• 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 Society for Precision Engineering
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• v.30 no.2
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• pp.171-176
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• 2013

In this research a Self-Standable mobile Robot with standing arms based on an Wheeled Inverted Pendulum is developed. Almost existing mobile robots have wide planar shape that is statistically stable and it is sometimes hard for them to run or steer on a narrow road. A Wheeled Inverted Pendulum based mobile robot has vertical shape that is upright-running and easily steering on a narrow road. It, however, requires actively balancing control and never restores the shape once it falls down. This research develops a Self-Standable mobile robot which equips standing arms and is able to change its chassis' posture freely from planar to vertical shape or vice versa.

• Journal of Industrial Technology
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• v.18
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• pp.303-308
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• 1998

In this paper a neural network controller called "Feedback-State Learning" for control of the attitude of a wheeled inverted pendulum is presented. For the controller the design of a stable feedback controller is necessary, so the LQR is used for the feedback controller because the LQR has good performance on controlling nonlinear systems. And the neural networks are used for a feed forward controller. The designed controller is applied to the stabilization of a wheeled inverted pendulum. Because of its nonlinear characteristics such as friction and parameter variations in the linearization, the wheeled inverted pendulum is used for demonstration of the effectiveness of the proposed controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.725-726
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• 2010

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.2
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• pp.162-172
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• 2011

This paper proposes embedded System of two wheeled inverted pendulum robot designed by model based design method, using MATLAB/SIMULINK and LEGO NXT Mindstorms. At first, stability and performance of controller is verified through modeling and simulation. After that direct conversion from simulation model to C code is carried and effectiveness of controller is experimentally verified. Two wheeled inverted pendulum robot has basic function about autonomous balancing control using principle of inverted pedulum and it is also possible to arrive at destination. In this paper, state feedback controller designed by quadratic optimal control method is used. And quadratic optimal control uses state feedback control gain K to minimize performance index function J. Because it is easy to find gain, this control method can be used in the controller of two wheeled inverted pendulum robot. This proposed robot system is experimentally verified with following performances - balancing control, disturbance rejection, remote control, line following and obstacle avoidance.

• 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.

• 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.15 no.3
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• pp.536-544
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• 2011

In this paper, a controller for two wheeled inverted pendulum type robot is designed to have more stable balancing capability than conventional controllers. Traditional PID control structure is chosen for the two wheeled inverted pendulum type robot, and proper gains for the controller are obtained for specified user's weights using trial-and-error methods. Next a neural network is employed to generate PID controller gains for more stable control performance when the user's weight is arbitrarily selected. Through simulation studies we find that the designed controller using the neural network is superior to the conventional PID controller.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.8-14
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• 2013

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

• 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.