scholarly journals Integrated Guidance and Control Using Model Predictive Control with Flight Path Angle Prediction against Pull-Up Maneuvering Target

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3143
Author(s):  
Jongho Park ◽  
Youngil Kim ◽  
Jong-Han Kim
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Flight Path ◽  
Actuator Dynamics ◽  
Guidance And Control ◽  
Maneuvering Target ◽  
Flight Path Angle ◽  
Short Period ◽  
Integrated Guidance And Control ◽  
And Control

Integrated guidance and control using model predictive control against a maneuvering target is proposed. Equations of motion for terminal homing are developed with the consideration of short-period dynamics as well as actuator dynamics of a missile. The convex optimization problem is solved considering inequality constraints that consist of acceleration and look angle limits. A discrete-time extended Kalman filter is used to estimate the position of the target with a look angle as a measurement. This is utilized to form a flight-path angle of the target, and polynomial fitting is applied for prediction. Numerical simulation including a Monte Carlo simulation is performed to verify the performance of the proposed algorithm.

Integrated guidance and control of interceptors with impact angle constraint against a high-speed maneuvering target

2019 ◽  
Vol 233 (14) ◽  
pp. 5192-5204
Author(s):  
Guanjie Hu ◽  
Jianguo Guo ◽  
Jun Zhou
Keyword(s):  
Control System ◽  
High Speed ◽  
Control Method ◽  
Impact Angle ◽  
Adaptive Sliding Mode Control ◽  
Guidance And Control ◽  
Maneuvering Target ◽  
Integrated Guidance And Control ◽  
And Control ◽  
Impact Angle Constraint

An integrated guidance and control method is investigated for interceptors with impact angle constraint against a high-speed maneuvering target. Firstly, a new control-oriented model with impact angle constraint of the integrated guidance and control system is built in the pitch plane by combining the engagement kinematics and missile dynamics model between the interceptor and target. Secondly, the flight path angle of the target is estimated by extended Kalman filter in order to transform the terminal impact angle constraint into the terminal line-of-sight angle constraint. Thirdly, a nonlinear adaptive sliding mode control law of the integrated guidance and control system is designed in order to directly obtain the rudder deflection command, which eliminates time delay caused by the traditional backstepping control method. Then the Lyapunov stability theory is used to prove the stability of the whole closed-loop integrated guidance and control system. Finally, the simulation results confirm that the integrated guidance and control method proposed in this paper can effectively improve the interception performance of the interceptor to a high-speed maneuvering target.

scholarly journals Decentralized Mesh-Based Model Predictive Control for Swarms of UAVs

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4324
Author(s):  
Salvatore Rosario Bassolillo ◽  
Egidio D’Amato ◽  
Immacolata Notaro ◽  
Luciano Blasi ◽  
Massimiliano Mattei
Keyword(s):  
Model Predictive Control ◽  
Unmanned Aerial Vehicles ◽  
Predictive Control ◽  
Control Strategy ◽  
Target Area ◽  
Guidance And Control ◽  
Aerial Vehicles ◽  
Control Scheme ◽  
And Control ◽  
Numerical Simulator

This paper deals with the design of a decentralized guidance and control strategy for a swarm of unmanned aerial vehicles (UAVs), with the objective of maintaining a given connection topology with assigned mutual distances while flying to a target area. In the absence of obstacles, the assigned topology, based on an extended Delaunay triangulation concept, implements regular and connected formation shapes. In the presence of obstacles, this technique is combined with a model predictive control (MPC) that allows forming independent sub-swarms optimizing the formation spreading to avoid obstacles and collisions between neighboring vehicles. A custom numerical simulator was developed in a Matlab/Simulink environment to prove the effectiveness of the proposed guidance and control scheme in several 2D operational scenarios with obstacles of different sizes and increasing number of aircraft.

scholarly journals Neural Extended State Observer Based Intelligent Integrated Guidance and Control for Hypersonic Flight

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2605
Author(s):  
Liang Wang ◽  
Ke Peng ◽  
Weihua Zhang ◽  
Donghui Wang
Keyword(s):  
State Observer ◽  
Lyapunov Theory ◽  
Extended State Observer ◽  
Control Surface ◽  
Extended State ◽  
Actuator Dynamics ◽  
Guidance And Control ◽  
Hypersonic Flight ◽  
Integrated Guidance And Control ◽  
And Control

Near-pace hypersonic flight has great potential in civil and military use due to its high speed and low cost. To optimize the design and improve the robustness, this paper focuses on the integrated guidance and control (IGC) design with nonlinear actuator dynamics in the terminal phase of hypersonic flight. Firstly, a nonlinear integrated guidance and control model is developed with saturated control surface deflection, and third-order actuator dynamics is considered. Secondly, a neural network is introduced using an extended state observer (ESO) design to estimate the complex model uncertainty, nonlinearity and disturbance. Thirdly, a command-filtered back-stepping controller is designed with flexible designed sliding surfaces to improve the terminal performance. In this process, hybrid command filters are implemented to avoid the influences of disturbances and repetitive derivation, meanwhile solving the problem of unknown control direction caused by nonlinear saturation. The stability of the closed-loop system is proved by the Lyapunov theory, and the controller parameters can be set according to the relevant remarks. Finally, a series of numerical simulations are presented to show the feasibility and validity of the proposed IGC scheme.

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