On Stochastic Model Predictive Control with Bounded Control Inputs

This paper is concerned with the problem of Model Predictive Control and Rolling Horizon Control of discrete-time systems subject to possibly unbounded random noise inputs, while satisfying hard bounds on the control inputs. We use a nonlinear feedback policy with respect to noise measurements and show that the resulting mathematical program has a tractable convex solution in both cases. Moreover, under the assumption that the zero-input and zero-noise system is asymptotically stable, we show that the variance of the state, under the resulting Model Predictive Control and Rolling Horizon Control policies, is bounded. Finally, we provide some numerical examples on how certain matrices in the underlying mathematical program can be calculated off-line.Comment: 8 page

Networked control systems: a sampled-data approach

Browse \u3e Conferences\u3e Intelligent Control. 2003 IEEE ... Networked control systems: a sampled-data approach .1254671 abstract . Hokayem, P.F.; Abdallah, C.T.; Dept. of EECE, Univ. of New Mexico, Albuquerque, NM, USA This paper appears in: Intelligent Control. 2003 IEEE International Symposium on Issue Date: 8-8 Oct. 2003 On page(s): 415 - 419 Location: Houston, TX, USA Print ISBN: 0-7803-7891-1 INSPEC Accession Number: 7929432 Digital Object Identifier: 10.1109/ISIC.2003.1254671 Date of Current Version: 08 January 2004 Abstract In this paper we present a novel modelling method for networked control systems, motivated from a sampled-data approach. We study sufficient conditions that guarantee exponential stability for the closed-loop system and illustrate our results via a numerical example

Internet-like protocols for the control and coordination of multiple agents with time delay

In this paper we show how Internet-like protocols may be used to coordinate and control the usage of a resource by n agents. Lyapunov second method is used to provide sufficient stability conditions of the dynamics of the n agents in the presence of time delay

Attaining mean square boundedness of a marginally stable noisy linear system with a bounded control input

We construct control policies that ensure bounded variance of a noisy marginally stable linear system in closed-loop. It is assumed that the noise sequence is a mutually independent sequence of random vectors, enters the dynamics affinely, and has bounded fourth moment. The magnitude of the control is required to be of the order of the first moment of the noise, and the policies we obtain are simple and computable.Comment: 10 page

Technical Report: Optimal Current Trajectories for Power Converters with Minimal Common Mode Voltage

This article addresses the topic of computing optimized pulse patterns with common mode voltage constraints. The main thrust is to obtain tractable reformulations of the CMV constraints in the frequency domain in order to avoid complex mixed time-frequency formulations. The resulting optimization problem is a nonlinear one for which efficient numerical solvers are readily available. Moreover, we provide an algorithmic way of reducing the conservatism in the reformulated problem and validate our method with numerical illustrations that highlight the benefit of the proposed approach

Stochastic receding horizon control with output feedback and bounded controls

International audienceWe study the problem of receding horizon control for stochastic discrete-time systems with bounded control inputs and incomplete state information. Given a suitable choice of causal control policies, we first present a slight extension of the Kalman filter to estimate the state optimally in mean-square sense. We then show how to augment the underlying optimization problem with a negative drift-like constraint, yielding a second-order cone program to be solved periodically online. We prove that the receding horizon implementation of the resulting control policies renders the state of the overall system mean-square bounded under mild assumptions. We also discuss how some quantities required by the finite-horizon optimization problem can be computed off-line, thus reducing the on-line computation

Integration of control, communication, computation, com- plexity and energy considerations in a coherent design strategy

This report is an overview of the research activities regarding WP06 (C4E co-design) of the FeedNetBack project. The objective of WP6 of Feed- NetBack is to propose a co-design framework, which allows the integration of control-estimation, communication, computation, complexity, and energy considerations in networked control systems. In this report we outline gen- eral guidelines for co-design and illustrate their applicability to the following case studies: (i) surveillance systems using a network of smart cameras and (ii) eets of Autonomous Underwater Vehicles (AUVs).