Integrated Guidance and Control of AUVs Using Shrinking Horizon Model Predictive Control

Author(s):  
Charmane Caldwell ◽  
Emmanuel Collins ◽  
Srinivas Palanki
Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3143
Author(s):  
Jongho Park ◽  
Youngil Kim ◽  
Jong-Han Kim

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.


Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4324
Author(s):  
Salvatore Rosario Bassolillo ◽  
Egidio D’Amato ◽  
Immacolata Notaro ◽  
Luciano Blasi ◽  
Massimiliano Mattei

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.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Li Ma ◽  
Jiayuan Shan ◽  
Junhui Liu ◽  
Yan Ding

Considering recurrent optimization process in model predictive control (MPC), the model uncertainties and disturbances terms in the missile’s guidance and control model can degrade recursive feasibility, and there are control mutation problems in common MPC algorithm. This paper presents a disturbance rejection model predictive control algorithm for missile integrated guidance and control (IGC). Firstly, a sliding mode observer (SMDO) is designed to estimate the unknown disturbances caused by target maneuvering. Secondly, the method of optimizing control increment is adopted in MPC to avoid the phenomenon of control mutation in the model calculation. By limiting the control increment in each cycle, it ensures the continuity of the control input. Thirdly, by combining the SMDO and MPC, an IGC algorithm is presented, and the stability of the algorithm is proved by using Lyapunov stability theory. Finally, the simulation results with different impact angles verify the effectiveness of the proposed algorithm for intercepting maneuver target.


Author(s):  
Bin Zhao ◽  
Zhenxin Feng ◽  
Jianguo Guo

The problem of the integrated guidance and control (IGC) design for strap-down missile with the field-of-view (FOV) constraint is solved by using the integral barrier Lyapunov function (iBLF) and the sliding mode control theory. Firstly, the nonlinear and uncertainty state equation with non-strict feedback form for IGC design is derived by using the strap-down decoupling strategy. Secondly, a novel adaptive finite time disturbance observer is proposed to estimate the uncertainties based on an improved adaptive gain super twisting algorithm. Thirdly, the special time-varying sliding variable is designed and the iBLF is employed to handle the problem of FOV constraint. Theoretical derivation and simulation show that the IGC system is globally uniformly ultimately bounded and the FOV angle constraint is also guaranteed not only during the reaching phase but also during the sliding mode phase.


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