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OPTIMIZATION OF A FUZZY CONTROL DESIGN WITH RESPECT TO A PARALLEL MECHANISM WORKSPACE
Andrš, Ondřej ; Maga, Dušan (referee) ; Singule, Vladislav (referee) ; Březina, Tomáš (advisor)
The Ph.D. thesis is focused on using the fuzzy logic for control of a parallel manipulator based on a Stewart platform. The proposed mechanism makes possible to simulate the physiological movements of the human body and observe degradation processes of the cord implants. Parallel manipulators such as a Stewart platform represent a completely parallel kinematic mechanism that has major differences from typical serial link robots. However, they have some drawbacks of relatively small workspace and difficult forward kinematic problems. Generally, forward kinematic of a parallel manipulators is very complicated and difficult to solve. This thesis presents a simple and efficient approach to design simulation model of forward kinematic based on Takagi-Sugeno type fuzzy inference system. The control system of the parallel manipulator id based on state-space and fuzzy logic controllers. The proposed fuzzy controller uses a Sugeno type fuzzy inference system (FIS) which is derived from discrete position state-space controller with an input integrator. The controller design method is based on anfis (adaptive neuro-fuzzy inference system) training routine. It utilizes a combination of the least-squares method and the backpropagation gradient descent method for training FIS membership function parameters to emulate a given training data set. The proposed fuzzy logic controllers are used for the control of a linear actuator. The capabilities of the designed control system are shown on verification experiment.
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Design and implementation of demonstration model "double inverted pendulum"
Slabý, Vít ; Brablc, Martin (referee) ; Bastl, Michal (advisor)
This thesis describes the process of rebuilding an experimental model of a single pendulum on a cart into the double pendulum on a cart. The control algorithm in MATLAB/Simulink environment for stabilization of the pendulum in the inverse position is designed. For this purpose, LQR state feedback control was implemented. Also method for swinging the pendulum into inverse position from stable state (swing-up) was designed. Feedforward method was utilised for swing-up control. In the thesis, functionality of these algorithms is shown.
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Modeling and analysis of laboratory rotational pendulum
Nedvědický, Pavel ; Bastl, Michal (referee) ; Brablc, Martin (advisor)
This bachelor thesis aims at modelling, identification and control of Furuta pendulum. System was described via mathematical equations and simulation model was created in Matlab/Simulink. Parameters of rotary inverted pendulum were estimated using the simulation model. Then the thesis deals with swing up via torque impulse, energy control and PD regulator. In the part dealing with friction five compensation models were created. They include change of friction during rotation and one of them is dynamic model, Reset Integrator. Models were verified by adding them as an input to an actuator and testing them. To stabilize pendulum in inverted position state feedback control with state observer was designed using LQR method. Final regulation included all knowledge obtained during this thesis.
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Inteligent Controller of Active Magnetic Bearing
Turek, Milan ; Čech, Vladimír (referee) ; Ondrůšek, Čestmír (referee) ; Březina, Tomáš (advisor)
The PhD thesis describes control design of active magnetic bearing. Active magnetic bearing is nonlinear unstable system. This means it is not possible to use classic methods of control design for linear time invariant systems. Also methods of nonlinear control design are not universal and theirs application is not easy task. The thesis describes usage of simple nonlinear compensation which linearizes response of active magnetic bearing and allows usage of classic methods of control design for linear time invariant systems. It is shown that CARLA method can significantly improve parameters of designed controller. First part of thesis describes derivation of model of controlled active magnetic bearing and nonlinear compensation which linearizes response of controlled active magnetic bearing on input signal. Following part contains description of methods of state control design methods, selected methods of robust control design and most common methods of artificial intelligence used for control design and implementation. Next part describes hardware of used experimental device and its parameters. It also contains experimental derivation of model of electromagnetic force because the parameters are not available from manufacturer. Last part describes control design of active magnetic bearing. Several different approaches are described here. The approaches vary from completely experimental approach, through using Ziegler-Nichols method, state control design to methods for robust control design. During design is heavily used CARLA method which is very suitable for usage for online learning in real controller due its principle.
