The Joint Control of a Robotic Manipulator in the Presence of Disturbances

Joint angular position control of a robotic manipulator with disturbance caused by improper dynamics modeling

Abstract

Due to improvements in science and technology, the field of robotics is constantly evolving. Robots are increasingly replacing humans in the workplace for convenience. To achieve the highest level of precision, several strategies are used in this work to successfully regulate the joint angular position of robotic manipulators. The need for accurate dynamic modeling and the disruptions that might result from improper modeling are two major ideas covered in this work. In terms of task accuracy or precision, using robotic manipulators rather than people is particularly advantageous. Some activities demand a lot of accuracies and take longer, particularly in the medical industry. The human arm is unable of carrying out those tasks due to wear and tear over time and a lack of accuracy. Therefore, several strategies have been suggested here to regulate the angular position of a robotic manipulator to get over that issue and increase the accuracy of using robotic arms. To solve such issues, In the past, a number of tactics have been used, some of which have shown to be quite effective. The introduction discusses the methods and their experimental or theoretical findings. These methods are effective for particular jobs, however, the majority of them were created for repeated activities, which means that they are ineffective when used in unpredictable environments. Our strategy is to create a model that can operate with extreme precision and be controlled by human signals in every situation. According to the idea, the controlled system should theoretically be able to recognize human body movements and imitate them in real time. There are certain drawbacks to the method, but with time improvements are being made, and the model provided here may be refined into a superior form. The advanced aspect of this approach is that it does not require any heavy computations, making it more practicable. Additionally, it enables us to do rid of the speed sensor that many sophisticated robotic manipulators need to control performance and job efficiency. The technology has enormous value since it would increase precision while removing the tedious and stressful process of training the robotic manipulator to carry out a particular operation, hence reducing human effort. The system will become stable as a result of the outcomes we obtain and has a finite error response to parabolic inputs. Stability enables the system to reach a steady state and maintain it for that specific input even after altering its settings.