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29th Mediterranean Conference on control and Automation (MED)

作者： Asani, Zemerart Ambrosino, Michele Cotorruelo, Andres Garone, Emanuele Vrije Univ Brussel Fac Engn Pl Laan 2 B-1050 Brussels Belgium Univ Libre Bruxelles Dept Control Engn & Syst Anal Brussels Belgium

ISBN: (纸本)9781665422581

The goal of this paper is to present a nonlinear model predictive control scheme for boom cranes, one of the most common type of rotary cranes. In this paper we first present a complete mathematical model for this type of cranes where it is possible to control the two rotations of the crane and the cable length. Then, we design a model predictive control law able to drive the load to a desired position while fulfilling mechanical and safety constraints. We finally compare our controller to a partial feedback linearization coupled with a proportional derivative control with gravity compensation applied to the same model.

关键词： Boom cranes Robotics Motion control Under-actuated systems nonlinear model predictive control

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nonlinear model predictive control of Ultra-supercritical Once Through Boiler-turbine Unit

Nonlinear Model Predictive Control of Ultra-supercritical On...

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Chinese Automation Congress (CAC)

作者： Zhang, Fan Shen, Jiong Li, Yiguo Wu, Xiao Southeast Univ Sch Energy & Environm Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781467371896

The coordinated control system (CCS) plays an import role in the operation of ultra-supercritical once-through boiler-turbine unit. To overcome the operating issues of the CCS, such as multivariable coupling, nonlinearity and large-time delay, a collocation method based nonlinear model predictive control is proposed in this paper. The dynamic optimization problem is transcribed into a finite dimensional nonlinear programming problem and solved using interior point-based large scale nonlinear optimization algorithm. Simulation results on a 1000MW ultra-supercritical once-through boiler-turbine unit show the effectiveness of the proposed approach.

关键词： ultral-supercritical boiler-turbine unit coordinated control system nonlinear model predictive control collocation methods

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nonlinear model predictive control of an Oxy-Fuel Combustion Boiler for Regulating the Excess Oxygen Percentage in the Flue Gas

Nonlinear Model Predictive Control of an Oxy-Fuel Combustion...

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Annual Conference of the SICE

作者： Haryanto, Ade Hong, Keum-Shik Jeon, Chung Hwan Pusan Natl Univ Sch Mech Engn Pusan South Korea

ISBN: (纸本)9784907764302

In this paper, a nonlinear model predictive control (MPC) of a water-tube boiler system with oxy-fuel combustion process in an electric power plant is investigated. The control objectives are to maintain the water and pressure levels in the drum, the steam temperature in the secondary superheater, and the oxygen percentage in the flue gas. Upon the riser and drum models developed by angstrom strom [5], mathematical (nonlinear) models of the primary and secondary superheaters, attemperator and oxy-fuel combustion process are first developed. The introduced seven state variables are the water volume, steam pressure, and steam volume in the drum, vapor fraction in the riser, temperatures in the primary and secondary superheaters, and attemperator temperature. The five input variables are the feed water flow, steam flow, fuel flow, oxygen flow, and spray flow. The four output variables are the steam pressure and water level in the drum, secondary superheater temperature, and excess of oxygen in the flue gas. Since the water and steam volumes in the drum, vapor fraction in the riser, and the temperatures in the primary superheater and attemperator cannot be directly measured, two nonlinear state estimators (extended Kalman filter and particle filter for comparison purpose) are designed. Simulation results of the designed nonlinear MPC algorithm are provided.

关键词： Water-tube boiler nonlinear model predictive control power plant oxy-fuel combustion extended Kalman filter particle filter

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nonlinear model predictive control of Inverted Pendulum Using Iterative Steepest Descent Algorithm 15

Nonlinear Model Predictive Control of Inverted Pendulum Usin...

