��������������������Lecture 6 � �Laguerre Network-Based �MPC: SISO Unconstrained Case�
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Instructor: Ercan Atam
Institute for Data Science & Artificial Intelligence
Course: DSAI 586– Data-Driven Model Predictive Control
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List of contents for this lecture
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Classical methods for MPC to reduce computational load
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Discrete-time Laguerre functions (1)
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Discrete-time Laguerre functions (2)
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Discrete-time Laguerre functions (3)
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Discrete-time Laguerre functions (4)
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Orthonormality of DTLN
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DTLN: a special case (1)
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DTLN: a special case (2)
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Use of DTLN in system description (1)
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Use of DTLN in system description (2)
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Use of DTLN in MPC (1)
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Use of DTLN in MPC (2)
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DTLN-based MPC: unconstrained systems (1)
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DTLN-based MPC: unconstrained systems (2)
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DTLN-based MPC: unconstrained systems (3)
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DTLN-based MPC: unconstrained systems (4)
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DTLN-based MPC: unconstrained systems (5)
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DTLN-based MPC: unconstrained systems (6)
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DTLN-based MPC: unconstrained systems (7)
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DTLN-based MPC: unconstrained systems (8)
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DTLN-based MPC: unconstrained systems (9)
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DTLN-based MPC: unconstrained systems (10)
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DTLN-based MPC: unconstrained systems (11)
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Receding horizon implementation of DTLN-based MPC (unconstrained systems) (1)
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Receding horizon implementation of DTLN-based MPC (unconstrained systems) (2)
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Receding horizon implementation of DTLN-based MPC (unconstrained systems) (3)
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zero vector
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Infinite-time discrete-time LQR (DT-LQR) (1)
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Infinite-time discrete-time LQR (DT-LQR) (2)
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Infinite-time discrete-time LQR (DT-LQR) (3)
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Tuning parameters of DTLN-based MPC (1)
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Tuning parameters of DTLN-based MPC (2)
References �(utilized for preparation of lecture notes or MATLAB code)
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