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Model predictive control system and method for controlling operation of machine

A model predictive control, machine operation technology, applied in general control systems, control/regulation systems, adaptive control, etc., can solve the problems of unknown parameters of machine dynamics models, reduce control performance, and limit current methods.

Active Publication Date: 2019-11-15
MITSUBISHI ELECTRIC CORP
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] However, current approaches to adaptive and learning-based MPC are limited for several reasons
For example, while estimating unknown parameters, constraints may be violated, or control performance may be excessively degraded in order to conservatively enforce constraints
In fact, several existing methods, such as the one described in US2011 / 0022193, simply ignore the constraints and thus cannot produce an admissible control strategy for the machine given the constraints
The method described in US2016 / 0147203 solves the problem of constraints, but estimating the unknown parameters of the machine dynamics model is still difficult

Method used

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Embodiment Construction

[0033] figure 1 A block diagram of a control system 101 for controlling operation of a machine 102 is shown, according to some implementations. The control system 101 determines control inputs to the machine 102 by optimizing a cost function using a model of the machine's dynamics over time according to the principles of model predictive control (MPC). For this reason, control system 101 is referred to herein as an MPC system.

[0034] Machine 102 is a device that operates to change a quantity (such as position, velocity, current, temperature, value) in response to a command. As used herein, the operation of a machine determines the motion of the machine that changes by such an amount. A control system receives desired motion 103 of the machine, such as a desired trajectory or target point for some of the quantities, and controls the machine via control inputs 104 . Control inputs may include commands to change parameters of the machine's operation, or may include actual va...

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Abstract

A model predictive control (MPC) system for controlling an operation of a machine according to a model of the machine dynamics optimizes a cost function over a time-horizon subject to constraints to produce a sequence of control inputs to control the state of the machine over the time horizon. The machine is control using the first control input in the sequence. The cost function includes a firstterm defined by an objective of the MPC and a second term penalizing deviation of a state of the machine from a value satisfying an equation of dynamics of the machine.

Description

technical field [0001] The present invention relates generally to controlling the operation of machines, and more particularly to controlling operation using model predictive control (MPC) over a setback range. Background technique [0002] In machine control, a controller, which may be implemented using one or a combination of software or hardware, generates command values ​​for inputs to the machine based on measurements obtained, for example, from sensors and / or estimators, from the output of the machine. A controller selects an input so that the machine operates as desired, eg, operates following a desired reference profile or adjusts an output to a specific value. In several cases, the controller enforces constraints on the inputs and outputs of the machine, eg, this ensures that corresponding variables are over some predetermined ranges to ensure safe machine operation from physical specifications. To enforce such constraints, controllers often use a model of the mach...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05B13/04
CPCG05B13/048
Inventor A·克尼亚瑟夫A·马雷舍夫
Owner MITSUBISHI ELECTRIC CORP