EFFECTIVE FINITE HORIZON LINEAR-QUADRATIC CONTINUOUS TERMINAL CONTROL

2013 ◽  
Vol 10 (06) ◽  
pp. 1350038 ◽  
Author(s):  
X. XIA ◽  
Z. XU
Keyword(s):  
Matrix Method ◽  
Optimization Problem ◽  
Computation Time ◽  
Finite Horizon ◽  
Terminal Control ◽  
Linear Quadratic ◽  
Sweep Method ◽  
Crucial Point ◽  
Automatic Landing ◽  
Landing Control

An effective algorithm for the finite-horizon linear quadratic continuous terminal control is proposed. It is the combination of existing continuous soft and hard terminal control. We apply the algorithm to the automatic landing control of OH-6A helicopters. Numerical demonstration shows that, whether noise exists or not, the algorithm has less computation time and less feedback gains than existing hard terminal control while generally achieving the same terminal accuracy. The optimization problem which represents the hard terminal control can be addressed by sweep method and transit matrix method. It is also discovered that transit matrix method is a crucial point for improving terminal accuracy.

Accelerated 3D blind separation of convolved mixtures based on the fast iterative shrinkage thresholding algorithm for adaptive multiple subtraction

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. V99-V113 ◽  
Author(s):  
Zhong-Xiao Li ◽  
Zhen-Chun Li
Keyword(s):  
Field Data ◽  
Optimization Problem ◽  
Computational Cost ◽  
Computation Time ◽  
Blind Separation ◽  
L1 Norm ◽  
Norm Minimization ◽  
Iterative Shrinkage ◽  
Thresholding Algorithm ◽  
Iterative Shrinkage Thresholding

After multiple prediction, adaptive multiple subtraction is essential for the success of multiple removal. The 3D blind separation of convolved mixtures (3D BSCM) method, which is effective in conducting adaptive multiple subtraction, needs to solve an optimization problem containing L1-norm minimization constraints on primaries by the iterative reweighted least-squares (IRLS) algorithm. The 3D BSCM method can better separate primaries and multiples than the 1D/2D BSCM method and the method with energy minimization constraints on primaries. However, the 3D BSCM method has high computational cost because the IRLS algorithm achieves nonquadratic optimization with an LS optimization problem solved in each iteration. In general, it is good to have a faster 3D BSCM method. To improve the adaptability of field data processing, the fast iterative shrinkage thresholding algorithm (FISTA) is introduced into the 3D BSCM method. The proximity operator of FISTA can solve the L1-norm minimization problem efficiently. We demonstrate that our FISTA-based 3D BSCM method achieves similar accuracy of estimating primaries as that of the reference IRLS-based 3D BSCM method. Furthermore, our FISTA-based 3D BSCM method reduces computation time by approximately 60% compared with the reference IRLS-based 3D BSCM method in the synthetic and field data examples.

CAT III Autoland Control Laws Design Based on Multi-Objective Optimization

2012 ◽  
Vol 452-453 ◽  
pp. 548-552 ◽  
Author(s):  
Hui Jie Li ◽  
Ling Yu Yang ◽  
Gong Zhang Shen
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Multi Objective Optimization ◽  
Control Laws ◽  
Multi Objective ◽  
Automatic Landing ◽  
Simulation Results ◽  
Free Parameters ◽  
Structure Measurement ◽  
Landing Control

The CAT III longitudinal automatic landing control laws based on multi-objective optimization is discussed. Firstly summarized the CAT III airworthiness criteria and transformed into the specifications of control system. The configuration of the longitudinal automatic landing controllers is proposed secondly and multi-objective optimization is used to tradeoff free parameters of the controllers. The Monte Carlo simulation results show the designed control laws fulfill the CAT III requirements, when there are uncertainties of structure, measurement error and disturbances.

Wind Shear Encountered Landing Control Based on CMACs

2013 ◽  
Vol 284-287 ◽  
pp. 2351-2355 ◽  
Author(s):  
Jih Gau Juang ◽  
Chung Ju Cheng ◽  
Teng Chieh Yang
Keyword(s):  
Intelligent Control ◽  
Adaptive Learning ◽  
Wind Shear ◽  
Learning Rule ◽  
Lyapunov Theory ◽  
Intelligent Control System ◽  
Automatic Landing ◽  
Control Scheme ◽  
Shear Condition ◽  
Landing Control

This paper presents an intelligent control scheme that uses different cerebellar model articulation controllers (CMACs) in aircraft automatic landing control. The proposed intelligent control system can act as an experienced pilot and guide the aircraft landed safely in wind shear condition. Lyapunov theory is applied to obtain adaptive learning rule and stability analysis is also provided. Furthermore, the proposed controllers are implemented in a DSP. The simulations by MatLab are demonstrated.

scholarly journals Finite-Horizon Optimal Tracking Guidance for Aircraft Based on Approximate Dynamic Programming

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Shizheng Wan ◽  
Xiaofei Chang ◽  
Quancheng Li ◽  
Jie Yan
Keyword(s):  
Dynamic Programming ◽  
Approximate Dynamic Programming ◽  
Least Squares Method ◽  
Flight Path ◽  
Finite Horizon ◽  
Dynamic Programming Method ◽  
Reference Trajectory ◽  
Linear Quadratic ◽  
Optimal Tracking ◽  
Flight Path Angle

Referring to the optimal tracking guidance of aircraft, the conventional time based kinematics model is transformed into a downrange based model by independent variable replacement. The deviations of in-flight altitude and flight path angle are penalized and corrected to achieve high precision tracking of reference trajectory. The tracking problem is solved as a linear quadratic regulator applying small perturbation theory, and the approximate dynamic programming method is used to cope with the solving of finite-horizon optimization. An actor-critic structure is established to approximate the optimal tracking controller and minimum cost function. The least squares method and Adam optimization algorithm are adopted to learn the parameters of critic network and actor network, respectively. A boosting trajectory with maximum final velocity is generated by Gauss pseudospectral method for the validation of guidance strategy. The results show that the trained feedback control parameters can effectively resist random wind disturbance, correct the initial altitude and flight path angle deviations, and achieve the goal of following a given trajectory.

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