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Rigid link manipulators have attracted more and more attention from robot control theorists and robot users because of its various potential advantages. However, their nonlinear dynamics present a challenging control problem, since traditional linear control approaches do not easily apply. For a while, the difficulty was mitigated by the fact that manipulators were highly geared, thereby strongly...
In this paper, the problems on the model predictive control (MPC) of nonlinear systems are studied. A direct weight optimization (DWO) method based predictive control for nonlinear systems is presented. The approach gives a direct and effective predicting method and uses linear method to get the control law which avoids the complicated nonlinear optimization. The simulation result shows the efficiency...
This paper proposes a robust model predictive control scheme for nonlinear systems with state and input constraints and unknown but bounded disturbances. A standard nominal model predictive control problem with tightened constraints is solved online, and its solution defines the nominal trajectory. An ancillary control law is determined off-line which keeps the trajectories of the error system in...
In this paper, a predictor-based controller is proposed for both linear and nonlinear systems with constant input delay. The central idea is that the control signal is constructed based on the prediction of the state in the future rather than on the current state. Its performance depends on the estimation accuracy. The controller developed for linear systems is mathematically equivalent to Artstein...
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