• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.69-74
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• 2012

In this research equations of motion of a Wheeled Inverted Pendulum (WIP) which is running on the inclined road and changing its center of gravity. Difference between a conventional cart inverted pendulum and the WIP is also considered. The WIP has small planar size so that it has been used as a mobile platform for several applications which require slender frame in order to travel on the narrow road. The WIP has almost the same unstable properties as conventional inverted pendulums have. There needs an aggressive control scheme for the WIP not to fall down. In order to design a high performance control scheme, equations of motion of the WIP, which is running under various environment and operating conditions, should be derived and considering its properties is necessary.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.617-623
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• 2010

In this research an LMI based mixed $H_2/H_{\infty}$ controller for a Wheeled Inverted Pendulum is designed and a numerical simulation of that is carried out. The Wheeled Inverted Pendulum is a kind of an inverted pendulum that has two equivalent points. To keep that the naturally unstable equivalent point, a controller should control the wheels persistently. Dynamic equations of the Wheeled Inverted Pendulum are derived with considering inclined road that is one of the representative road conditions. A Linear Matrix Inequality method is used to construct a controller that is able to stabilize the Wheeled Inverted Pendulum with considering the inclined road condition aggressively. Various numerical simulations show that the LMI based controller is doing well on not only flat road but also inclined road condition.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.283-289
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• 2011

In this research a controller based on velocity estimator for a Wheeled Inverted Pendulum (WIP) is designed and various numerical simulation studies are carried out. The WIP has stable and unstable equivalent points. To Keep the unstable equilibrium point, a controller should control carefully the wheels persistently. There are angle, angular velocity, displacement, and velocity of the WIP for controller inputs. The velocity is obtained by differentiating the encoder signals from the motor and is subject to the resolution of the encoder. An improved velocity detection method is proposed based on low resolution encoder and velocity estimator. Various numerical simulations are carried out for showing the validation of the velocity estimator in case of the inclined road condition.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.127-134
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• 2016

This paper presents a robust control of a reaction wheel inverted pendulum. To this end, a mathematical model is derived using physical laws, and then parameters in the model are identified as well. Based on the model, a robust position control is designed, which consists of two parts: swing-up control using passivity and robust stabilization control using LMI (Linear Matrix Inequality). When the pendulum starts to move, the swing-up control is applied. If the position of the pendulum is near the desired upright position, the control is switched to the robust stabilization control. This robust control is employed in order to deal with the uncertainties in the inertia of the pendulum dynamics. The performance of the proposed control scheme is validated not only simulation but also real experiment.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.157-163
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• 2011

In this paper, configuration control for the Horizontal Maintenance and driving of the mobile inverted pendulum robot has been studied using ARS(Attitude Refrence System). The inverted pendulum technique is getting attention and there have been many researches on the seg-way since the US. Using its 2 freedom, a mobile inverted pendulum robot can move in various modes and Our robot performs goal reaching ARS. Mobile inverted pendulum robot fall down to the forward or reverse direction to converge to the stable point. Kalman Filter is normally used for the algorithm and numerous research is progressing at the moment. To calculate the attitude in ARS using 2 axis gyro(roll, pitch) and 3 axis accelerometers (x, y, z). In this paper we present a two wheel robot system for an autonomous mobile robot. This paper realized the robot control method which is much simpler but able to get desired performance by using the IMU and PID control.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.432-439
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• 2012

In this paper, instead of the conventional PD controller for balancing control of two wheeled inverted pendulum robots, an improved PD controller using the neural network is proposed and implemented for performance verification. First, a two wheeled inverted pendulum robot system is constructed for experiment. Next proper gains of the conventional PD controller according to users' weights are obtained for balancing the robot by use of the trial and error method. The PD gains based on the trial and error method are generalized through the neural network. Experiment results show that the PD controller based on the neural network has better performance than the conventional PD controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.228-236
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• 2012

In this paper, a controller for two wheeled inverted pendulum robot is designed to have more stable balancing capability than conventional controller. Fuzzy control structure is chosen for the two wheeled inverted pendulum robot, and fuzzy membership function factors for the controller are obtained for specified 3 users' weights using trial-and-error method. Next a neural network is employed to generate fuzzy membership function factors for more stable control performance when the user's weight is arbitrarily selected. Through the simulation study we find that the designed fuzzy controller using the neural network is superior to the conventional fuzzy controller.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.01a
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• pp.279-280
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• 2011

2바퀴이상의 로봇은 중심점을 기준으로 안정화가 이루어진다. 그러나 2바퀴이하의 로봇으로 수직 자세를 유지하기 위해서는 로봇자체를 기울여 중심점을 이동하므로 수평을 유지할 수 있다. 그러나 이러한 중심점의 이동은 속도나 방향성분이 같이 출력되므로 정확한 센서의 계산이 요구되고 정밀한 제어를 필요로 한다. 또한 많은 구조물로 인해 장애물 인식 및 자율주행 알고리즘 등이 필요하며 장시간 정보획득과 무인기 연동을 위한 빠른 움직임을 가져야한다. 위의 2조건을 만족하기 위한 구성으로 최근들어 두 바퀴를 가지는 모바일 역진자 로봇에 대한 연구가 활발히 이루어지고 있다. 이는 서비스 및 주행 로봇의 알고리즘이 휴머노이드에서 모바일 역진자 로봇으로 변화되었기 때문이다. 모바일 역진자 로봇은 휴머노이드에 비하여 사용되는 모터의 수가 적고 균형을 잡으려면 관절마다 값비싼 고성능 모터가 필요하며 이를 가동하려면 전력도 많이 소모되며 대용량 배터리를 장착할 수밖에 없게 된다. 반면 바퀴로 움직이는 로봇은 전력이 적게 들고 이동도 쉽다. 따라서 본 연구에서는 IMU를 이용한 간단하면서도 정확한 센서의 연산 방법과 이를 이용한 자세제어 방법을 연구한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.595-601
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• 2011

This paper presents balancing control of inverted pendulum on the ROBOKER arm using visual information. The angle of the inverted pendulum placed on the robot arm is detected by a stereo camera and the detected angle is used as a feedback and tracking error for the controller. Thus, the overall closed loop forms a visual servoing control task. To improve control performance, neural network is introduced to compensate for uncertainties. The learning algorithm of radial basis function(RBF) network is performed by the digital signal controller which is designed to calculate floating format data and embedded on a field programmable gate array(FPGA) chip. Experimental studies are conducted to confirm the performance of the overall system implementation.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.5
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• pp.652-658
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• 2010

This paper presents the implementation and control of a two wheeled mobile robot(TWMR) based on a balancing mechanism. The TWMR is a mobile inverted pendulum structure that combines an inverted pendulum system and a mobile robot system with two arms instead of a rod. To improve robustness due to disturbances, the radial basis function (RBF) network is used to control an angle and a position at the same time. The reference compensation technique(RCT) is used as a neural control method. Experimental studies are conducted to demonstrate performance of neural network controllers. The robot are implemented with the remote control capability.