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Kaoru Hirota - One of the best experts on this subject based on the ideXlab platform.

  • a new fuzzy controller for stabilization of parallel type double inverted Pendulum System
    Fuzzy Sets and Systems, 2002
    Co-Authors: Naoyoshi Yubazaki, Kaoru Hirota
    Abstract:

    A new fuzzy controller with 6 input items and 1 output item for stabilizing a parallel-type double inverted Pendulum System is presented based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. Each input item is assigned with a SIRM and a dynamic importance degree. The SIRMs and the dynamic importance degrees are designed such that the angular control of the longer Pendulum takes the highest priority over the angular control of the shorter Pendulum and the position control of the cart when the angle of the longer Pendulum is big. By using the SIRMs and the dynamic importance degrees, the priority orders of the three controls are automatically adjusted according to control situations. The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the three controls entirely in parallel. Simulation results show that the proposed fuzzy controller can stabilize completely a parallel-type double inverted Pendulum System within 10.0 s for a wide range of the initial angles of the two Pendulums. This is the first result for a fuzzy controller to achieve successfully complete stabilization control of a parallel-type double inverted Pendulum System.

  • upswing and stabilization control of inverted Pendulum System based on the sirms dynamically connected fuzzy inference model
    Fuzzy Sets and Systems, 2001
    Co-Authors: Naoyoshi Yubazaki, Kaoru Hirota
    Abstract:

    Abstract A new fuzzy controller is presented based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model for upswing and stabilization control of inverted Pendulum System. The fuzzy controller takes the angle and angular velocity of the Pendulum and the position and velocity of the cart as its input items, and the driving force as its output item. Each input item is assigned with a SIRM and a dynamic importance degree. When the Pendulum locates at the pending domain, the fuzzy controller becomes an upswing controller by using the saturation feature of the membership functions of the Pendulum angle. When the Pendulum locates at the upright domain, the fuzzy controller then becomes a stabilization controller and realizes smoothly the Pendulum angular control and the cart position control in parallel by using the SIRMs and the dynamic importance degrees. The fuzzy controller has a simple structure and is easily understandable compared with the other approaches. Simulation results show that the fuzzy controller can swing up the Pendulum from the pending position and then stabilize the whole System in about 3.0 s.

  • stabilization fuzzy control of parallel type double inverted Pendulum System
    IEEE International Conference on Fuzzy Systems, 2000
    Co-Authors: Naoyoshi Yubazaki, Kaoru Hirota
    Abstract:

    A fuzzy controller for stabilizing parallel-type double inverted Pendulum System is presented, based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. By using the SIRMs and the dynamic importance degrees, the angular controls of the two Pendulums and the position control of the cart are done entirely in parallel and the priority orders of the three controls are automatically adjusted according to control situations. Simulation results show that the fuzzy controller with a simple and intuitive structure can stabilize completely a parallel-type double inverted Pendulum System within 10 seconds. This is the first result for a fuzzy controller to realize complete stabilization of a parallel-type double inverted Pendulum System.

Naoyoshi Yubazaki - One of the best experts on this subject based on the ideXlab platform.

  • a new fuzzy controller for stabilization of parallel type double inverted Pendulum System
    Fuzzy Sets and Systems, 2002
    Co-Authors: Naoyoshi Yubazaki, Kaoru Hirota
    Abstract:

    A new fuzzy controller with 6 input items and 1 output item for stabilizing a parallel-type double inverted Pendulum System is presented based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. Each input item is assigned with a SIRM and a dynamic importance degree. The SIRMs and the dynamic importance degrees are designed such that the angular control of the longer Pendulum takes the highest priority over the angular control of the shorter Pendulum and the position control of the cart when the angle of the longer Pendulum is big. By using the SIRMs and the dynamic importance degrees, the priority orders of the three controls are automatically adjusted according to control situations. The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the three controls entirely in parallel. Simulation results show that the proposed fuzzy controller can stabilize completely a parallel-type double inverted Pendulum System within 10.0 s for a wide range of the initial angles of the two Pendulums. This is the first result for a fuzzy controller to achieve successfully complete stabilization control of a parallel-type double inverted Pendulum System.

  • upswing and stabilization control of inverted Pendulum System based on the sirms dynamically connected fuzzy inference model
    Fuzzy Sets and Systems, 2001
    Co-Authors: Naoyoshi Yubazaki, Kaoru Hirota
    Abstract:

    Abstract A new fuzzy controller is presented based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model for upswing and stabilization control of inverted Pendulum System. The fuzzy controller takes the angle and angular velocity of the Pendulum and the position and velocity of the cart as its input items, and the driving force as its output item. Each input item is assigned with a SIRM and a dynamic importance degree. When the Pendulum locates at the pending domain, the fuzzy controller becomes an upswing controller by using the saturation feature of the membership functions of the Pendulum angle. When the Pendulum locates at the upright domain, the fuzzy controller then becomes a stabilization controller and realizes smoothly the Pendulum angular control and the cart position control in parallel by using the SIRMs and the dynamic importance degrees. The fuzzy controller has a simple structure and is easily understandable compared with the other approaches. Simulation results show that the fuzzy controller can swing up the Pendulum from the pending position and then stabilize the whole System in about 3.0 s.

