Visible to the public Biblio

Filters: Keyword is position control  [Clear All Filters]
2020-11-02
Zhao, Xinghan, Gao, Xiangfei.  2018.  An AI Software Test Method Based on Scene Deductive Approach. 2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C). :14—20.
Artificial intelligence (AI) software has high algorithm complexity, and the scale and dimension of the input and output parameters are high, and the test oracle isn't explicit. These features make a lot of difficulties for the design of test cases. This paper proposes an AI software testing method based on scene deductive approach. It models the input, output parameters and the environment, uses the random algorithm to generate the inputs of the test cases, then use the algorithm of deductive approach to make the software testing automatically, and use the test assertions to verify the results of the test. After description of the theory, this paper uses intelligent tracking car as an example to illustrate the application of this method and the problems needing attention. In the end, the paper describes the shortcoming of this method and the future research directions.
2020-07-24
Voronkov, Oleg Yu..  2019.  Synergetic Synthesis of the Hierarchical Control System of the “Flying Platform”. 2019 III International Conference on Control in Technical Systems (CTS). :23—26.
The work is devoted to the synthesis of an aircraft control system using a synergetic control theory. The paper contains a general description of the apparatus and its control system, a synthesis of control laws, and a computer simulation. The relevance of the work consists in the need to create a vertically take-off aircraft of the “flying platform” type in order to increase the efficiency of rescue operations in disaster zones where helicopters and other modern means can't cope with the task. The scientific novelty of the work consists in the application of synergetic approaches to the development of a hierarchical system for balancing the vehicle spatial position and to the coordinating energy-saving control of electric motors that receive energy from a turbine generator.
2019-12-30
Kubo, Ryogo.  2018.  Detection and Mitigation of False Data Injection Attacks for Secure Interactive Networked Control Systems. 2018 IEEE International Conference on Intelligence and Safety for Robotics (ISR). :7-12.

Cybersecurity in control systems has been actively discussed in recent years. In particular, networked control systems (NCSs) over the Internet are exposed to various types of cyberattacks such as false data injection attacks. This paper proposes a detection and mitigation method of the false data injection attacks in interactive NCSs, i.e., bilateral teleoperation systems. A bilateral teleoperation system exchanges position and force information through the Internet between the master and slave robots. The proposed method utilizes two redundant communication channels for both the master-to-slave and slave-to-master paths. The attacks are detected by a tamper detection observer (TDO) on each of the master and slave sides. The TDO compares the position responses of actual robots and robot models. A path selector on each side chooses the appropriate position and force responses from the responses received through the two communication channels, based on the outputs of the TDO. The proposed method is validated by simulations with attack models.