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The controlled variable, namely the modes\u2019 schedule, consists of the sequence of modes and the switchover times between them. We propose a gradient-descent algorithm that adjusts a given mode-schedule by changing multiple modes over time-sets of positive Lebesgue measures, thereby avoiding the inefficiencies inherent in existing techniques that change the modes one at a time. The algorithm is based on steepest descent with Armijo step sizes along G\u00e2teaux differentials of the performance functional with respect to schedule-variations, which yields effective descent at each iteration. Since the space of mode-schedules is infinite dimensional and incomplete, the algorithm\u2019s convergence is proved in the sense of Polak\u2019s framework of optimality functions and minimizing sequences. Simulation results are presented, and possible extensions to problems with dwell-time lower-bound constraints are discussed.<\/jats:p>","DOI":"10.1145\/3047411","type":"journal-article","created":{"date-parts":[[2018,1,4]],"date-time":"2018-01-04T16:27:31Z","timestamp":1515083251000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Hybrid Optimal Control under Mode Switching Constraints with Applications to Pesticide Scheduling"],"prefix":"10.1145","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2064-0788","authenticated-orcid":false,"given":"Usman","family":"Ali","sequence":"first","affiliation":[{"name":"Georgia Institute of Technology, Atlanta GA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Magnus","family":"Egerstedt","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta GA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,1,3]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2012. 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