In this paper the nonlinear model predictive control (NMPC) is used in designing of Adaptive Cruise control (ACC) and Cruise control (CC) systems. An algorithm is proposed to carry out automatic switching between ACC ...
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In this paper the nonlinear model predictive control (NMPC) is used in designing of Adaptive Cruise control (ACC) and Cruise control (CC) systems. An algorithm is proposed to carry out automatic switching between ACC and CC, depending on the situation in front of the vehicle. Also, an algorithm based on MPC equation is devised to obtain the prediction of future reference trajectories corresponding to desired speed and distance. NMPC equation used in this paper is developed based on state-dependent representation of linear models corresponding to the modes of the operation: accelerating-throttle is active and braking-brake is active. The developed automated ACC system is tested in simulation against different scenarios proving good performance of the system. Furthermore, the results of proposed control algorithm based on NMPC methods are compared with a different ACC structure. (C) 2014 Elsevier Ltd. All rights reserved.
The economic performance of an industrial scale semi-batch reactor for biodiesel production via transesterification of used vegetable oils is investigated by simulation using nonlinear model predictive control (NMPC) ...
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The economic performance of an industrial scale semi-batch reactor for biodiesel production via transesterification of used vegetable oils is investigated by simulation using nonlinear model predictive control (NMPC) technology. The objective is to produce biodiesel compliant to the biodiesel standards at the minimum costs. A first-principle model is formulated to describe the dynamics of the reactor mixture temperature and composition. The feed oil and mixture composition are characterized using a pseudo-component approach, and the thermodynamic properties are estimated from group contribution methods. The dynamic model is used by the NMPC framework to predict the optimal control profiles, where a multiple shooting based dynamic optimization problem is solved at every sampling time. Simulation results with the economic performance of an industrial scale semi-batch reactor are presented for control configurations manipulating the methanol feed flow rate and the heat duty. (C) 2013 Elsevier Ltd. All rights reserved.
A nonlinear model predictive controller is designed for a continuous reheating furnace for steel slabs. Based on a first-principles mathematical model, the controller defines local furnace temperatures so that the sla...
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A nonlinear model predictive controller is designed for a continuous reheating furnace for steel slabs. Based on a first-principles mathematical model, the controller defines local furnace temperatures so that the slabs reach their desired final temperatures. The controller is suitable for non-steady-state operating situations and reaching user-defined desired slab temperature profiles. In the control algorithm, a nonlinear unconstrained dynamic optimization problem is solved by the quasi-Newton method. The design of the controller exploits the fact that the considered slab reheating furnace is a continuous production process. Long-term measurement results from an industrial application of the controller demonstrate its reliability and accuracy. (C) 2012 Elsevier Ltd. All rights reserved.
This paper proposes a novel nonlinear model predictive control design method based on the finite time disturbance observer (FTDO) and dynamic control allocation (DCA) algorithm for the near-space interceptor (NSI). Fi...
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This paper proposes a novel nonlinear model predictive control design method based on the finite time disturbance observer (FTDO) and dynamic control allocation (DCA) algorithm for the near-space interceptor (NSI). First, the FTDO is introduced to estimate the mismatched system disturbance. The nonlinear model predictive control scheme based on the estimation value is proposed to obtain the virtual control command, and the mismatched disturbance can be effectively removed from the output channels of the NSI by designing a feed-forward disturbance compensation term with an appropriate compensation gain matrix. Moreover, a new DCA method is given to distribute the above virtual control command among the corresponding actuators (reaction jets and aerodynamic fins). Finally, numerical simulations illustrate that the proposed control scheme can track the command signal with high precision and have strong robustness against the mismatched disturbance.
Path tracking control is one of the essential controls for lateral positioning controls such as collision avoidance and lane keeping and changing. In severe situations in which the tire force reaches its limit, such a...
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Path tracking control is one of the essential controls for lateral positioning controls such as collision avoidance and lane keeping and changing. In severe situations in which the tire force reaches its limit, such as entering a corner at high speed or in a low-friction situation, not only accurate path tracking but also stable driving must be ensured. In this paper, an integrated braking and steering controller for path tracking is proposed in consideration of the road friction limit. In particular, individual tire forces were predicted using the vehicle and the tire models, and the results were directly compared with the road friction. A nonlinear model predictive controller (NMPC) was utilized for constrained optimal control using nonlinearmodels. The proposed controller is verified through vehicle simulators Carsim and MATLAB Simulink. Results show the effectiveness of the proposed controller: it guarantees stable driving and accurate tracking performance.
A dynamic model of a chemical CO2 absorption process with aqueous monoethanolamine (MEA) is presented, validated against experimental data. Based on the validated model, a reduced-order model is developed, suitable fo...
