• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.66-75
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• 2008

In this work, we explore the feasibility of roll-pitch-yaw integrated autopilots for high angle-of-attack missiles. An investigation of the aerodynamic characteristics of a surface-to-air missile is presented, which reveals the strong effects of cross coupling between the longitudinal and lateral dynamics. Robust control techniques based on $H_{\infty}$ synthesis are employed to design roll-pitch-yaw integrated autopilots. The performance of the proposed roll-pitch-yaw integrated controller is tested in high-fidelity nonlinear five-degree-of-freedom simulations accounting for kinematic cross-coupling effects between the lateral and longitudinal channels. Against nonlinearity and cross-coupling effects of the missile dynamics, the integrated controller demonstrates superior performance when compared with the controller designed in a decoupled manner.

• Clinical and Experimental Pediatrics
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• v.65 no.5
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• pp.239-249
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• 2022

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model's interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.77-82
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• 2004

This paper presents polar converting logic(PCL) of BTT missiles against slowly moving or stationary targets. A guidance commands expressed in rectangular coordinates must be converted in the form of polar coordinates for BTT control. Since conventional PCL has nonlinear and discontinuous function, the missiles may lose controllability when pitch acceleration command equals to zero. Further, roll coupling may have a serious unstabilizing influence on homing guidance with two gimbals seeker. In this paper, a linear homotopy equation is introduced to improve the controllability and a command following performance at midcourse phase. We also design a PCL which is less sensitive to pitch acceleration command so that it may improve the stability of the homing loop. To substantiate our conclusion, results of the computer simulation have been illustrated.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.401-407
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• 2016

This paper introduces 3-dimensional path planning and guidance including power model for high altitude long endurance (HALE) UAV using solar energy. Dubins curve used in this paper has advantage of being directly available to apply path planning. However, most of the path planning problems using Dubins curve are defined in a two-dimensional plan. So, we used 3-dimensional Dubins path generation algorithm which was studied by Randal W. Beard. The aircraft model which used in this paper does not have an aileron. So we designed lateral controller by using a rudder. And then, we were conducted path tracking simulations by using a nonlinear path tracking algorithm. We generate examples according to altitude conditions. From the path tracking simulation results, we confirm that the path tracking is well on the flight path. Finally, we were modeling the power system of HALE UAVs and conducting path tracking simulation during 48hours. Modeling the amount of power generated by the solar cell through the calculation of the solar energy yield. And, we show the 48hours path tracking simulation results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.5
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• pp.551-557
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• 2014

This paper presents a robust lateral controller for autonomous guidance of a farm tractor in field operations. Although mechanical steering actuators have recently been used for passenger vehicles, the steering actuator of the farm tractor is based on a hydraulic system, resulting in limited bandwidth and a larger time delay. Based on a kinematic tractor model with steering actuator dynamics, a nonlinear control technique called dynamic surface control is applied to design a robust lateral controller that compensates for uncertainty owing to steering actuator and road geometry. Finally, tracking performance and robustness of the proposed controller are validated via commercial tractor simulations, with respect to the time delay of the steering actuator and road geometry (e.g., up and down hills), on a given field with a constant friction coefficient.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.4
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• pp.495-506
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• 2024

In this study, we propose the terrain following algorithm using model predictive control and nonlinear disturbance observer-based backstepping sliding mode controller for an aircraft system. Terrain following is important for military missions because it helps the aircraft avoid detection by the enemy radar. The model predictive control is used to replace the generating trajectory and guidance with the flight path angle constraint. In addition, the aircraft is affected to the parameter uncertainty and unknown disturbance such as wind near the mountainous terrain. Therefore, we suggest the nonlinear disturbance-based backstepping sliding mode control method for the aircraft that has highly nonlinearity to enhance flight path angle tracking performance. Through the numerical simulation, the proposed method showed the better tracking performance than the traditional backstepping method. Furthermore, the proposed method presented the terrain following maneuver maintaining the desired altitude.

• Advances in aircraft and spacecraft science
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• v.7 no.1
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• pp.1-17
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• 2020

In this paper, a new model-based Fault Detection and Diagnosis (FDD) method for an agile supersonic flight vehicle is presented. A nonlinear model, controlled by a classical closed loop controller and proportional navigation guidance in interception scenario, describes the behavior of the vehicle. The proposed FDD method employs the Inertial Navigation System (INS) data and nonlinear dynamic model of the vehicle to inform fins damage to the controller before leading to an undesired performance or mission failure. Broken, burnt, unactuated or not opened control surfaces cause a drastic change in aerodynamic coefficients and consequently in the dynamic model. Therefore, in addition to the changes in the control forces and moments, system dynamics will change too, leading to the failure detection process being encountered with difficulty. To this purpose, an equivalent aerodynamic model is proposed to express the dynamics of the vehicle, and the health of each fin is monitored by the value of a parameter which is estimated using an adaptive robust filter. The proposed method detects and isolates fins damages in a few seconds with good accuracy.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.1
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• pp.87-96
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• 2009

In conventional method, flight model is discribed to differential equation by linealization of nonlinear object motion equation. As state equation from differential equation of moving object, the controller is designed by transfer functions of each module under discrimination of stability criteria. But this conventional method is designed under limitation of nonlinearity from object's shape and speed. In other word, The greater part of guidance/navigation system was satisfied with the result of good performance for normal figure of flight object, not sudden changed flight condition, not high speed. But it is not able to give full play to its ability on flight object which has abnormal figure, sudden changeable motion, high speed. Therefore, in this paper was presented performance analysis of load control model for navigation/guidance system on flying object being uncertainty, non-linear like abnormal figure, sudden changeable motion, high speed and is presented method of trajectory control(controllability) ahead of controllability and stability to achieve flight mission. In other word, this paper shows the first step of Min-design method and flight control model.

• Journal of Korean Association for Spatial Structures
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• v.10 no.2
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• pp.61-68
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• 2010

The collapsing accidents of pipe greenhouses in the farmhouse have been increased duo to heavy snow load. However, the study on exact structure analysis to prevent the collapse of pipe greenhouses is rare and the damage of the farmhouse is annually repeated. The method of existing structure analysis is basically made of linear elastic analysis based on the micro displacement. But the actual stiffness of the pipe greenhouse is significantly weaker than the stiffness of buildings and the load acting on the greenhouses gets to become relatively bigger. It means that the geometry shape of greenhouses changes so that the relation of strain-displacement gets to indicate a nonlinear behavior. Therefore, this study is performed to evaluate the structural safety so as to prevent the collapse of pipe greenhouses, which are the single-span greenhouse(farmhouse guidance shape, G) and multi-span greenhouse(farmhouse supply shape, 1-2W), by performing the large-displacement analysis considering nonlinear effects.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.315-320
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• 2003

This paper presents a control augmentation system (CAS) based on the dynamic model inversion (DMI) architecture for a highly maneuverable aircraft. In the application of DMI not treating actuator dynamics, significant instabilities arise due to limitations on the aircraft inputs, such as actuator time delay based on dynamics and actuator displacement limit. Actuator input saturation usually occurs during high angles of attack maneuvering in low dynamic pressure conditions. The pseudo-control hedging (PCH) algorithm is applied to prevent or delay the instability of the CAS due to a slow actuator or occurrence of actuator saturation. The performance of the proposed CAS with PCH architecture is demonstrated through a nonlinear flight simulation.