Model predictive control for mobile robot applications
A system generally has one or more input signals and one or more output signals. By far, the greatest amount of work in system analysis is on Single-Input-Single-Output (SISO) systems. Therefore, it is very often that systems with multiple inputs or multiple outputs, such as Multiple-Input-Multiple-...
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2012
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| Online Access: | http://hdl.handle.net/10356/49899 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | A system generally has one or more input signals and one or more output signals. By far, the greatest amount of work in system analysis is on Single-Input-Single-Output (SISO) systems. Therefore, it is very often that systems with multiple inputs or multiple outputs, such as Multiple-Input-Multiple-Output (MIMO) are regarded as multiple SISO systems. Model Predictive Control (MPC) is an advanced control technique that can handle multiple-input-multiple-output systems with constraints naturally.Controlling the path of a system of multiple robots can be regarded as controlling a MIMO system with the inputs defined as the velocities of the robots and the outputs defined as the robot positions. Path planning is responsible for enabling robots to move to some desired locations while avoiding collisions with each other and obstacles, therefore, it is critical for robots to be autonomous. |
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