{'fraction_non_alphanumeric': 0.015174506828528073, 'fraction_numerical': 0.0, 'mean_word_length': 5.055045871559633, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The Application of Neural Position/Force Control in a Robotised Machining Process

This paper presents an application of a robotic manipulator in a machining process. Due to the specifics of the process and numerous phenomena which are difficult to be modelled, suitable tool for the robot control are neural networks. This work concentrates on the robot control process. A synthesis of a neural position/force control algorithm is presented. The algorithm was tested by simulation and in actual conditions on a laboratory stand. The work presents the experimental results with their comparison with an adaptive method based on the robot’s mathematical model.