Feedback Solution to Optimal Switching Problems With Switching Cost
Related Experiment Video
Updated: Apr 18, 2026

Measuring the Switch Cost of Smartphone Use While Walking
Published on: April 30, 2020
Abstract:
The problem of optimal switching between nonlinear autonomous subsystems is investigated in this paper where the objective is not only bringing the states to close to the desired point, but also adjusting the switching pattern, in the sense of penalizing switching occurrences and assigning different preferences to utilization of different modes. The mode sequence is unspecified and a switching cost term is used in the cost function for penalizing each switching. It is shown that once a switching cost is incorporated, the optimal cost-to-go function depends on the subsystem which was active at the previous time step. Afterward, an approximate dynamic programming-based method is developed, which provides an approximation of the optimal solution to the problem in a feedback form and for different initial conditions. Finally, the performance of the method is analyzed through numerical examples.
More Related Videos
16:23Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction
Published on: February 26, 2014
07:05Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
Published on: September 10, 2018
Related Concept Videos
Switching of BJT
Cut-off Mode ("Off" State): In this state, both the emitter-base and collector-base junctions are...
Optimal Foraging
Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
Social Exchange Theory
Social Exchange Theory
Woodward–Hoffmann Selection Rules and Microscopic Reversibility