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Kinematics and dynamics of parallel structures for control design
Belda, Květoslav
The presentation deals with the kinematic and dynamic analysis of parallel structures of robotic systems. From the analysis, the model of the structure is obtained and used for simulation, control design, trajectory planning, determination of geometry of structure components (calibration), singular analysis and force construction design (choice of the drives). As an auspicious control approach is model-based approach that enable to effectively design control actions in comparison with classical approaches.
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Parallel robotic structures and their control in SIMULINK environment
Belda, Květoslav
Machine centers for industrial purposes should be accurate and proportionally flexible. One possible direction solving such requirements is utilization of parallel robots. In the paper, modeling and control of such robots are discussed. They are demonstrated by comparative SIMULINK simulation of PID/PSD controllers and discrete model-based predictive controllers. Predictive controllers design control with either mechanical or global model. The global model, in comparison with mechanical, includes drives.
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Real-time simulation and visualization of high-level model-based control of redundant parallel robots
Belda, Květoslav
The paper briefly introduces examples of high-level model-based control (Sliding Mode Control and Generalized Predictive Control) applied to the redundant parallel robots. The objective is a presentation of using MATLAB˙SIMULINK environment for real-time simulation and visualization of control of these robots. Implementation is accomplished by combination of C MEX S-Functions and ordinary C MEX-Files within SIMULINK scheme under support of Real-Time Windows Target (2.1) and Virtual Reality Toolbox (2.0).
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Adaptivní prediktivní LQ řízení s omezením
Böhm, Josef
Controller design for real systems must consider levels of signals in the system. This contrasts with the most design techniques that are based on linearity assumption. The Model predictive control (MPC) is a technique able to consider desired levels of signals. Paper deals with the situation in LQ controller design. It is shown that the latest results in MPC control can be also considered as an LQ approach.
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Optimalizace návrhu řízení založená na Monte-Carlo simulaci
Novák, Miroslav ; Pavelková, Lenka
We propose an optimization technique of controller parameters for given system according to defined signal constraints. The quality of the controller is evaluated using Monte-Carlo simulation. The system is considered to be stochastic. The optimization uses sample path method and deterministic quasi-Newtonian method. Capability of proposed technique is illustrated in the experiment.
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