{"id":{"repo_id":"rice","oai_identifier":"oai:repository.rice.edu:1911/13349"},"canonical_url":"https://search.dev.ndltd.org/etd/rice/oai:repository.rice.edu:1911/13349","repository":{"repo_id":"rice","name":"Rice University","base_url":"https://repository.rice.edu/server/oai/request"},"display":{"title":"Modelling, simulation, and control of robots","abstract":"The continuous dynamic model of a robot is represented by nonlinear coupled differential equations. These can be discretized using first or second order Taylor's series approximations. One such model, the Greenspan Discrete Mechanics model appears to be the best for control applications. Global linearization of this model is straightforward and the linearized model is used to design $l\\sp1$ optimal controllers for the robot. The Multi Input Multi Output optimization problem splits up into decoupled Single Input Single Output problems which are individually solved. Optimal systems thus designed are simulated and compared to traditional robot controllers. Simulations confirm the $l\\sp1$ optimality of the controllers. This thesis thus provides a useful new tool for the robot control engineer.","abstract_html":"The continuous dynamic model of a robot is represented by nonlinear coupled differential equations. These can be discretized using first or second order Taylor's series approximations. One such model, the Greenspan Discrete Mechanics model appears to be the best for control applications. Global linearization of this model is straightforward and the linearized model is used to design $l\\sp1$ optimal controllers for the robot. The Multi Input Multi Output optimization problem splits up into decoupled Single Input Single Output problems which are individually solved. Optimal systems thus designed are simulated and compared to traditional robot controllers. Simulations confirm the $l\\sp1$ optimality of the controllers. This thesis thus provides a useful new tool for the robot control engineer.","abstract_has_math":true,"creators":["Chatterjee, Trinanjan"],"institution":"Rice University","degree_name":"Master of Science","degree_level":"Masters","degree_discipline":"Engineering","degree_department":null,"school":null,"contributors":[],"advisors":["Pearson, J. Boyd"],"committee_chairs":[],"committee_members":[],"year":1989,"date_issued":"1989","date_published":"1989","updated_at":"2026-07-24T04:10:39Z","subjects":["Electronics","Electrical engineering"],"languages":["eng"],"rights":["Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1911/13349","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Pearson, J. 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One such model, the Greenspan Discrete Mechanics model appears to be the best for control applications. Global linearization of this model is straightforward and the linearized model is used to design $l\\sp1$ optimal controllers for the robot. The Multi Input Multi Output optimization problem splits up into decoupled Single Input Single Output problems which are individually solved. Optimal systems thus designed are simulated and compared to traditional robot controllers. Simulations confirm the $l\\sp1$ optimality of the controllers. This thesis thus provides a useful new tool for the robot control engineer."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/1911/13349"],"dc:language.iso":["eng"],"dc:rights":["Copyright is held by the author, unless otherwise indicated. 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