Discrete-time positive periodic systems with state and control constraints

The aim of this paper is to provide an efficient control design technique for discrete-time positive periodic systems. In particular, stability, positivity and periodic invariance of such systems are studied. Moreover, the concept of periodic invariance with respect to a collection of boxes is introduced and investigated with connection to stability. It is shown how such concept can be used for deriving a stabilizing state-feedback control that maintains the positivity of the closed-loop system and respects states and control signals constraints. In addition, all the proposed results can be efficiently solved in terms of linear programming.

Optimal control problems with nonsmooth mixed constraints

In this paper we present a weak maximum principle for optimal control problems involving mixed constraints and pointwise set control constraints. Notably such result holds for problems with possibly nonsmooth mixed constraints. Although the setback of such result resides on a convexity assumption on the extended velocity set, we show that if the number of mixed constraints is one, such convexity assumption may be removed when an interiority assumption holds. © 2008 IEEE.

Neural Network Based Optimal Control with Constraints

In the present paper the problems of the optimal control of systems when constraints are imposed on the control is considered. The optimality conditions are given in the form of Pontryagin’s maximum principle. The obtained piecewise linear function is approximated by using feedforward neural network. A numerical example is given.

«School choice with controlled choice constraints: hard bounds versus soft bounds»

Controlled choice over public schools attempts giving options to parents while maintaining diversity, often enforced by setting feasibility constraints with hard upper and lower bounds for each student type. We demonstrate that there might not exist assignments that satisfy standard fairness and non-wastefulness properties; whereas constrained non-wasteful assignments which are fair for same type students always exist. We introduce a "controlled" version of the deferred acceptance algorithm with an improvement stage (CDAAI) that finds a Pareto optimal assignment among such assignments. To achieve fair (across all types) and non-wasteful assignments, we propose the control constraints to be interpreted as soft bounds-flexible limits that regulate school priorities. In this setting, a modified version of the deferred acceptance algorithm (DAASB) finds an assignment that is Pareto optimal among fair assignments while eliciting true preferences. CDAAI and DAASB provide two alternative practical solutions depending on the interpretation of the control constraints. JEL C78, D61, D78, I20.

Free time and mixed constrained optimal control problems

We consider free time optimal control problems with pointwise set control constraints u(t) ∈ U(t). Here we derive necessary conditions of optimality for those problem where the set U(t) is defined by equality and inequality control constraints. The main ingredients of our analysis are a well known time transformation and recent results on necessary conditions for mixed state-control constraints. ©2010 IEEE.

An Access Control Model for Protecting Provenance Graphs

Postprint

Dedução de Funções de Alívio para Priorização de Variantes de Chaveamento Adequadas à Eliminação de Sobrecargas

Eventually, violations of voltage limits at buses or admissible loadings of transmission lines and/or power transformers may occur by the power system operation. If violations are detected in the supervision process, corrective measures may be carried out in order to eliminate them or to reduce their intensity. Loading restriction is an extreme solution and should only be adopted as the last control action. Previous researches have shown that it is possible to control constraints in electrical systems by changing the network topology, using the technique named Corrective Switching, which requires no additional costs. In previous works, the proposed calculations for verifying the ability of a switching variant in eliminating an overload in a specific branch were based on network reduction or heuristic analysis. The purpose of this work is to develop analytical derivation of linear equations to estimate current changes in a specific branch (due to switching measures) by means of few calculations. For bus-bar coupling, derivations will be based on short-circuit theory and Relief Function methodology. For bus-bar splitting, a Relief Function will be derived based on a technique of equivalent circuit. Although systems of linear equations are used to substantiate deductions, its formal solution for each variant, in real time does not become necessary. A priority list of promising variants is then assigned for final check by an exact load flow calculation and a transient analysis using ATP Alternative Transient Program. At last, results obtained by simulation in networks with different features will be presented

Optimization of Discrete-Time, Stochastic Systems

* This research was supported by a grant from the Greek Ministry of Industry and Technology.

Pandemic influenza control in Europe and the constraints resulting from incoherent public health laws.

Background With the emergence of influenza H1N1v the world is facing its first 21st century global pandemic. Severe Acute Respiratory Syndrome (SARS) and avian influenza H5N1 prompted development of pandemic preparedness plans. National systems of public health law are essential for public health stewardship and for the implementation of public health policy[1]. International coherence will contribute to effective regional and global responses. However little research has been undertaken on how law works as a tool for disease control in Europe. With co-funding from the European Union, we investigated the extent to which laws across Europe support or constrain pandemic preparedness planning, and whether national differences are likely to constrain control efforts. Methods We undertook a survey of national public health laws across 32 European states using a questionnaire designed around a disease scenario based on pandemic influenza. Questionnaire results were reviewed in workshops, analysing how differences between national laws might support or hinder regional responses to pandemic influenza. Respondents examined the impact of national laws on the movements of information, goods, services and people across borders in a time of pandemic, the capacity for surveillance, case detection, case management and community control, the deployment of strategies of prevention, containment, mitigation and recovery and the identification of commonalities and disconnects across states. Results Results of this study show differences across Europe in the extent to which national pandemic policy and pandemic plans have been integrated with public health laws. We found significant differences in legislation and in the legitimacy of strategic plans. States differ in the range and the nature of intervention measures authorized by law, the extent to which borders could be closed to movement of persons and goods during a pandemic, and access to healthcare of non-resident persons. Some states propose use of emergency powers that might potentially override human rights protections while other states propose to limit interventions to those authorized by public health laws. Conclusion These differences could create problems for European strategies if an evolving influenza pandemic results in more serious public health challenges or, indeed, if a novel disease other than influenza emerges with pandemic potential. There is insufficient understanding across Europe of the role and importance of law in pandemic planning. States need to build capacity in public health law to support disease prevention and control policies. Our research suggests that states would welcome further guidance from the EU on management of a pandemic, and guidance to assist in greater commonality of legal approaches across states.

Mobile Robot Local Predictive Control under Perception Constraints

This research extends a previously developed work concerning about the use of local model predictive control in mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The platformused is a differential driven robot with a free rotating wheel. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are also introduced. In this sense, monocular image data provide an occupancy grid where safety trajectories are computed by using goal attraction potential fields

The Control of Human Arm Movement Models and Mechanical Constraints

A serial-link manipulator may form a mobile closed kinematic chain when interacting with the environment, if it is redundant with respect to the task degrees of freedom (DOFs) at the endpoint. If the mobile closed chain assumes a number of configurations, then loop consistency equations permit the manipulator and task kinematics to be calibrated simultaneously using only the joint angle readings; endpoint sensing is not required. Example tasks include a fixed endpoint (0 DOF task), the opening of a door (1 DOF task), and point contact (3 DOF task). Identifiability conditions are derived for these various tasks.

Solving optimal control problems with state constraints using nonlinear programming and simulation tools

This paper illustrates how nonlinear programming and simulation tools, which are available in packages such as MATLAB and SIMULINK, can easily be used to solve optimal control problems with state- and/or input-dependent inequality constraints. The method presented is illustrated with a model of a single-link manipulator. The method is suitable to be taught to advanced undergraduate and Master's level students in control engineering.

Optimality conditions for infinite horizon control problems with state constraints

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)