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nonlinear model predictive control for improving range-based relative localization by maximizing observability

INTERNATIONAL JOURNAL OF MICRO AIR VEHICLES 2022年 14卷

作者： Li, Shushuai De Wagter, Christophe de Croon, Guido C. H. E. TUDelft MAVLab Delft Netherlands

Wireless ranging measurements have been proposed for enabling multiple Micro Air Vehicles (MAVs) to localize with respect to each other. However, the high-dimensional relative states are weakly observable due to the scalar distance measurement. Hence, the MAVs have degraded relative localization and control performance under unobservable conditions as can be deduced by the Lie derivatives. This paper presents a nonlinear model predictive control (NMPC) by maximizing the determinant of the observability matrix to generate optimal control inputs, which also satisfy constraints including multi-robot tasks, input limitation, and state bounds. Simulation results validate the localization and control efficacy of the proposed MPC method for range-based multi-MAV systems with weak observability, which has faster convergence time and more accurate localization compared to previously proposed random motions. A real-world experiment on two Crazyflies indicates the optimal states and control behaviours generated by the proposed NMPC.

关键词： Optimal control micro air vehicle swarming ultra-wideband nonlinear model predictive control

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Experimental study of rigorous nonlinear model predictive control for a packed distillation column

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JOURNAL OF THE CHINESE INSTITUTE OF CHEMICAL ENGINEERS 1997年第3期28卷 151-162页

作者： Jang, SS Wang, LLJ NATL TSING HUA UNIV DEPT CHEM ENGN HSINCHU 30043 TAIWAN

Dynamic modeling of distillation processes has been substantial in recent years. Our objective is to study the feasibility of real-time implementation of rigorous dynamic distillation models through on-line experimental studies. A rigorous model for a packed bed system is solved using the method of collocation polynomial. The control methodology used is a two-phase approach that consists of an on-line identification phase and an on-line optimization phase. The identification phase updates the key parameters of the rigorous model, while the optimization phase determines the control actions for the immediate future. The experimental system selected is a pilot-scale packed bed distillation process. The experimental studies show that the on-line control using this approach is feasible and performs better than traditional controllers.

关键词： rigorous model real-time control nonlinear model predictive control packed bed distillation process

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modeling, state estimation and nonlinear model predictive control of cathode exhaust gas mass flow for PEM fuel cells

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control ENGINEERING PRACTICE 2016年 49卷 76-86页

作者： Schultze, M. Horn, J. Univ Fed Armed Forces Hamburg Helmut Schmidt Univ Dept Elect Engn Inst Control Engn Holstenhofweg 85 D-22043 Hamburg Germany

Polymer electrolyte membrane fuel cells are efficient energy converters and provide electrical energy, water and oxygen depleted air with a low oxygen content as exhaust gas if fed with air. Due to their low emission of greenhouse gases and noise they are investigated as replacement for auxiliary power units currently used for electrical power supply on aircraft. Oxygen depleted air, called ODA-gas, with an oxygen concentration of 10-11% and a low humidity can be used for tank-inerting on aircraft. A challenging task is controlling the fuel cell system for generation of dehumidified ODA-gas mass flow while simultaneously keeping bounds and gradients on control inputs. This task is attacked by a nonlinear model predictive control. Not all system states can be measured and some states measured exhibit a significant time delay. A nonlinear state estimation strategy builds the entire system state and compensates for the delay. The nonlinear model predictive control and the state estimation are derived from the system model, which is presented. Simulation and experimental results are shown. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： State estimation nonlinear model predictive control PEM fuel cell

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Robust nonlinear model predictive control for Ship Dynamic Positioning Using Laguerre Function

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IEEE ACCESS 2022年 10卷 127563-127574页

作者： Hou, Xiuhui Deng, Fang Yang, Hualin Yu, Dunjing Zhang, Hanlin Li, Boyang Qingdao Univ Sci & Technol Coll Mech & Elect Engn Qingdao 266061 Peoples R China

This paper is devoted to the issue of computationally efficient and robust nonlinear model predictive control (NMPC) for ship dynamic positioning (DP) systems subjected to input constraints and unknown environmental disturbances. The Laguerre functions, typically applied to the linear systems, are introduced to the constrained NMPC design of the nonlinear DP system to reduce the computational burden. The unscented Kalman filter is adopted to estimate the unknown disturbances and states;thus, the disturbance estimates are utilized as the cancellation signal to achieve robust offset-free control. Simulations of the proposed Laguerre function-based NMPC scheme are implemented and compared with the performance of typical Laguerre function-based linear model predictive control (LMPC) for the DP system. Simulation results well demonstrate the effectiveness, robustness and superiority of the proposed controller.

