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Reentry Flight Controller Design Using Nonlinear Dynamic Inversion

R. R. da Costa, Q. P. Chu, J. A. Mulder
2003 Journal of Spacecraft and Rockets  
The control design is based on nonlinear/linear inversion of the vehicle model and is divided in three phases: nonlinear inversion of the vehicle’s dynamics, linearization and linear inversion of the aerodynamic  ...  For the behavior of the aerodynamic surfaces, the inversion is necessary and consists in the inversion of the nonlinear aerodynamic database.  ... 
doi:10.2514/2.3916 fatcat:tmfmynsqojhnxodoxm37ik6lvq

Distributed H∞ Control of AVs Interacting by Uncertain and Switching Topology in a Platoon

Feng Gao, Dongfang Dang, Qiuxia Hu, Yingdong He
2019 Journal of Advanced Transportation  
After compensating for the powertrain nonlinearities, we model the node dynamics as a linear uncertain system.  ...  Then a numerical method is provided to solve the state feedback controller by using the LMI scheme.  ...  Inverse Vehicle Model. One challenge for control is the salient nonlinearities of powertrain dynamics, which can be linearized by feedback [15] or compensated for by an inverse models [5] .  ... 
doi:10.1155/2019/9723042 fatcat:fploq3srjfduhclr2tbm7wgrwa

Composite Adaptive Internal Model Control and Its Application to Boost Pressure Control of a Turbocharged Gasoline Engine

Zeng Qiu, Mario Santillo, Mrdjan Jankovic, Jing Sun
2015 IEEE Transactions on Control Systems Technology  
The design of the CAIMC assumes that the plant model and its inverse are represented by the first-order linear dynamics.  ...  Internal model control (IMC) explicitly incorporates the plant model and its approximate inverse and offers an intuitive controller structure and calibration procedure.  ...  Another incentive for identifying the inverse directly is that it avoids numerical inversion.  ... 
doi:10.1109/tcst.2015.2414400 fatcat:j7g3qxsbxvaufo2z6hq6yjl2by

Inverse Resource Rational Based Stochastic Driver Behavior Model [article]

Mehmet Ozkan, Yao Ma
2022 arXiv   pre-print
A nonlinear model predictive control (NMPC) with a time-varying horizon approach is used to generate driver-specific trajectories by using the learned distributions of the planning horizon and the cost  ...  The results reveal that the proposed inverse resource rational-based stochastic driver model can address the resource rationality and stochasticity of human driving behaviors in a variety of realistic  ...  by using the nonlinear model predictive control with the time-varying horizon approach in realistic longitudinal driving scenarios.  ... 
arXiv:2207.07088v1 fatcat:ejllfa664nbhtb6cidisymnt7m

Personalized Adaptive Cruise Control and Impacts on Mixed Traffic [article]

Mehmet Ozkan, Yao Ma
2021 arXiv   pre-print
The results reveal that the learned driver model can identify and replicate the personalized driving behaviors accurately and consistently when following the preceding vehicle in a variety of traffic conditions  ...  This paper presents a personalized adaptive cruise control (PACC) design that can learn driver behavior and adaptively control the semi-autonomous vehicle (SAV) in the car-following scenario, and investigates  ...  Nonlinear Model Predictive Control (NMPC) Implementation In this section, the nonlinear model predictive control (NMPC) algorithm is introduced to solve the PACC due to the nonlinearity introduced by the  ... 
arXiv:2103.14705v1 fatcat:24s7yb3zcnfqtocjdfdhueu24u

Robust Control Design for Autonomous Vehicles Using Neural Network-Based Model-Matching Approach

Dániel Fényes, Tamás Hegedus, Balázs Németh, Péter Gáspár
2021 Energies  
The model matching process results in an additional control input, which is computed by a neural network during the operation of the control system.  ...  In the first step, the model matching algorithm is proposed, which can adjust the nonlinear dynamics of the controlled system to a nominal, linear model.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/en14217438 fatcat:d63flt6enrha5bebbuurgpt5ry

A Mental Simulation Approach for Learning Neural-Network Predictive Control (in Self-Driving Cars)

Mauro Da Lio, Riccardo Dona, Gastone Pietro Rosati Papini, Francesco Biral, Henrik Svensson
2020 IEEE Access  
., at a deferred time) to prepare "inverse models" for behavior and control, including for yet hypothetical situations.  ...  The agent is potentially autonomous in exploring the world, making its predictive models, and then exploiting these models for efficient synthesis of control and behaviors carried out offline in a selfcreated  ... 
doi:10.1109/access.2020.3032780 fatcat:4tzdpitfznampobz7fu5q34g4m

Numerical Approach to Inverse Flight Dynamics

Marco Borri, Carlo L. Bottasso, Fabio Montelaghi
1997 Journal of Guidance Control and Dynamics  
Following a suggestion of Thomson and Bradley,” Hess and co-workers*® avoided the numerical difficul- ties of numerical differentiation by recasting the inverse problem of vehicle motion to one of an integration  ...  Although the maneu- ver is of little interest from the point of view of flight mechanics, it represents a valid test case for a numerical approach because it is characterized by large-amplitude variations  ... 
doi:10.2514/2.4106 fatcat:n7sr2nqul5hyzaa42gsek7apa4