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A dynamic model of a chemical CO2 absorption process with aqueous monoethanolamine (MEA) is presented, validated against experimental data. Based on the validated model, a reduced-order model is developed, suitable for an online optimization control strategy. The objective of the optimization is to enable fast adaptations to changes in operating conditions of the power plant, while minimizing the energy consumption in the operation of the CO2 separation plant. The results indicate that model-based online optimization is a feasible technology for control of CO2 separation systems.
nonlinear model predictive control (NMPC) has become a preferred option particularly for controlling a strongly nonlinear system due to an increase in the availability of powerful cheap computing resources in recent y...
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nonlinear model predictive control (NMPC) has become a preferred option particularly for controlling a strongly nonlinear system due to an increase in the availability of powerful cheap computing resources in recent years. However, there are still some hurdles to widely apply the NMPC algorithm for fast nonlinear dynamic systems. One of the primary challenges is how to quickly solve a set of nonlinear differential model equations and a nonlinear dynamic optimization problem in real time. A large portion of the computational problems arises from gradient vector and Hessian matrix derivations and evaluations. In this paper, the problem has been handled using an advanced symbolic computation tool called SymPy. With the symbolic computation, the complex gradient vector, Hessian matrix, and nonlinear dynamic optimization problem are derived analytically and evaluated with machine accuracy. As the rising need for a higher safety level, autonomous marine surface vehicles have been vastly used for various applications in recent years. It is known that model-free methods such as proportional-integral-derivative and nonlinear sliding mode controls are not sufficient to provide a robust control for a highly nonlinear surface vehicles. In this paper, the developed NMPC algorithm has been adopted to solve the two- dimensional trajectory tracking problem for an autonomous marine surface vehicle.
This letter addresses the task of stabilizing a wheeled unmanned aerial vehicle on a pipe, which is an emerging application in oil and gas facilities for nondestructive measurements. After the derivation of the dynami...
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This letter addresses the task of stabilizing a wheeled unmanned aerial vehicle on a pipe, which is an emerging application in oil and gas facilities for nondestructive measurements. After the derivation of the dynamic model of the system, a discrete-time nonlinear model predictive controller is designed over a finite horizon. The analysis of the asymptotic stability of the designed controller is carried out. Numerical tests show the performance and the robustness of the proposed solution.
Anode hydrogen circulation system with purge valve has become one of the most effective ways for proton exchange membrane fuel cell (PEMFC) to alleviate performance degrada-tion caused by nitrogen permeation and impro...
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Anode hydrogen circulation system with purge valve has become one of the most effective ways for proton exchange membrane fuel cell (PEMFC) to alleviate performance degrada-tion caused by nitrogen permeation and improve the hydrogen utilization rate. However, nonlinearity and multivariable coupling of the system make it difficult for PEMFC to ach-ieve pressure and hydrogen supply synchronous tracking under complex operating con-ditions. To solve the problem, a novel nonlinear model predictive control scheme based on coupling analysis is proposed in this paper. Firstly, coupling characteristics of the hydrogen circulation system and the control pairing of the multivariable system are analyzed based on the relative gain array method. Then a novel control scheme based on an adaptive modelpredictivecontroller and a nonlinear model predictive controller is designed to keep the anode pressure stable and sufficient hydrogen supply, which use nonlinear observers to estimate the internal states online. Finally, the proposed controllers are implemented in control experiments of a 50 kW PEMFC anode hydrogen circulation system. The results demonstrate that the proposed control approach has great dynamic performance, anti -disturbance ability and can maintain a high hydrogen utilization rate under purge opera-tion, current disturbance and uncertain intake pressure.(c) 2022 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
The availability of reliable online moisture content measurements exploiting near-infrared (NIR) spectroscopy and chemometric tools allows the application of online control strategies to a wide range of drying process...
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The availability of reliable online moisture content measurements exploiting near-infrared (NIR) spectroscopy and chemometric tools allows the application of online control strategies to a wide range of drying processes in the pharmaceutical industry. In this paper, drying of particles with a pilot-scale batch fluidized bed dryer (FBD) is studied using a in-line NIR probe. A consolidated phenomenological state-space model of an FBD based on mass and energy balances is calibrated applying a nonlinear least-square identification to experimental data (grey-box modeling). Then, relying on the calibrated model, a nonlinear model predictive controller and a moving horizon state estimator are designed. The objective is to reach a specific particle moisture content setpoint at the end of the drying batch while decreasing cycle time and limiting particle temperature. A penalty term on the energy consumption can also be added to the usual tracking control cost function. Compared to a typical FBD operation in industry (mostly open-loop), it is shown that the drying time and the energy consumption can be efficiently managed on the pilot-scale process while limiting various operation problems like under drying, over drying, or particles overheating.
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