关键词： Laguerre functions nonlinear model predictive control input constraints ship dynamic positioning

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Constrained nonlinear model predictive control of pH value in wet flue gas desulfurization process

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OPTIMAL control APPLICATIONS & METHODS 2023年第3期44卷 1523-1539页

作者： Li, Xiaoli Dong, Jiawei Wang, Kang Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Beijing Univ Technol Beijing Key Lab Computat Intelligence & Intellige Beijing Peoples R China Beijing Univ Technol Engn Res Ctr Digital Community Beijing Peoples R China

In wet flue gas desulfurization (WFGD) process, the pH value of the absorption tower slurry is a crucial factor to the efficiency of desulfurization system. Aiming at the nonlinearity and large lag of the pH change in WFGD process, a predictive control strategy based on Hammerstein-Wiener inverse model compensation is proposed. During the calculation of optimal control, an anti-model of Wiener nonlinearity unit is adopted to transform the output setting values and sampling values. Similarly in the control process, the controller output is applied to the actual controlled object after inverse transformation of the static nonlinear Hammerstein model. Through the above two inverse transformations, the controller output is identical with the input of linear link in the closed-loop system. In this article, the inverse model compensation method is utilized to transform nonlinear process control into linear system control, avoiding the large computation of nonlinear model optimization. Finally, the feasibility and effectiveness of the proposed scheme are verified by simulation.

关键词： Hammerstein-Wiener model inverse model compensation nonlinear model predictive control wet flue gas desulfurization

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Line-of-sight nonlinear model predictive control for autonomous rendezvous in elliptical orbit

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AEROSPACE SCIENCE AND TECHNOLOGY 2017年第Oct.期69卷 236-243页

作者： Li, Peng Zhu, Zheng H. York Univ Dept Mech Engn 4700 Keele St Toronto ON M3J 1P3 Canada

The paper investigates the trajectory planning and control of autonomous spacecraft rendezvous in the orbital plane with line-of-sight dynamics. The control problem, based on nonlinear model predictive control, is formulated in terms of line-of-sight range and azimuth angle. The state feedback with measurement uncertainties is introduced to form a closed-loop optimal control problem by integration of receding horizon strategy. Furthermore, the control input increment instead of total control input is considered in the cost function to generate a smooth transient response. The formulated nonlinear optimal control problem is then transformed into convex quadratic programming problems over the predictive horizon, leading to a computationally efficient algorithm implementable for spacecraft. The numerical results show that the newly proposed line-of-sight nonlinear model predictive control scheme is able to effectively generate optimized approach trajectories with satisfactory control accuracy and the proposed method is insensitive to the measurement uncertainties. (C) 2017 Elsevier Masson SAS. All rights reserved.

关键词： Spacecraft autonomous rendezvous Line-of-Sight nonlinear model predictive control Quadratic programming Measurement uncertainties

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Aero-engine direct thrust control with nonlinear model predictive control based on linearized deep neural network predictor

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND control ENGINEERING 2020年第3期234卷 330-337页

作者： Zheng, Qiangang Wang, Yong Sun, Fengyong Zhang, Haibo Nanjing Univ Aeronaut & Astronaut Jiangsu Prov Key Lab Aerosp Power Syst Nanjing Peoples R China AECC Aero Engine Control Syst Inst Wuxi Jiangsu Peoples R China

A novel nonlinear model predictive control method for aero-engine direct thrust control is proposed to improve engine response ability and reduce computational complexity of nonlinear model predictive control. The control objective of the proposed method is the thrust directly instead of the measurable parameters. The linearized model based on online sliding window deep neural network is proposed as predictive model. The online sliding window deep neural network has strong fitting capacity for nonlinear object and adopted to fitting the transient process of engine. The back propagation is adopted to obtain linearized model of online sliding window deep neural network, which greatly reduce the calculated amount. The comparison simulations of the popular nonlinear model predictive control based on extended Kalman filter and the proposed one are carried out. The simulation results show that compared with the popular nonlinear model predictive control, the proposed nonlinear model predictive control not only has the better response ability but also has reduced computational complexity greatly, nearly reduce computation time more than 35 ms.

