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We present an object oriented design for a reusable nonlinear model predictive controller framework. The framework balances reusability with flexibility and performance. Separation of interface from implementation simplifies development and facilitates use of dynamic polymorphism to change the controller behaviour at runtime. The work is presented in language agnostic terms, but the success of a particular...
This paper presents a nonlinear model predictive control algorithm for online motion planning and tracking of an omnidirectional autonomous robot. The formalism is based on a Hamiltonian minimization to optimize a control path as evaluated by a cost function. This minimization is constrained by a nonlinear plant model, which confines the solution space to those paths which are physically feasible...
We present a nonlinear model predictive control algorithm for online motion planning and tracking of an omnidirectional autonomous robot. The formalism is based on the minimization of a control Hamiltonian related to the cost function. This minimization is constrained by a nonlinear plant model. The algorithm considers point obstacles and uses a potential field to penalize proximity to those obstacles...
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