SDRE and LQR Controls Comparison Applied in High-Performance Aircraft in a Longitudinal Flight

Guilherme P. Dos Santos, Adriano Kossoski, Jose M. Balthazar, Angelo Marcelo Tusset
2021 International Journal of Robotics and Control Systems  
When applied in flight conditions with an angle of attack above the stall situation and influenced by the gust model, it was demonstrated that the LQR and SDRE controllers were able to smooth the flight  ...  This paper presents the design of the LQR (Linear Quadratic Regulator) and SDRE (State-Dependent Riccati Equation) controllers for the flight control of the F-8 Crusader aircraft considering the nonlinear  ...  The authors in [39] present an evolving neuro-fuzzy controller called PAC (Parsimonious Controller) for micro aerial vehicles considering the presence of a high level of environmental perturbations.  ... 
doi:10.31763/ijrcs.v1i2.329 fatcat:mkpq6dsa2rbfppoqkgibh3nkom

Synchronization of Chaotic Gyros Based on Robust Nonlinear Dynamic Inversion

Inseok Yang, Dongik Lee
2013 Journal of Applied Mathematics  
A robust nonlinear dynamic inversion (RNDI) technique is proposed in order to synchronize the behavior of chaotic gyros subjected to uncertainties such as model mismatches and disturbances.  ...  Gyro is a crucial device that measures and maintains the orientation of a vehicle. By Leipnik and Newton in 1981, chaotic behavior of a gyro under specific conditions was established.  ...  2013-H0401-13-1005) supervized by the National IT Industry Promotion Agency (NIPA).  ... 
doi:10.1155/2013/519796 fatcat:bn7vinznwff2lewknsopf4obca

Effects of control structure on performance for an automotive powertrain with a continuously variable transmission

S. Liu, A.G. Stefanopoulou
2002 IEEE Transactions on Control Systems Technology  
Simulations show that the multivariable strategy improves the system performance because it produces minimum phase (MP) behavior without large transient deviations from the optimal fuel economy operation  ...  We revisit the seminal work by Guzzella and Schmid and show that the control structure that dedicates the throttle actuator to maintaining engine operation at the maximum fuel efficient operating points  ...  It is thus not possible to change the sign of the component of the initial response that contributes to the inverse behavior ( ) by manipulating the sign of the controller .  ... 
doi:10.1109/tcst.2002.801881 fatcat:nxbwvgueufe6tgvebioprmo46e

Neural Network Control for PPDCV Clinker Cooler System

Majid AhmedOleiwi, Zaid Abed Aljasem
2014 International Journal of Computer Applications  
The paper is focused on the possibilities of applying trained artificial neural networks for creating the system inverse models that are used to design inverse control algorithm for non-linear dynamic  ...  The simulation experiment is performed using Matlab and Simulink to show the response of these controllers.  ...  The advantage of used the inverse control by NN is to cancel the nonlinearities in the process and therefore it must be very accurate [1, 2] .  ... 
doi:10.5120/14815-3038 fatcat:opnx4wa6enew5h36cadb7ybqmq

Stochastic control of traffic patterns

Yuri B. Gaididei, Carlos Gorria, Rainer Berkemer, Peter L. Christiansen, Atsushi Kawamoto, Mads Sørensen, Jens Starke
2013 Networks and Heterogeneous Media  
This opens the possibility for the construction of technical tools to control traffic jam formation. 2010 Mathematics Subject Classification.  ...  A stochastic modulation of the safety distance can reduce traffic jams. It is found that the effect of random modulation on congestive flow formation depends on the spatial correlation of the noise.  ...  the Basque Country, Bilbao, for their hospitality.  ... 
doi:10.3934/nhm.2013.8.261 fatcat:52hkkfl4y5aqnf47r5fg45oo3q

The nonlinear computed torque control of a quadrotor

Youssouf Meddahi, K Zemalache Meguenni, Houari Aoued
2020 Indonesian Journal of Electrical Engineering and Computer Science  
<p>This paper work focused on the study of a quadrotor helicopter, the nonlinear behavior of quadrotors requires an advanced stabilizing control of this vehicles.  ...  In order to model the dynamic of the vehicles, kinematics and dynamics modeling of the X4 is presented.  ...  The control of a quadrotor is the principally problem because the nonlinear behavior of quadrotors requires an advanced stabilizing.  ... 
doi:10.11591/ijeecs.v20.i3.pp1221-1229 fatcat:qkrbpxaimbdadmrvhoibmie6rq

Sliding Modes based Nonlinear PID Controller for Quadrotor - Theory and Experiment

Yasser Bouzid, Houria Siguerdidjane, Yasmina Bestaoui
2017 Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics  
Sliding Modes based Nonlinear PID Controller for Quadrotor -Theory and Experiment.  ...  The numerical simulations have shown satisfactory results using nominal model or disturbed one compared to the use of classic sliding modes technique only.  ...  We give a brief explanation of the classic process followed to derive a simplified model that describes the drone's in-flight behavior where more accurate dynamic models may be found as for instance in  ... 
doi:10.5220/0006433402860294 dblp:conf/icinco/BouzidSB17 fatcat:i3dwewmclrggthdrcq5p7b7kwe
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