关键词： Aero-engine nonlinear model predictive control online deep neural network direct thrust control

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Slugging attenuation using nonlinear model predictive control in offshore oil production

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JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2018年 165卷 187-198页

作者： Gerevini, Giovani G. Farenzena, Marcelo Trierweiler, Jorge O. Fed Univ Rio Grande do Sul UFRGS Chem Engn Dept Grp Intensificat Modeling Simulat Control & Proc R Engn Luiz EnglertS-NCampus Cent Porto Alegre RS Brazil

The increase in oil production in offshore systems can be achieved by active control, as state in the literature. However, the approach based on linear controllers has performance limitations in real applications, because of valve rate of change, as shown in this paper. As an evolution control approach, we show up the advantages of using a nonlinear model predictive controller (NMPC) by the Local Linearization on the Trajectory (LLT) algorithm, with the Fast Offshore Well model (FOWM) as internal model, together with a first idea for tuning the controller parameters. Through a monovariable pressure control strategy, manipulating the production choke, we observed a potential production increase around 9.0% using NMPC. In addition, the multivariable advantage of NMPC strategy is stressed including the gas lift flow as a second manipulated variable. With this structure, it is possible to decrease the production choke variation in 76% and the oil production variability by 80% compared to monovariable structure, with similar production gain.

关键词： Slug flow Deepwater Offshore crude production nonlinear model predictive control

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Speed Tracking of a Linear Induction Motor-Enumerative nonlinear model predictive control

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IEEE TRANSACTIONS ON control SYSTEMS TECHNOLOGY 2013年第5期21卷 1956-1962页

作者： Thomas, Jean Hansson, Anders Beni Suef Univ Div Automat Control Bani Suwayf 62111 Egypt Linkoping Univ Div Automat Control S-58181 Linkoping Sweden

Direct torque control (DTC) is considered as one of the most efficient techniques for speed and/or position tracking control of induction motor drives. However, this control scheme has several drawbacks: the switching frequency may exceed the maximum allowable switching frequency of the inverters, and the ripples in current and torque, especially at low speed tracking, may be too large. In this brief, we propose a new approach that overcomes these problems. The suggested controller is a model predictive controller, which directly controls the inverter switches. It is easy to implement in real time and it outperforms all previous approaches. Simulation results show that the new approach has as good tracking properties as any other scheme, and that it reduces the average inverter switching frequency about 95% as compared to classical DTC.

关键词： Integer programming inverter linear induction motor nonlinear model predictive control optimal control speed tracking control

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A simulated annealing optimization algorithm based nonlinear model predictive control strategy with application

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EVOLVING SYSTEMS 2021年第1期12卷 225-231页

作者： Mallaiah, M. Rao, K. Rama Venkateswarlu, Ch BV Raju Inst Technol Dept Chem Engn Narsapur India Univ Teknol Brunei Petr & Chem Engn Gadong Brunei

Batch reactors are widely used in the production of fine chemicals, polymers, pharmaceuticals and other specialty products. For certain exothermic reactions, the transient operation of the reactor with respect to small changes in critical parameters like coolant temperature and initial composition of the reactants can lead runaway condition of the reactor. In order to avoid the hazards associated with runaway situations, it is imperative to operate the reactor by means of an efficient controller. This work presents a nonlinear model predictive control (NMPC) strategy based on simulated annealing (SA) for the temperature control of a batch reactor involving a highly exothermic runaway reaction. The efficacy of the proposed strategy is studied through simulation for the temperature control of the reactor in which a highly parametric sensitive exothermic reaction of hydrolysis of acetic anhydride with sulfuric acid as catalyst and acetic acid as a solvent is carried out. The controller is found effective in averting the runaway behavior with the smooth and quick attainment of the desired operating condition. The results demonstrate the better performance of the SA based NMPC over the linear model predictive controller (LMPC).

关键词： Exothermic batch reactor nonlinear model predictive control Runaway reaction Simulated annealing

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