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Model predictive control (MPC) is an advanced method of process control that is used to control a process ... Nonlinear Model Predictive Control Toolbox for MATLAB ...
Depending on the configuration, open-chain robotic manipulators require a degree of trajectory optimization. For instance, a robotic arm with 7 joints and 7 links (7-DOF) is a redundant system where one cartesian position of an end-effector can correspond to an infinite number of joint angle positions, thus this redundancy can be used to optimize a trajectory to, for example, avoid any ...
In contrast to the frequency domain analysis of the classical control theory, modern control theory utilizes the time-domain state space representation, [citation needed] a mathematical model of a physical system as a set of input, output and state variables related by first-order differential equations. To abstract from the number of inputs ...
In process control, the superposition principle is used in model predictive control. The superposition principle can be applied when small deviations from a known solution to a nonlinear system are analyzed by linearization .
The emgr framework is a compact open source toolbox for gramian-based model reduction and compatible with OCTAVE and MATLAB. KerMor: An object-oriented MATLAB© library providing routines for model order reduction of nonlinear dynamical systems. Reduction can be achieved via subspace projection and approximation of nonlinearities via kernels ...
Robust model predictive control is a more conservative method which considers the worst scenario in the optimization procedure. However, this method, similar to other robust controls, deteriorates the overall controller's performance and also is applicable only for systems with bounded uncertainties.
For Kugle a path-planning model predictive controller (MPC) is designed to control the inclination angles of the ballbot to follow a given path. A path-following strategy is chosen over common trajectory or reference tracking controllers to accommodate for the temporally lacking behaviour of ballbots due to the underactuated nature.
FEATool Multiphysics is a fully integrated physics and PDE simulation environment where the modeling process is subdivided into six steps; preprocessing (CAD and geometry modeling), mesh and grid generation, physics and PDE specification, boundary condition specification, solution, and postprocessing and visualization.