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公开(公告)号：US20190250571A1
公开(公告)日：2019-08-15
申请号：US15895393
申请日：2018-02-13
发明人： Rien Quirynen , Pedro Hespanhol
CPC分类号： G05B13/048 , G06F17/11 , G06F17/16
摘要： A control system for controlling an operation of a system with continuous-time nonlinear dynamics subject to constraints including equality and inequality constraints on state and control variables of the system, including an estimator to estimate a current state of the system using measurements of the operation of the system and a controller to iteratively solve, at each control time step, an approximation of a constrained nonlinear optimization problem to produce a control solution, wherein the approximation includes a linearization of the nonlinear dynamics of the system discretized by time intervals in the control horizon and represented using an approximation of the constraint Jacobian matrix for each time interval of the control horizon. The iterative solution procedure is based on a block-wise update formula for the approximation of the constraint Jacobian matrix and the intermediate condensing matrices using an evaluation of one or combination of the discretized dynamics of the system and at least one directional derivative of the discretized dynamics of the system. Each block in the constraint Jacobian matrix and in the intermediate condensing matrices represents one time interval in the prediction horizon and can be updated independently, based on a block-wise rank-one update formula without any iterative solution procedure and without any matrix-matrix multiplications or matrix factorizations.
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2.发明申请公开(公告)号：US20200293009A1
公开(公告)日：2020-09-17
申请号：US16297870
申请日：2019-03-11
摘要： A controller for controlling a system with continuous and discrete elements of operation accepts measurements of a current state of the system, solves a mixed-integer model predictive control (MI-MPC) problem subject to state constraints on the state of the system to produce control inputs to the system, and submits the control inputs to the system thereby changing the state of the system. To solve the MI-MPC, the controller transforms the state constraints into state-invariant control constraints on the control inputs to the system, such that any combination of values for the control inputs, resulting in a sequence of values for the state variables that satisfy the state constraints, also satisfy the state-invariant control constraints, and solve the MI-MPC problem subject to the state constraints and the state-invariant control constraints.
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公开(公告)号：US10996639B2
公开(公告)日：2021-05-04
申请号：US16297870
申请日：2019-03-11
摘要： A controller for controlling a system with continuous and discrete elements of operation accepts measurements of a current state of the system, solves a mixed-integer model predictive control (MI-MPC) problem subject to state constraints on the state of the system to produce control inputs to the system, and submits the control inputs to the system thereby changing the state of the system. To solve the MI-MPC, the controller transforms the state constraints into state-invariant control constraints on the control inputs to the system, such that any combination of values for the control inputs, resulting in a sequence of values for the state variables that satisfy the state constraints, also satisfy the state-invariant control constraints, and solve the MI-MPC problem subject to the state constraints and the state-invariant control constraints.
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公开(公告)号：US10409233B2
公开(公告)日：2019-09-10
申请号：US15895393
申请日：2018-02-13
发明人： Rien Quirynen , Pedro Hespanhol
摘要： A control system for controlling an operation of a system with continuous-time nonlinear dynamics subject to constraints including equality and inequality constraints on state and control variables of the system, including an estimator to estimate a current state of the system using measurements of the operation of the system and a controller to iteratively solve, at each control time step, an approximation of a constrained nonlinear optimization problem to produce a control solution, wherein the approximation includes a linearization of the nonlinear dynamics of the system discretized by time intervals in the control horizon and represented using an approximation of the constraint Jacobian matrix for each time interval of the control horizon. The iterative solution procedure is based on a block-wise update formula for the approximation of the constraint Jacobian matrix and the intermediate condensing matrices using an evaluation of one or combination of the discretized dynamics of the system and at least one directional derivative of the discretized dynamics of the system. Each block in the constraint Jacobian matrix and in the intermediate condensing matrices represents one time interval in the prediction horizon and can be updated independently, based on a block-wise rank-one update formula without any iterative solution procedure and without any matrix-matrix multiplications or matrix factorizations.
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