This paper describes a novel Decentralized Predictive Control (DePC) technique for tracking constant reference signals. The controlled system is supposed to be constituted by a set of non-overlapping subsystems coupled by states and inputs. First the offset-free tracking problem is recast as a regulation one by reformulating the plant model in the so-called “velocity-form”; secondly the decentralized control problem is solved by resorting to “tube-based” robust MPC, where dynamic interactions between subsystems are interpreted as perturbations to be rejected. Convergence results are reported and a simulation example is provided to evaluate the performances of DePC
Various efforts have been devoted to developing stabilizing distributed model predictive control (MP...
In this paper we propose a distributed MPC methods with chance constraints for tracking reference si...
A non-iterative, non-cooperative distributed state-feedback control algorithm based on neighbor-tone...
This paper describes a novel Decentralized Predictive Control (DePC) technique for tracking constant...
This paper presents a Distributed Predictive Control (DPC) method for tracking piecewise constant re...
A Distributed Predictive Control (DPC) algorithm for tracking (piecewise) constant output reference ...
This paper proposes a decentralized model predictive control (DMPC) scheme for large-scale dynamical...
For large-scale processes whose dynamics can be represented as the interaction of several dynamicall...
Distributed Model Predictive Control refers to a class of predictive control architectures in which ...
This paper presents a novel tracking predictive controller for constrained nonlinear systems capable...
Decentralized and distributed model predictive control (DMPC) addresses the problem of controlling a...
We propose in this paper novel cooperative distributed MPC algorithms for tracking of piecewise cons...
This paper proposes a cooperative distributed linear model predictive control strategy for tracking ...
Some processes are naturally suitable to be controlled in a decentralized framework: centralized con...
Various efforts have been devoted to developing stabilizing distributed model predictive control (MP...
In this paper we propose a distributed MPC methods with chance constraints for tracking reference si...
A non-iterative, non-cooperative distributed state-feedback control algorithm based on neighbor-tone...
This paper describes a novel Decentralized Predictive Control (DePC) technique for tracking constant...
This paper presents a Distributed Predictive Control (DPC) method for tracking piecewise constant re...
A Distributed Predictive Control (DPC) algorithm for tracking (piecewise) constant output reference ...
This paper proposes a decentralized model predictive control (DMPC) scheme for large-scale dynamical...
For large-scale processes whose dynamics can be represented as the interaction of several dynamicall...
Distributed Model Predictive Control refers to a class of predictive control architectures in which ...
This paper presents a novel tracking predictive controller for constrained nonlinear systems capable...
Decentralized and distributed model predictive control (DMPC) addresses the problem of controlling a...
We propose in this paper novel cooperative distributed MPC algorithms for tracking of piecewise cons...
This paper proposes a cooperative distributed linear model predictive control strategy for tracking ...
Some processes are naturally suitable to be controlled in a decentralized framework: centralized con...
Various efforts have been devoted to developing stabilizing distributed model predictive control (MP...
In this paper we propose a distributed MPC methods with chance constraints for tracking reference si...
A non-iterative, non-cooperative distributed state-feedback control algorithm based on neighbor-tone...