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Design and implementation of demonstration model "double inverted pendulum"
Slabý, Vít ; Brablc, Martin (referee) ; Bastl, Michal (advisor)
This thesis describes the process of rebuilding an experimental model of a single pendulum on a cart into the double pendulum on a cart. The control algorithm in MATLAB/Simulink environment for stabilization of the pendulum in the inverse position is designed. For this purpose, LQR state feedback control was implemented. Also method for swinging the pendulum into inverse position from stable state (swing-up) was designed. Feedforward method was utilised for swing-up control. In the thesis, functionality of these algorithms is shown.
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|
|
Modeling and analysis of laboratory rotational pendulum
Nedvědický, Pavel ; Bastl, Michal (referee) ; Brablc, Martin (advisor)
This bachelor thesis aims at modelling, identification and control of Furuta pendulum. System was described via mathematical equations and simulation model was created in Matlab/Simulink. Parameters of rotary inverted pendulum were estimated using the simulation model. Then the thesis deals with swing up via torque impulse, energy control and PD regulator. In the part dealing with friction five compensation models were created. They include change of friction during rotation and one of them is dynamic model, Reset Integrator. Models were verified by adding them as an input to an actuator and testing them. To stabilize pendulum in inverted position state feedback control with state observer was designed using LQR method. Final regulation included all knowledge obtained during this thesis.
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|
|
OPTIMIZATION OF A FUZZY CONTROL DESIGN WITH RESPECT TO A PARALLEL MECHANISM WORKSPACE
Andrš, Ondřej ; Maga, Dušan (referee) ; Singule, Vladislav (referee) ; Březina, Tomáš (advisor)
The Ph.D. thesis is focused on using the fuzzy logic for control of a parallel manipulator based on a Stewart platform. The proposed mechanism makes possible to simulate the physiological movements of the human body and observe degradation processes of the cord implants. Parallel manipulators such as a Stewart platform represent a completely parallel kinematic mechanism that has major differences from typical serial link robots. However, they have some drawbacks of relatively small workspace and difficult forward kinematic problems. Generally, forward kinematic of a parallel manipulators is very complicated and difficult to solve. This thesis presents a simple and efficient approach to design simulation model of forward kinematic based on Takagi-Sugeno type fuzzy inference system. The control system of the parallel manipulator id based on state-space and fuzzy logic controllers. The proposed fuzzy controller uses a Sugeno type fuzzy inference system (FIS) which is derived from discrete position state-space controller with an input integrator. The controller design method is based on anfis (adaptive neuro-fuzzy inference system) training routine. It utilizes a combination of the least-squares method and the backpropagation gradient descent method for training FIS membership function parameters to emulate a given training data set. The proposed fuzzy logic controllers are used for the control of a linear actuator. The capabilities of the designed control system are shown on verification experiment.
|
|
|
Inteligent Controller of Active Magnetic Bearing
Turek, Milan ; Čech, Vladimír (referee) ; Ondrůšek, Čestmír (referee) ; Březina, Tomáš (advisor)
The PhD thesis describes control design of active magnetic bearing. Active magnetic bearing is nonlinear unstable system. This means it is not possible to use classic methods of control design for linear time invariant systems. Also methods of nonlinear control design are not universal and theirs application is not easy task. The thesis describes usage of simple nonlinear compensation which linearizes response of active magnetic bearing and allows usage of classic methods of control design for linear time invariant systems. It is shown that CARLA method can significantly improve parameters of designed controller. First part of thesis describes derivation of model of controlled active magnetic bearing and nonlinear compensation which linearizes response of controlled active magnetic bearing on input signal. Following part contains description of methods of state control design methods, selected methods of robust control design and most common methods of artificial intelligence used for control design and implementation. Next part describes hardware of used experimental device and its parameters. It also contains experimental derivation of model of electromagnetic force because the parameters are not available from manufacturer. Last part describes control design of active magnetic bearing. Several different approaches are described here. The approaches vary from completely experimental approach, through using Ziegler-Nichols method, state control design to methods for robust control design. During design is heavily used CARLA method which is very suitable for usage for online learning in real controller due its principle.
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