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15th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Pinyopawasutthi, Petchakrit Banjerdpongchai, David Oishi, Yasuaki Chulalongkorn Univ Fac Engn Dept Elect Engn Intelligent Control Automat Proc Syst iCAPS Res U 254 Phayathai Rd Bangkok 10330 Thailand Nazan Univ Fac Sci & Engn Dept Mechatron Showa Ku Yamazatocho 18 Nagoya Aichi 4668673 Japan

ISBN: (纸本)9781538635551

This paper presents nonlinear model predictive control (NMPC) for nonlinear systems and apply to the inverted pendulum. There is distinction between the optimal control and NMPC. The optimal control aims to minimize the cost function over the finite horizon and applies the control input to the system. On the other hand, NMPC employs the state feedback and updates the control input at each time step. At each sampling time, the control design of NMPC is formulated as a two-point boundary-value (TPBV) problem. When the optimal control law is calculated, only the first control input is applied to the controlled system. We employ an iterative steepest descent algorithm to solve the TPBV problem. Numerical results show comparison between the optimal control and NMPC applied to the inverted pendulum.

关键词： optimal control nonlinear systems nonlinear model predictive control inverted pendulum

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nonlinear model predictive control of Rotation Floating Space Robots for Autonomous Active Debris Removal 22

Nonlinear Model Predictive Control of Rotation Floating Spac...

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22nd International-Federation-of-Automatic-control (IFAC) Symposium on Automatic control in Aerospace (ACA)

作者： Srivastava, Raunak Sah, Roshan Das, Kaushik TCS Res Bengaluru India

ISBN: (纸本)9781713867890

Active Debris removal using robotic manipulators onboard satellites is a promising way of cleaning up the space junk. However, complexities and non-linearities associated with the control of such coupled space-based systems present difficulties in their feasible implementation. Lack of a fixed base arises serious problems in controlling the space manipulators for precision tasks like capture of an orbiting space debris. This paper presents systematic modelling and control approaches for Rotation floating space robots in order to draw a comparison between them while tracking a moving target representing autonomous debris capture. We propose a nonlinear model predictive controller (NMPC) for the space robot in order to design an optimal path that the end-effector can follow while being controlled to capture the target. To the best of the knowledge of the authors, such a controller has not been tested for a Rotation floating space robot before. Further, the current work implements and reviews one of the most commonly used Transpose Jacobian Cartesian (TJC) controller for Rotation floating space robots through the use of Generalized Jacobian Matrix (GJM). The results provide sufficient evidence of the superior performance of the nonlinear model predictive controller over the TJC controller. Finally, the current work also implements the same nonlinear model predictive controller on a more popular state of the art Free floating space robot and compares it with the Rotation floating space robot.

关键词： Rotation Floating Space robot nonlinear model predictive control

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nonlinear model predictive control for Enhanced Path Tracking and Autonomous Drifting Through Direct Yaw Moment control and Rear-Wheel-Steering 16th

Nonlinear Model Predictive Control for Enhanced Path Trackin...

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16th International Symposium on Advanced Vehicle control

作者： Tavo, Gaetano Stanol, Pietro Tavernini, Davide Montanaro, Umberto Tufo, Manuela Fiengo, Giovanni Perlo, Pietro Sorniotti, Aldo Univ Surrey Guildford GU2 7XH Surrey England Univ Sannio I-82100 Benevento Italy Kineton R&D I-80146 Naples Italy Interact Fully Elect VehicleS IFEVS I-10040 Turin Italy Politecn Torino I-10129 Turin Italy

ISBN: (纸本)9783031703942;9783031703928;9783031703911

Path tracking (PT) controllers capable of replicating race driving techniques, such as drifting beyond the limits of handling, have the potential of enhancing active safety in critical conditions. This paper presents a nonlinear model predictive control (NMPC) approach that integrates multiple actuation methods, namely four-wheel-steering, longitudinal tyre force distribution, and direct yaw moment control, to execute drifting when this is beneficial for PT in emergency scenarios. Simulation results of challenging manoeuvres, based on an experimentally validated vehicle model, highlight the substantial PT performance improvements brought by: i) vehicle operation outside the envelope enforced by the current generation of stability controllers;and ii) the integrated control of multiple actuators.

关键词： active safety systems electrified vehicles modelling testing and validation autonomous drifting nonlinear model predictive control

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nonlinear model predictive control in modelica using FMI and Optimization library 16

Nonlinear Model Predictive Control in Modelica using FMI and...

