An Optimal Missile Autopilot Design Model

Yong-chao Chen (Electronic Engineering Department, Shijiazhuang Mechanical Engineering College, Shijiazhuang, China), Xin-bao Gao (Electronic Engineering Department, Shijiazhuang Mechanical Engineering College, Shijiazhuang, China), Min Gao (Electronic Engineering Department, Shijiazhuang Mechanical Engineering College, Shijiazhuang, China) and Dan Fang (Electronic Engineering Department, Shijiazhuang Mechanical Engineering College, Shijiazhuang, China)
DOI: 10.4018/IJEIS.2018010106
Available
\$37.50
No Current Special Offers

Abstract

This article describes how one optimal design method is given to the design of missile autopilots. This method profits from an exhaustive method. By this method, the design process of a missile autopilot is simplified, and the design efficiency is improved. In the design process of this method, the performance indexes of autopilot are translated into constraint conditions, and the response speed is translated to an objective function. Thus, the optimal design of missile autopilot is translated into the optimal design of a nonlinear system with multiple constraints. The optimization algorithm is found to be out of controller parameter combinations which can satisfy constrained conditions. Firstly, calculations of the corresponding objective function values. Second, by the extract the optimal combination which has the minimal objective function value.
Article Preview
Top

2. Principle Of Optimal Design

The preconditions of autopilot optimization are that the rise time, overshoot, transient time and steady state error should satisfy the performance indexes (Wang, 2007; Wang, 2006; Shen, 2007). Therefore, we should ascertain the ranges of overshoot and steady state error by empirical values firstly. The optimization objective is minimizing the rise time. And then the optimization design could be regard as solve the optimization problem with multiple constraints and single target.

Suppose overshoot is a percent of steady state value, steady state error is ±b percent of steady state value, transient time is t1, simulation time is T, simulation step size is h, and steady state value is g. Then the sketch of system response with constraint conditions could be shown as Figure 1.

Constraints have been set in every simulation node of system response curve. As shown in Figure 1, there is one constraint in every simulation node from 0s to t1s, and the simulation value should lesser than the constraint value; there are two constraints in every simulation node from t1s to Ts, and the simulation value should between the constraint values. Therefore, the number of constraints is t1/h+2(T- t1) /h.

The simulation time, when the simulation value is rise to 80 percent of steady state value firstly, is defined as the rise time. This rise time is the optimization objective. Then we should find out the control parameters which have the minimum rise time and satisfy the constraint conditions. Thus, the optimal design of missile autopilot is translated to the optimal design of nonlinear system with multiple constraints.

Figure 1.

Sketch of system response and constraints

Top

3. Realization Of Optimal Design

There are many optimum design methods in modern control theory, such as LOG reaction control system optimum design method, synthetic optimum design method. But these methods are difficulty to calculate and realize. So the idea of exhaustion method in classical control theory has been considered in this paper, and one optimization method has been put forward for the design of missile autopilot.

Complete Article List

Search this Journal:
Reset
Volume 18: 4 Issues (2022): Forthcoming, Available for Pre-Order
Volume 17: 4 Issues (2021)
Volume 16: 4 Issues (2020)
Volume 15: 4 Issues (2019)
Volume 14: 4 Issues (2018)
Volume 13: 4 Issues (2017)
Volume 12: 4 Issues (2016)
Volume 11: 4 Issues (2015)
Volume 10: 4 Issues (2014)
Volume 9: 4 Issues (2013)
Volume 8: 4 Issues (2012)
Volume 7: 4 Issues (2011)
Volume 6: 4 Issues (2010)
Volume 5: 4 Issues (2009)
Volume 4: 4 Issues (2008)
Volume 3: 4 Issues (2007)
Volume 2: 4 Issues (2006)
Volume 1: 4 Issues (2005)
View Complete Journal Contents Listing