Robust H∞ Controller Design for Aircraft Lateral Dynamics using Multi-objective Optimization and Genetic Algorithms
نویسندگان
چکیده
Two techniques are combined during the design of an optimal controller: Linear Matrix Inequalities (LMIs) and Multi-objective Genetic Algorithms (MOGAs). In this paper the LMI optimization technique is used to obtain a single controller while MOGA is used to convert the controller design into a multi-objective optimization procedure. The combination of these techniques is proposed in this document and is shown to be advantageous against independent application of the aforementioned techniques. It is also presented how the sensitivity and complementary sensitivity functions are shaped with the weighting functions, while restricting the magnitude of the control signals by adding them as a hard objective in the MOGA approach.
منابع مشابه
Robust optimal multi-objective controller design for vehicle rollover prevention
Robust control design of vehicles addresses the effect of uncertainties on the vehicle’s performance. In present study, the robust optimal multi-objective controller design on a non-linear full vehicle dynamic model with 8-degrees of freedom having parameter with probabilistic uncertainty considering two simultaneous conflicting objective functions has been made to prevent the rollover. The obj...
متن کاملH∞ Controller Design and Fault Detection Method Based on Genetic Algorithms for MIMO System
This paper describes a new procedure to design robust H∞ controller with time domain specifications and a fault detection method for MIMO system. Controller design parameters and fault detection method are calculated solving multi-objective optimization problems which are based on genetic algorithms. Simulations tests are carried out to evaluate our design procedure, and satisfactory simulation...
متن کاملMulti-objective optimization of nanofluid flow in microchannel heat sinks with triangular ribs using CFD and genetic algorithms
Abstract In this paper, multi-objective optimization (MOO) of Al2O3-water nanofluid flow in microchannel heat sinks (MCHS) with triangular ribs is performed using Computational Fluid Dynamics (CFD) techniques and Non-dominated Sorting Genetic Algorithms (NSGA II). At first, nanofluid flow is solved numerically in various MCHS with triangular ribs using CFD techniques. Finally, the CFD data will...
متن کاملPareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms
A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...
متن کاملMulti-objective evolutionary design of robust controllers on the grid
The emerging paradigm of grid computing provides a powerful platform for the solution of complex and computationally expensive problems. An example of this is the multi-objective evolutionary design of robust controllers, where each candidate controller design has to be synthesised and the resulting performance of the compensated system evaluated by computer simulation. This paper introduces a ...
متن کامل