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Reliable robust path planning with application to mobile robots

100%

Pepy R., Kieffer M., Walter E.

International Journal of Applied Mathematics and Computer Science

2009

tom 19

nr 3

413-424

This paper is devoted to path planning when the safety of the system considered has to be guaranteed in the presence of bounded uncertainty affecting its model. A new path planner addresses this problem by combining Rapidly-exploring Random Trees (RRT) and a set representation of uncertain states. An idealized algorithm is presented first, before a description of one of its possible implementations, where compact sets are wrapped into boxes. The resulting path planner is then used for nonholonomic path planning in robotics.

Disturbance modeling and state estimation for offset-free predictive control with state-space process models

88%

Tatjewski P.

International Journal of Applied Mathematics and Computer Science

2014

tom 24

nr 2

313-323

Disturbance modeling and design of state estimators for offset-free Model Predictive Control (MPC) with linear state-space process models is considered in the paper for deterministic constant-type external and internal disturbances (modeling errors). The application and importance of constant state disturbance prediction in the state-space MPC controller design is presented. In the case with a measured state, this leads to the control structure without disturbance state observers. In the case with an unmeasured state, a new, simpler MPC controller-observer structure is proposed, with observation of a pure process state only. The structure is not only simpler, but also with less restrictive applicability conditions than the conventional approach with extended process-and-disturbances state estimation. Theoretical analysis of the proposed structure is provided. The design approach is also applied to the case with an augmented state-space model in complete velocity form. The results are illustrated on a 2×2 example process problem.

Ograniczanie wyników

2 International Journal of Applied Mathematics and Computer Science

1 Kieffer M.

1 Pepy R.

1 Tatjewski P.

1 Walter E.

1 2014

1 2009

Wyniki wyszukiwania

Reliable robust path planning with application to mobile robots

Disturbance modeling and state estimation for offset-free predictive control with state-space process models