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7th International Workshop on Equation-Based Object-Oriented modeling Languages and Tools (EOOLT)

作者： Seefried, Andreas Pfeiffer, Andreas DLR Oberpfaffenhofen Inst Syst Dynam & Control Oberpfaffenhofen Germany

ISBN: (纸本)9781450342025

In this work-in-progress paper, a currently ongoing development of a generic tool for nonlinear model predictive control is presented. By using an extended interface of FMI 2.0, it is possible to simulate a model that acts as prediction model while the actual system is simulated simultaneously. A trajectory optimization that uses the prediction model provides optimized input control values for the actual system at every sample time. The current work is based on the Optimization library for Dymola and an extended version of FMI 2.0 Co-Simulation. The structure of this approach is explained in detail as well as possible settings and limitations. An example shows the practicability and an outlook for further development is given.

关键词： nonlinear model predictive control optimization FMI FMU Co-Simulation modelica

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nonlinear model predictive control for the industrial BioPower 5 CHP plant 27

Nonlinear model predictive control for the industrial BioPow...

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IEEE 27th International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Kortela, Jukka Aalto Univ Dept Chem & Met Engn Sch Chem Engn PL 16100 FI-00076 Aalto Finland

ISBN: (数字)9781665499965

ISBN: (纸本)9781665499965

In the operation of a biopower plant, a crucial role is played by the residual oxygen content in the flue gas. The flue gas oxygen content, depending on the total air supply and on the fuel composition, provides the information needed to estimate the power developed by the combustion. Therefore, in control systems that operate power plants, the flue gas oxygen content is directly measured and represents a key feedback variable. The novel nonlinear model predictive control developed is based on the model of the BioPower 5 CHP plant which also includes the nonlinear model of the flue gas oxygen content. In addition, the fast response is achieved by regulating primary air flow. To verify the model, experiments were performed at a biopower plant, which utilizes BioGrate combustion technology to enable the use of wet biomass fuels with a moisture content as high as 65%. Then the nonlinear model predictive control was tested in the simulated environment. Finally, the results are presented, analyzed, and discussed.

关键词： NMPC nonlinear model predictive control biomass industrial process

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nonlinear model predictive control of Omnidirectional Mobile Robot Formations

Nonlinear Model Predictive Control of Omnidirectional Mobile...

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10th International Conference on Intelligent Autonomous Systems

作者： Kanjanawanishkul, Kiattisin Li, Xiang Zell, Andreas Univ Tubingen Dept Comp Architecture D-72076 Tubingen Germany

ISBN: (纸本)9781586038878

In this paper we focus on solving a path following problem and keeping a geometrical formation. The problem of formation control is divided into a leader agent subproblem and a follower agent subproblem such that a leader agent follows a given path, while each follower agent tracks a trajectory. estimated by using the leader's information. In this paper, we exploit nonlinear model predictive control (NMPC) as a local control law due to its advantages of taking the robot constraints and future information into account. For the leader agent, we propose to explicitly integrate the rate of progression of a virtual vehicle into the local cost function of NMPC. This strategy can overcome stringent in constraints in a path following problem. Our approach was validated by experiments using three omnidirectional mobile robots.

关键词： Omnidirectional mobile robots multi-robot systems formation control nonlinear model predictive control path-following problems

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nonlinear model predictive control based on hyper chaotic diagonal recurrent neural network

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Journal of Central South University 2022年第1期29卷 197-208页

作者： Samira Johari Mahdi Yaghoobi Hamid RKobravi Department of Control Mashhad BranchIslamic Azad UniversityMashhad ***Iran Department of Biomedical Engineering Mashhad BranchIslamic Azad UniversityMashhad ***Iran

nonlinear model predictive controllers(NMPC)can predict the future behavior of the under-controlled system using a nonlinear predictive ***,an array of hyper chaotic diagonal recurrent neural network(HCDRNN)was proposed for modeling and predicting the behavior of the under-controller nonlinear system in a moving forward *** order to improve the convergence of the parameters of the HCDRNN to improve system’s modeling,the extent of chaos is adjusted using a logistic map in the hidden layer.A novel NMPC based on the HCDRNN array(HCDRNN-NMPC)was proposed that the control signal with the help of an improved gradient descent method was *** controller was used to control a continuous stirred tank reactor(CSTR)with hard-nonlinearities and input constraints,in the presence of uncertainties including external *** results of the simulations show the superior performance of the proposed method in trajectory tracking and disturbance *** convergence and neglectable prediction error of the neural network(NN),guaranteed stability and high tracking performance are the most significant advantages of the proposed scheme.

关键词： nonlinear model predictive control diagonal recurrent neural network chaos theory continuous stirred tank reactor

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