Combining Model Predictive Control with Constraint-satisfaction Formulation for the Operative Pumping Control in Water Networks

ME290J Model Predictive Control Project On Input Constraint Satisfaction

Model Predictive Control for Operational Water Management Model Predictive Control for Operational Water Management

SUMMARY W ater is needed everywhere to satisfy domestic, agricultural and industrial water demands, to maintain navigation systems, and to preserve healthy and sustainable ecosystems. In order to protect us from floods and to reallocate water resources in a man-made environment, the 'hardware', water-related structures, is constructed in many water systems. However, the 'software', suitable con...

Chance-Constrained Model Predictive Control for Drinking Water Networks

This paper addresses a chance-constrained model predictive control (CC-MPC) strategy for the management of drinking water networks (DWNs) based on a finite horizon stochastic optimisation problem with joint probabilistic (chance) constraints. In this approach, water demands are considered additive stochastic disturbances with non-stationary uncertainty description, unbounded support and known (...

Constraint Reduction with Exact Penalization for Model-Predictive Rotorcraft Control

Model-Predictive Control (also known as Receding-Horizon Control (RHC)) has been highly successful in process control applications. Its use for aerospace applications has been hindered by its high computational requirements. In the present paper, it is proposed to use enhanced primal-dual interior-point optimization techniques in the convex-quadratic-program-based RHC control of a rotorcraft. E...

Nonlinear Model Predictive Control with Constraint Satisfactions for a Quadcopter

This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of ...