3 research outputs found
Constrained Predictive Control of Three-PhaseBuck Rectifiers
In this paper, constrained optimal control of a current source rectifier (CSR) is presented, based on a mathematical model developed in Park鈥檚 frame. To comply with the system constraints an explicit model-based predictive controller was established. To simplify the control design, and avoid linearization, a disjointed model was utilised due to the significant time constant differences between the AC and DC side dynamics. As a result, active damping was used on the AC side, and explicit Model Predictive Control (MPC) on the DC side, avoiding non-linear dynamics. The results are compared by simulation with the performance of a state feedback control
Towards Online Model Predictive Control on a Programmable Logic Controller: Practical Considerations
Given the growing computational power of embedded controllers, the use of model
predictive control (MPC) strategies on this type of devices becomes more and more attractive.
This paper investigates the use of online MPC, in which at each step, an optimization problem
is solved, on both a programmable automation controller (PAC) and a programmable
logic controller (PLC). Three different optimization routines to solve the quadratic program
were investigated with respect to their applicability on these devices. To this end,
an air heating setup was built and selected as a small-scale multi-input single-output
system. It turns out that the code generator (CVXGEN) is not suited for the PLC as the
required programming language is not available and the programming concept with preallocated
memory consumes too much memory. The Hildreth and qpOASES algorithms
successfully controlled the setup running on the PLC hardware. Both algorithms perform
similarly, although it takes more time to calculate a solution for qpOASES. However, if
the problem size increases, it is expected that the high number of required iterations when
the constraints are hit will cause the Hildreth algorithm to exceed the necessary time to
present a solution. For this small heating problem under test, the Hildreth algorithm is
selected as most useful on a PLC
Desarrollo de un sistema de control predictivo multivariable de un generador de vapor de tubos de agua
Partiendo de la motivaci贸n de buscar medios que permitan el ahorro de
energ铆a tanto por el aspecto econ贸mico como el ecol贸gico se desarroll贸 este
trabajo el cual pretende dise帽ar un controlador predictivo basado en modelo
(CPBM) para controlar un generador de vapor de tubos de agua de forma
m谩s efectiva y eficiente que los sistemas actuales
Para este fin se realiz贸 una revisi贸n del estado del arte de los generadores
de vapor y de sus sistemas de control donde se identificaron las principales
variables a controlar. Debido al bajo desempe帽o de estos sistemas de
control se propuso, luego de un an谩lisis previo, el uso de un controlador
predictivo basado en modelo para su aplicaci贸n en el generador de vapor.
Para lograr este objetivo se estudi贸 un modelo matem谩tico no lineal
multivariable de un generador de vapor reportado en la literatura, el cual
posteriormente se utiliz贸 para realizar la simulaci贸n de la planta real. Luego
para el dise帽o del controlador se utiliz贸 el modelo linealizado con el fin de
aligerar c谩lculos.
El dise帽o del controlador multivariable est谩 basado en un controlador
predictivo que es computacionalmente m谩s eficiente que el controlador
predictivo convencional. Para la aplicaci贸n de este controlador se
consideraron restricciones en la se帽al de control y durante las pruebas
simuladas en Matlab/Simulink se le introdujo se帽ales ruidosas y
perturbaciones alcanzando buenos resultados en eficiencia energ茅tica y de
control superando al sistema actual basado en controladores PID.
Finalmente se propuso la implementaci贸n pr谩ctica del controlador haciendo
uso de un DSP hibrido.Tesi