Abstract
There are two main approaches to motion control on parallel platforms: joint space control and workspace control. Joint space control is an easy-to-implement semi-closed-loop strategy, but its control effect could be better. The workspace control is to obtain the real-time position of the parallel platform through the forward solution and close the speed and position loop of the parallel platform in the workspace. This paper uses a model predictive controller (MPC) to control the parallel platform with workspace control as the research goal. The loss function is constructed based on the swarm intelligence optimization idea, and the adaptive difference algorithm is used to optimize the parameters of MPC. This part details the research background and the algorithm design process. Then, the MPC algorithm is implemented on the upper computer using C++, and the physical test is implemented. The test results show that the controller has a good control effect on the physical platform.
Published Version
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