1,770 research outputs found
Slijeđenje reference s ograničenjima zasnovano na homotetičnim skupovima
In this paper, we consider the problem of constrained tracking of piecewise constant references for nonlinear dynamical systems. In the considered problem we assume that an existing controller satisfies constraints in a corresponding positive-invariant set of the system. To solve the problem we propose the use of homothetic transformations of the positive-invariant set to modify the existing control law. The proposed approach can be implemented as a tracking model predictive control or as a reference governor. Simulation and experimental results are provided, showing the applicability of the proposed approach to a class of nonlinear systems.U radu se razmatra problem slijeđenja reference s ograničenjima za nelinearne dinamičke sustave. Polazna je pretpostavka da postojeći zakon upravljanja zadovoljava ograničenja u pripadnom invarijantom skupu sustava. Uz takvu pretpostavku u radu se predlaže primjena homotetične transformacije invarijantnih skupova kako bi se izmjenio postojeći zakon upravljanja. Predloženi pristup se može primjeniti u sklopu modelskog prediktivnog upravljanja za slijeđenje reference ili samostalno za oblikovanje reference. Dani su simulacijski i eksperimentalni rezultati koji pokazuju primjenjivost predložene metode za klasu nelinearnih sustava
A Feasibility Governor for Enlarging the Region of Attraction of Linear Model Predictive Controllers
This paper proposes a method for enlarging the region of attraction of Linear
Model Predictive Controllers (MPC) when tracking piecewise-constant references
in the presence of pointwise-in-time constraints. It consists of an add-on
unit, the Feasibility Governor (FG), that manipulates the reference command so
as to ensure that the optimal control problem that underlies the MPC feedback
law remains feasible. Offline polyhedral projection algorithms based on
multi-objective linear programming are employed to compute the set of feasible
states and reference commands. Online, the action of the FG is computed by
solving a convex quadratic program. The closed-loop system is shown to satisfy
constraints, be asymptotically stable, exhibit zero-offset tracking, and
display finite-time convergence of the reference
Model Predictive Control for Signal Temporal Logic Specification
We present a mathematical programming-based method for model predictive
control of cyber-physical systems subject to signal temporal logic (STL)
specifications. We describe the use of STL to specify a wide range of
properties of these systems, including safety, response and bounded liveness.
For synthesis, we encode STL specifications as mixed integer-linear constraints
on the system variables in the optimization problem at each step of a receding
horizon control framework. We prove correctness of our algorithms, and present
experimental results for controller synthesis for building energy and climate
control
Safe Control and Learning Using Generalized Action Governor
This paper introduces the Generalized Action Governor, which is a supervisory
scheme for augmenting a nominal closed-loop system with the capability of
strictly handling constraints. After presenting its theory for general systems
and introducing tailored design approaches for linear and discrete systems, we
discuss its application to safe online learning, which aims to safely evolve
control parameters using real-time data to improve performance for uncertain
systems. In particular, we propose two safe learning algorithms based on
integration of reinforcement learning/data-driven Koopman operator-based
control with the generalized action governor. The developments are illustrated
with a numerical example.Comment: 10 pages, 4 figure
Direct data-driven control of constrained linear parameter-varying systems: A hierarchical approach
In many nonlinear control problems, the plant can be accurately described by
a linear model whose operating point depends on some measurable variables,
called scheduling signals. When such a linear parameter-varying (LPV) model of
the open-loop plant needs to be derived from a set of data, several issues
arise in terms of parameterization, estimation, and validation of the model
before designing the controller. Moreover, the way modeling errors affect the
closed-loop performance is still largely unknown in the LPV context. In this
paper, a direct data-driven control method is proposed to design LPV
controllers directly from data without deriving a model of the plant. The main
idea of the approach is to use a hierarchical control architecture, where the
inner controller is designed to match a simple and a-priori specified
closed-loop behavior. Then, an outer model predictive controller is synthesized
to handle input/output constraints and to enhance the performance of the inner
loop. The effectiveness of the approach is illustrated by means of a simulation
and an experimental example. Practical implementation issues are also
discussed.Comment: Preliminary version of the paper "Direct data-driven control of
constrained systems" published in the IEEE Transactions on Control Systems
Technolog
Centralized and distributed command governor approaches for water supply systems management
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper evaluates the applicability of Command Governor (CG) strategies to the optimal management of Drinking Water Supply Systems (DWSS) in both centralized and distributed ways. It will be shown that CG approaches provide an adequate framework for addressing the management of these large-scale interconnected systems in the presence of periodically time-varying disturbances (water demands) that can be anticipated by using time-series forecasting approaches. The proposed centralized and distributed CG schemes are presented, discussed and compared when applied to the management of DWSS considering the same set of operational goals in all cases. The paper illustrates the effectiveness of all strategies using the Barcelona DWSS as a case study and highlighting the advantages of each approach.Peer ReviewedPostprint (author's final draft
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