Technical Brief

A Discrete Sliding-Mode Guidance Law

[+] Author and Article Information
Di Zhou

Department of Control Science and Engineering,
Harbin Institute of Technology,
Mailbox 327,
Harbin 150001, China
e-mail: zhoud@hit.edu.cn

Sheng Sun

Department of Control System Theory and Simulation,
Beijing Aerospace Automatic Control Institute,
Beijing 100854, China

Jing Yang Zhou

Department of Construction Management,
Curtin University,
Perth 6102, Australia

Kok Lay Teo

Department of Mathematics and Statistics,
Curtin University,
Perth 6102, Australia

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received February 5, 2014; final manuscript received July 7, 2014; published online September 10, 2014. Assoc. Editor: Hashem Ashrafiuon.

J. Dyn. Sys., Meas., Control 137(2), 024501 (Sep 10, 2014) (6 pages) Paper No: DS-14-1062; doi: 10.1115/1.4028038 History: Received February 05, 2014; Revised July 07, 2014

Based on the discrete form of the target-missile relative motion equations in plane, a discrete sliding-mode guidance (DSMG) law is proposed. All previous missile seeker's measurements are used in the design of the DSMG law to estimate the target acceleration such that noises in the seeker's measurements are effectively being smoothened. It is proved that the proposed DSMG law is finite time convergent. Quasi sliding-mode bands of the DSMG law are discussed, and the formula for calculating the terminal miss distances of the missile under the DSMG law are presented. Simulation results from a space interception process verify the effectiveness of the proposed method.

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Grahic Jump Location
Fig. 1

Planar relative motion of missile and target

Grahic Jump Location
Fig. 2

The LOS angular rate

Grahic Jump Location
Fig. 3

The missile acceleration

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Fig. 4

The estimate of target acceleration

Grahic Jump Location
Fig. 5

The LOS angular rate in stochastic environment

Grahic Jump Location
Fig. 6

The estimate of target acceleration in stochastic environment



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