explicit mpc design -凯发k8网页登录

fast model predictive control using precomputed solutions instead of run-time optimization

explicit model predictive control uses offline computations to determine all operating regions in which the optimal control moves are determined by evaluating an affine function of the state. explicit mpc controllers require fewer run-time computations than traditional (implicit) model predictive controllers and are therefore useful for applications that require small sample times. to implement explicit mpc, first design a traditional (implicit) model predictive controller for your application, and then use this controller to generate an explicit mpc controller for use in real-time control. for more information, see .

functions

create controller

	convert implicit mpc controller to explicit mpc controller
	bounds on explicit mpc control law parameters
	optimization options for explicit mpc generation
	reduce explicit mpc controller complexity and memory requirements

visualize control law

	visualize explicit mpc control law as 2-d sectional plot
	parameters for `plotsection`

simulate controller

	compute optimal control using explicit mpc
	option set for `mpcmove` function
	mpc controller state
	simulate an mpc controller in closed loop with a linear plant
	mpc simulation options

objects

explicit model predictive controller

blocks

explicit model predictive controller

topics

explicit mpc basics

explicit model predictive control uses offline computations to determine all operating regions in which the optimal control moves are determined by evaluating an affine function of the state.
to implement explicit mpc, first design a traditional model predictive controller for your application, and then use this controller to generate an explicit mpc controller for use in real-time control.
design and simulate an explicit model predictive controller for a siso plant.

case studies

control an unstable aircraft with saturating actuators using an explicit model predictive controller.
design an explicit model predictive controller for a dc servomotor with constraints on the manipulated variable and unmeasured output.
control an inverted pendulum in an unstable equilibrium position using an explicit model predictive controller.