useful in the stabilization control of an IP system.

• Transactions of The Korea Fluid Power Systems Society
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• v.8 no.2
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• pp.1-7
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• 2011

An inverted pendulum mounted on a cart and actuated by a hydraulic servo cylinder was designed and built. Position information of the cart was acquired via a potentiometer and a angle of the pendulum was sensed by an incremental encoder. These were collected by a DAQ board and processed through the Real-Time Windows Target software(included in simulink). A simulink graphical program was implemented as a controller of the hydraulic system that governed the motion of the cart in order to maintain vertical balance of the inverted pendulum. The purpose of this study is to develop an electro-hydraulic inverted pendulum system for a modeling and controling the intrinsic unstable system. The simulation results were compared with the experimental and verified.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.6
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• pp.746-752
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• 2006

This paper presents a scheme for the parameter estimation and stabilization of unstable systems, such as inverted pendulum systems. First a stable feedback loop is constructed for an inverted pendulum system and then its parameters are estimated based on input-output data, a real-coded genetic algorithm(RCGA) and the model adjustment technique. Then, a PI-type LQ control scheme is designed based on the estimated model. The performance of the proposed algorithm is demonstrated through a set of simulation and experiment.