The impact of static output nonlinearities on the control strategies that humans use in command-following tasks |
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| Authors: | Sajad Koushkbaghi Jesse B Hoagg T Michael Seigler |
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| Institution: | 1. The Seventh Research Division, Beihang University, Beijing 100191, PR China;2. The 45th Research Institute, China Electronics Technology Group Corporation, Beijing 100176, China;3. School of Industrial and Information Engineering, Politecnico di Milano, Milan 20133, Italy;1. The School of Information and Control Engineering, Liaoning Shihua University, Fushun 113000, PR China;2. The Institute of Intelligence Science and Engineering, Shenzhen Polytechnic, Shenzhen 518055, PR China;3. National Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Yuquan Campus, Hangzhou Zhejiang 310027, PR China;1. Department of Electrical Engineering, University of Chile, Av. Tupper 2007, Santiago, Chile;2. Departmento de Electricidad, Facultad de Ingeniería, Universidad Teconológica Metropolitana, Av. José Pedro Alessandri 1242, Santiago, Chile;3. Facultad de Ingeniería y Arquitectura, Universidad Central de Chile, Toesca 1783, Santiago, Chile;4. Advanced Mining Technology Center, University of Chile, Av. Tupper 2007, Santiago, Chile;5. Department of Industrial Technologies, University of Santiago of Chile, Av. El Belloto 3735, Santiago, Chile;6. Facultad de Ingeniería y Tecnología, Universidad San Sebastián, Bellavista 7, Santiago 8420524, Chile;7. Escuela de Negocios y Tecnología, Universidad Gabriela Mistral, Av. Ricardo Lyon 1177, Providencia, Santiago, Chile;1. School of Liberal Arts and Sciences, North China Institute of Aerospace Engineering, Langfang 065000, PR China;2. Electronics and Communications Engineering, North China Institute of Aerospace Engineering, Langfang 065000, PR China;3. 283 Company, Second Research Institute of the CASIC, Beijing 100089, PR China;1. Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education and School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China;2. Huatian Engineering & Technology Corporation, MCC, Ma’anshan 243005, China;3. School of Electrical and Information Engineering, Anhui University of Technology, Ma’anshan 243002, China |
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| Abstract: | The results of a human-in-the-loop experiment are used to investigate the control strategies that humans use to interact with nonlinear dynamic systems. Two groups of human subjects interact with a dynamic system and perform a command-following task. The first group interacts with a linear time-invariant (LTI) dynamic system. The second group interacts with a Wiener system, which consists of the same LTI dynamics cascaded with a static output nonlinearity. Both groups exhibit improved performance over the trials, but the average of the linear group’s performance is better on more than three-fourths of the trials. A new nonlinear subsystem identification algorithm is presented and used to identify the feedback and feedforward control strategies used by the subjects in both groups. The identification results for the linear group agree with prior studies suggesting that adaptive feedforward inversion is a primary control strategy used by humans for command-following tasks. The main results of this paper address an open question of whether a similar control strategy is used for nonlinear systems. The identification results for the nonlinear group suggest that those subjects also use adaptive feedforward inversion. However, the static output nonlinearity inhibits the human’s ability to approximate the inverse. |
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