Philosophy,structure, and examples of relegated control

With the availability of fast and economical microprocessors, effective design of systems that are immune to failure of individual or groups of sensors, actuators, or computational units is feasible. The system can be made tolerant of the failure of individual subsystems, but functions with reduced efficiency.One way to realize this design is to formulate the dynamics of the systems in larger than minimal state spaces, to process the large number of sensory inputs needed, to relegate control functions to different inputs and to provide reliable communication among the subsystems. The imbedding of the state of the system in a larger state space allows the system to have direct access to its minimal state and indirect access by computing it, hence the need for many sensors. The sensors themselves can then measure directly physical parameters of interest or indirectly by providing a processor with measurements from which the processor computes the needed parameter.This paper deals with the concept of relegation of control as a special kind of generalized nonlinear decoupling control.A structure is proposed that relegates control of specific functions to subsets of inputs. The concept is illustrated by a nonlinear robotic example where the control of constraint forces (due to contact, grip, hold, touch, etc.), control of trajectory of motion, control of stability, and control of collision avoidance are relegated to different inputs. The inputs can be the actuator outputs of force and torque applied to the mechanical system or alternatively the inputs to the actuators themselves. Any conflict in fulfilling the four functions is arbitrated at a higher level. Compromises among the functions, priorities of functions over each other and assignments of inputs in primary, secondary, or as lower contributors to function are elaborated, programmed, and stored. This structure allows integration of a certain amount of intelligence in a robotic system at the lowest level.This work was supported in part by the National Science Foundation under Grant ECS-820-1240 and in part by the Department of Electrical Engineering, The Ohio State University, Columbus, Ohio 43210, U.S.A.