Optimal State Convergence Controllers with Graph Communication for Tele-operation

State convergence (SC) theory provides a systematic way to design controllers for tele-operation systems. However, the SC scheme's dependency on model parameters poses a challenge for practical applications. The seamless integration of SC and the active disturbance rejection control (ADRC) theories has partially alleviated this model dependency. However, the dependency of this integrated SC-ADRC approach on environmental parameters is another obstruction to fully realizing the robust operation of SC controllers and its variants such as composite state convergence (CSC) controllers. This research proposal aims to develop novel strategies to robustify the SC and CSC controllers against environmental parameters while adhering to the design procedure of SC theory. This will also pave the way to enable the operation of these controllers in both the free as well as contact motions, which are previously valid in the contact motion only. The proposed research will be carried out in four phases: In the first phase, an adaptive algorithm will be developed to identify the environment parameters based on a computationally efficient neuro-fuzzy network. A family of switching SC-ADRC and CSC ADRC bilateral controllers will then be parameterized with the added information of the identified environment parameters. In the second phase, graph theory will be employed to establish communication among several SC/CSC-equipped master and slave nodes with force reflection ability. It will then be shown that it is indeed possible to synchronize the master and slave nodes in an arbitrary configuration following the lines of enhanced SC theory developed in the first phase. In the third phase, fractional order theory will be employed to further improve the robustness of the proposed bilateral and multilateral SC controllers. The entire problem will be posed as an optimization problem to find the fractional powers for the proposed controllers. In the final phase, the proposed control algorithms will be tested on multi-degrees of freedom robotic systems such as manipulators and bipedal robots. The anticipated new scientific knowledge and technological know-how will be made available to the scientific and industrial communities through publications and technology transfer agreements with industrial partners. Given the increased interest that the Canadian government and companies have in investing in the healthcare sector in areas such as robot-assisted surgical procedures, it is expected that the results of this work will eventually lead to greater local industrial competitiveness in working on intelligent haptic robotic systems.