O presente trabalho implementa a otimização dos ganhos de um controle ativo com regulador linear quadrático (LQR), em um modelo veicular completo sujeito a um perfil de estrada proposto pela ISO 8608, para atenuação das acelerações RMS transmitidas para a carroceria e o assento do motorista. Dado que o ganho do controle LQR é formulado a partir das matrizes Q e R, o procedimento determina as matrizes ótimas do controle para a minimização das acelerações RMS transmitidas. O modelo é analisado no domínio do tempo por meio da formulação de espaço-estado, e o procedimento de otimização é avaliado pelo método dos algoritmos genéticos. Os parâmetros Q e R, que fornecem o melhor ganho para minimização do problema de otimização, reduzem em até 1000 vezes as acelerações RMS quando comparadas à situação sem atuação do controle. Após otimizar Q e R, são analisadas a influência nos demais graus de liberdade e as forças necessárias para os resultados obtidos. / This work aims to optimize the gains of an active control with linear quadratic regulator (LQR), applied in a full vehicle model subject to a random road surface profile proposed by ISO 8608, for reduction of RMS accelerations transmitted to the driver’s seat and the vehicle body. Since the gain of LQR control is formulated from the matrices Q and R, the procedure determines the optimal control matrices that minimize the RMS accelerations transmitted. The model is analyzed in the time domain through state-space formulation, and the optimization process evaluated by the method of genetic algorithms. The parameters Q and R, which provide the best gain for minimizing the optimization problem, reduce by up to 1000 times the RMS accelerations when compared to the situation without active control. Finally, after optimizing Q e R, are analyzed the influence to the other degrees of freedom and the forces necessary for the results obtained.

This thesis describes the work done to implement and develop position and trajectory control of a quadcopter. The quadcopter was originally equipped with sensors and software to estimate and control the quadcopter's orientation, but did not estimate the current position. A GPS module, GPS antenna and a LIDAR have been added to measure the position in three dimensions. Filters have been implemented and developed to estimate the position, velocity and acceleration. Four controllers have been designed that use these estimates: one PID controller and one LQ controller for vertical movement, and a position controller and a trajectory controller for horizontal movement. The position controller maintains a constant position, while the trajectory controller maintains a constant velocity while travelling along a straight line. These position and trajectory controllers calculate the reference angles required to direct the thrust necessary to control the quadcopter's movement. Additionally, an algorithm has been developed to decrease overshoot by predicting future trajectories. These controllers have proven to be successful at controlling the quadcopter's position in all three dimensions, both in practice during outdoor flight and in simulations.

This thesis deals with the optimization of state space controller of DC motor on FPGA in LabVIEW environment on NI cRIO platform. In the first part, the state space model of the given DC motor is presented in Matlab/Simulink and then the position feedback controller with steady-state error elimination and with state observer with error compen-sation using LQR method is designed. The thesis continues with transforming the con-troller to LabVIEW environment where the code is edited for FPGA use. Next, the fo-cus on FPGA hardware resources consumption optimization leads to careful work with fixed-point data type. After successful code compilation on target hardware, the real given DC motor is connected and the series of tests are performed. The output of the thesis is working state space controller running on FPGA and the graphical user inter-face on real-time host cRIO, which enables the user to control the plant and save the data on the disk.

This diploma thesis deals with inverse pendulum control. There are described types of inverse pendulums, used power electronics, sensors and their connection to the MF624 control card and to external hardware. Further is described the identification of parameters, including the assembly of a custom algorithm for identification of viscous friction in the pendulum rotary coupling. For identification of moments of inertia are used 3D CAD models, where the thesis describes also use of these models for VRML visualization. The thesis also describes how to build a dynamic model by using Matlab-Simulink and the Simscape-Multibody toolbox. This model is further used in design of the controller using LQR and its simulation testing. The controller is complemented by swing-up algorithm, security elements and MF624 driver interface is designed. The control is tested on a real inverse pendulum assembly and implemented in external hardware.

This thesis deals with the design of a lecture model of an inverse pendulum controled by a flywheel, which is a system of an unstable beam with an electromotor and a reaction wheel at its end. The moment of motor acting on the flywheel also causes a moment acting on the beam, which is the way the system is controled. The device works connected to a personal computer.

Thesis deals with design of construction, control and electronics for unstable balancing vehicle. The rst part is focused on the determination of requirements for the function and then design and manufacture of structure in line with set requirements, including 3D models and drawings. The second part is devoted to the creation of simulation models of vehicles using the Lagrange equations of the second kind and using SimMechanics. Also PID and LQR regulators are designed, including the advantages and disadvantages of each regulator for this application. The last part is focused on electronics necessary to vehicle operating. They are mainly power electronics (H-bridge, battery charger, switching supply of voltage board). There are also necessary calculations, complete PCB design and a description of the rmware for the this specifc device.

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京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第17883号 / 工博第3792号 / 新制||工||1580(附属図書館) / 30703 / 京都大学大学院工学研究科建築学専攻 / (主査)教授 中島 正愛, 教授 川瀬 博, 教授 竹脇 出 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

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This thesis document outlines the development of a multibody dynamics simulation of an actively stabilized multiple-input, multiple-output, coupled, balancing cube and the process of verifying the results by implementing the control algorithm in hardware. A non-linear simulation of the system was created in Simscape and used to develop a Linear Quadratic Gaussian control algorithm. To implement this algorithm in actual hardware, the system was first designed, manufactured, and assembled. The structure of the cube and the reaction wheels were milled from aluminum. DC brushless motors were installed into the mechanical system. In terms of electronics, a processor, orientation sensor, motor drivers, analog to digital converters, and a pulse width modulation board were assembled into the cube. Upon completion, the software to control the cube was developed using Simulink and run on a Raspberry Pi computer within the mechanism.