Combine Evolutionary Optimization with Model Predictive Control in ...
Recommend Documents
putes the control actions for a problem with 12 states, 3 controls, and horizon of 30 time steps .... matrix control, and dynamic linear programming. It has been ap-.
May 31, 2012 - The scenario FHOCP is always convex, also when the uncertain ... are deterministic and aim to optimize a worst-case performance index, while ...
AbstractâThis paper addresses the optimization in fuzzy model predictive control. When the prediction model is a nonlinear fuzzy model, nonconvex ...
irradiance, temperature and six Time-of-Use (ToU) electricity rates applied on an .... where generally w(t+j) is represented by a first-order outline to ... exchange of heat with the external surroundings through the .... 256â268, Oct. 2015. [18] J
Oct 13, 2013 - of NCSs. One of the methods to overcome this drawback of the periodic paradigm, self-triggered control has been proposed so far (see, e.g., ...
Feb 1, 2011 - ... as well as prof. Danica Rosinová from Faculty of Electrical Engineering, for .... 5.1 Schematic representation of the closed-loop system. Here, d are ...... d22. Absorbed heat in layer 2 of window 5. [W ] no no no d23 ... no on ver
This paper has been developed in parallel with. [4] in which similar ideas are used in an adaptive MPC scheme for the centralized case. The paper is organized ...
Analysis and control synthesis generally hard â linearization to bring it to linear, time-invariant (LTI), continuous-time, state space form. Model Predictive Control.
1. Linear Systems. 1.1 Models of Dynamic Systems. 1.2 Analysis of LTI Discrete-Time Systems. Model Predictive Control. Spring Semester 2014. Zusatzmaterial ...
adjust the exhaust gas temperature and the rotor speed by compressor inlet ... Key-words: Gas turbine, Identification, ARX, Predictive control, Power plant, ... simplified mathematical model consist of a set of .... Turbine output torque is not appre
Printed on acid-free paper .... is due to fact that we had to be selective of our material so as to give a fuller ..... they ignore information about future uncertainty that, though not available at current ..... horizon of mode 1 are optimization va
integrated or distributed. The basic characters of the thought of MPC can be summarized as ...... 1.2 Model Predictive Control as Receding-Horizon Optimization ...... the search to the class of linear feedback u = Kx (or u = K(t)x). ...... applied to
Nov 11, 2016 - ALI MESBAH. Stochastic Model. Predictive Control. Model predictive control (MPC) has demon- strated exceptional success for the high-per-.
especially when the process is run close to its maximum capacity. Depending on the ratings of the refiner motors, there may also be active output constraints on ...
it personal in this case: all current and former members of the IST, Doris Köhler, Zoltan Nagy, Stefan ... 2 A Brief Review of Nonlinear Model Predictive Control. 7 .... They are rather applicable to a general class of sampled-data open- ...... For
where model predictive control (MPC) led to better control performance than
more traditional ..... 4.4.1 Interfaces for Matlab, Octave, Scilab and YALMIP . . . . .
61.
Abstract. This paper presents a nonlinear model predictive control (NMPC) strategy ... By means of constraint satisfactions, partial nonlinearities and modeling.
Jan 30, 2015 - OC] 30 Jan 2015. Concurrent Learning Adaptive Model. Predictive Control with Pseudospectral. Implementation. Olugbenga Moses Anubi.
Nov 21, 2017 - make it difficult to design output filters of voltage source inverters. .... switching patterns achieved by a carrier-based PWM method with a PI ...
formulation for the operative pumping control in water networks ..... in the same plot the pump flow after applying MPC with the electricity fee of pump station S4.
Aug 29, 2014 - 1. INTRODUCTION. Mobile robot unmanned path tracking is a problem of practical importance in the ... restrict the constraints of a nominal disturbance-free system and employ a form of ...... slip, Proceedings of IEEE/ASME International
MPC provides a systematic method of dealing with constraints on inputs and .... 0.5. 1. Figure 2: Closed-loop responses and responses predicted at k = 0 for an.
Dipartimento di Ingegneria dell'Informazione, .... tinuities of the state-update equations. ... for Matlab [24] (see Section 6), that can be freely downloaded from ... the first command input of the optimal sequence is applied to the process, because
This paper presents an adaptive-predictive vibration control system using ... The aim of the adaptive EKFâMPC control algorithm then is to attempt to keep.
Combine Evolutionary Optimization with Model Predictive Control in ...
Feb 11, 2015 - Abstract In order to establish successful flood control strategies to prevent or ... flood damages, real-time optimization-based control can be a ...
Water Resour Manage DOI 10.1007/s11269-015-0955-5
Combine Evolutionary Optimization with Model Predictive Control in Real-time Flood Control of a River System Po-Kuan Chiang & Patrick Willems
Received: 1 October 2014 / Accepted: 11 February 2015 # Springer Science+Business Media Dordrecht 2015
Abstract In order to establish successful flood control strategies to prevent or alleviate severe flood damages, real-time optimization-based control can be a supplementary strategy, besides setting operating rules (regulations) for the hydraulic structures. This research combines evolutionary optimization, by means of a Genetic Algorithm (GA), with the Model Predictive Control (MPC) technique to develop and test a real-time flood control method for the 12 gated weirs in the Belgian case study of the river Demer. The evolution of this method is also the main contribution of this study. The combination of GA with MPC allows coping with the highly nonlinear system behaviour and local minimum problems. The system searches for better control actions by minimizing a cost function while at the same time avoiding violation of the defined constraints. The optimization results testify that the system is able to assist the current regulation strategies that are based on fixed regulation rules (three-position controller). Keywords Evolutionary algorithm . Optimization . Model predictive control . Real-time flood control
1 Introduction In Belgium, the river Demer is viewed as an important case for flood studies. The Flemish Environment Agency (Vlaamse Milieumaatschappij, VMM) installed several hydraulic structures (e.g. movable gated weirs and flood reservoirs) and formulated operating rules, but still cannot fully avoid extreme flood events. Due to the limited space available to install additional flood control reservoirs or storage zones, it becomes more important to optimally use the available storage capacity. This can be achieved by real-time control. A complete real-time flood control scheme is capable of integrating weather prediction, flood simulation and optimization models. This research investigates the applicability of an advanced control strategy by means of MPC, and discusses its potential performance for the flood mitigation of the Demer river system.