State observer for a class of nonlinear systems and its application to machine vision

• Published in: IEEE transactions on automatic control Vol. 49; no. 11; pp. 2085 - 2091
• Main Authors: Xinkai Chen, Kano, H.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2004; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptative systems; Adaptive control; Appeals; Applied sciences; Cameras; Charge coupled devices; Computer science; control theory; systems; Control theory. Systems; Dynamical systems; Exact sciences and technology; Linear systems; Machine vision; Nonlinear dynamics; nonlinear system; Nonlinear systems; Observability; Observers; perspective observation; Space charge; state observer; State observers; Stereo vision; Sufficient conditions; Translations; Computer vision; Stereo image processing; Mode control; Sliding mode; Observer; Artificial vision; Non linear control; System identification; Stereopsis; Adaptive control; State estimation; Moving body
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2004.837529

In this note, we consider the state observer problem for a class of nonlinear systems which are usually encountered in the machine vision study. The formulation of the state observer is motivated by the sliding mode methods and adaptive control techniques. The proposed observer is applied to the identification problems of the motion parameters and space position of a moving object by using the perspective observation of a single point. It is clarified that the rotation parameters can be observed by using the observation of one camera, and the position and translation parameters cannot be observed by using one camera and must appeal to stereo vision. Simulation results show that the proposed algorithm is effective.