  • stabilization fuzzy control of parallel type double inverted Pendulum System
    IEEE International Conference on Fuzzy Systems, 2000
    Co-Authors: Naoyoshi Yubazaki, Kaoru Hirota
    Abstract:

    A fuzzy controller for stabilizing parallel-type double inverted Pendulum System is presented, based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. By using the SIRMs and the dynamic importance degrees, the angular controls of the two Pendulums and the position control of the cart are done entirely in parallel and the priority orders of the three controls are automatically adjusted according to control situations. Simulation results show that the fuzzy controller with a simple and intuitive structure can stabilize completely a parallel-type double inverted Pendulum System within 10 seconds. This is the first result for a fuzzy controller to realize complete stabilization of a parallel-type double inverted Pendulum System.

Ling-hong Yao - One of the best experts on this subject based on the ideXlab platform.

  • Stabilization Control of Double Inverted Pendulum System
    2008 3rd International Conference on Innovative Computing Information and Control, 2008
    Co-Authors: Wen-hua Tao, Na Sun, Chong-yang Zhang, Ling-hong Yao
    Abstract:

    The work deal with the stabilization control of double inverted Pendulum System. Inverted Pendulum System is a complicated, nonlinear, unstable System of high order. Fuzzy control research for stabilization a double inverted Pendulum at an upright position successfully is proposed based on weight variable fuzzy inputs. The weight variable fuzzy inputs is gained by combining the fuzzy control theory with the optimal control theory. The fuzzy control rules of a double inverted Pendulum are given. In order to consider cart, the lower Pendulum, the upper Pendulum error information, three different fuzzy controller were designed in this paper. Simulation results show that the controller, which the upper Pendulum is considered as main control variable, has higher accuracy and quicker convergence speed and higher precision, and simulation result is promising. The control result can be expanded the control of multilevel inverted Pendulum, and have a guiding meaning in the control of other unstable System.

Seul Jung - One of the best experts on this subject based on the ideXlab platform.

  • balancing control of a single wheel inverted Pendulum System using air blowers evolution of mechatronics capstone design
    Mechatronics, 2013
    Co-Authors: J H Lee, Hyunji Shin, Songjae Lee, Seul Jung
    Abstract:

    Abstract Inverted Pendulum Systems are one of typical control Systems suitable for cross-disciplinary education. This article delivers the historical evolution of inverted Pendulum Systems as Mechatronics capstone design projects for undergraduate students. A wheeled inverted Pendulum System is quite a challenging and interesting System to appeal students as a design project. Several design examples from two-wheel to one-wheel inverted Pendulum System are elaborated. As a current design, a one-wheel inverted Pendulum System which is our main contribution, is presented to deliver novel ideas of using air power to balance the System. The roll angle is regulated by air pressure generated from ducted fans while the pitch angle is controlled by a dc motor. Air pressure is controlled by linear control methods to keep the balancing in the roll direction. Experimental studies demonstrate the successful balancing performance.

  • balancing and navigation control of a mobile inverted Pendulum robot using sensor fusion of low cost sensors
    Mechatronics, 2012
    Co-Authors: Hyungjik Lee, Seul Jung
    Abstract:

    This article presents balancing and navigation control of the balancing robot called MIPS. MIPS is a mobile inverted Pendulum System whose structure is a combination of a wheeled mobile robot and an inverted Pendulum System. MIPS can navigate on the horizontal plane while balancing the Pendulum body. Control performance relies upon the accuracy of sensors to measure a tilted angle. Low cost gyro and tilt sensors are used and fused to detect a balancing angle. Digital filters are selectively designed for sensors to measure an inclined angle accurately with respect to different frequencies. Performances of balancing and navigation of the MIPS are tested by experimental studies through remote control.

  • control experiment of a wheel driven mobile inverted Pendulum using neural network
    IEEE Transactions on Control Systems and Technology, 2008
    Co-Authors: Seul Jung, Sungsu Kim
    Abstract:

    The mobile inverted Pendulum is developed and tested for an intelligent control experiment of control engineers. Intelligent control algorithms are tested for the control experiment of a low cost mobile inverted Pendulum System. Online learning and control using neural network of a wheel-driven mobile inverted Pendulum System is presented. Neural network learning algorithm is embedded on a digital signal processing board along with primary proportional-integral-differential controllers to achieve real time control. Without knowing dynamics of the System, uncertainties in System dynamics are compensated by neural network in an online fashion. Digital filters are designed for a gyro sensor to compensate for a phase lag. Experimental studies of balancing the Pendulum and tracking the desired trajectory of the cart for one dimensional motion are conducted. Results show the robustness of the proposed controller even when outer impacts as disturbance are present.

Sungsu Kim - One of the best experts on this subject based on the ideXlab platform.

  • control experiment of a wheel driven mobile inverted Pendulum using neural network
    IEEE Transactions on Control Systems and Technology, 2008
    Co-Authors: Seul Jung, Sungsu Kim
    Abstract:

    The mobile inverted Pendulum is developed and tested for an intelligent control experiment of control engineers. Intelligent control algorithms are tested for the control experiment of a low cost mobile inverted Pendulum System. Online learning and control using neural network of a wheel-driven mobile inverted Pendulum System is presented. Neural network learning algorithm is embedded on a digital signal processing board along with primary proportional-integral-differential controllers to achieve real time control. Without knowing dynamics of the System, uncertainties in System dynamics are compensated by neural network in an online fashion. Digital filters are designed for a gyro sensor to compensate for a phase lag. Experimental studies of balancing the Pendulum and tracking the desired trajectory of the cart for one dimensional motion are conducted. Results show the robustness of the proposed controller even when outer impacts as disturbance are present.