English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we present an iterative Model Predictive Control (MPC) designfor piecewise nonlinear systems. We consider finite time control tasks wherethe goal of the controller is to steer the system from a starting configurationto a goal state while minimizing a cost function. First, we present analgorithm that leverages a feasible trajectory that completes the task toconstruct a control policy which guarantees that state and input constraintsare recursively satisfied and that the closed-loop system reaches the goalstate in finite time. Utilizing this construction, we present a policyiteration scheme that iteratively generates safe trajectories which havenon-decreasing performance. Finally, we test the proposed strategy on adiscretized Spring Loaded Inverted Pendulum (SLIP) model with massless legs. Weshow that our methodology is robust to changes in initial conditions anddisturbances acting on the system. Furthermore, we demonstrate theeffectiveness of our policy iteration algorithm in a minimum time control task.

Iterative Model Predictive Control for Piecewise Systems