Maximising the guaranteed feasible set for stochastic MPC with chance constraints

IIS Cuts for Stochastic Programs with Joint Chance-Constraints

We present a new method for solving stochastic programs with joint chance constraints with discretely distributed random data. The problem can be reformulated as a large-scale mixed 0-1 integer program. We derive a new class of optimality cuts based on irreducibly infeasible subsets (IIS) of an LP defined by requiring that all scenarios be satisfied and propose a method for improving the upper ...

Optimal Control with Fuzzy Chance Constraints

In this paper, a model of an optimal control problem with chance constraints is introduced. The parametersof the constraints are fuzzy, random or fuzzy random variables. Todefuzzify the constraints, we consider possibility levels.  Bychance-constrained programming the chance constraints are converted to crisp constraints which are neither fuzzy nor stochastic and then the resulting classical op...

A Novel MPC with Chance Constraints for Signal Splits Control in Urban Traffic Network

It has been recognized that model predictive control (MPC) approach can be successfully applied to the signal control of the urban traffic systems. In this research, we mainly focus on dealing with the uncertainty of the inflow to the traffic network based on the MPC method. The stochastic process describing the uncertainty and chance constraints are embedded to the mathematic programming probl...

Entailment of Set Constraints Is Not Feasible

Set constraints are inclusions between expressions denoting sets of trees. They have been used extensively for type inference and program analysis. At the lower end of the expressiveness scale there are atomic set constraints and Ines constraints (inclusions over non-empty sets) for both of which a cubic time satissability test is known. Recently, there has been increasing interest in entailmen...

Stochastic programming problems with generalized integrated chance constraints