A hierarchical control architecture, consisting of a high level controller for trajectory tracking, and a control allocation algorithm, is developed and proved to be effective in tracking a desired trajectory while optimizing some cost related to actuator constraints.
The proposed approach takes advantage of the cascade structure of the system to design a hierarchical controller involving a High Level Controller devoted to position control and a Low Level Controller devoted to attitude stabilization.
The low level controller is designed to optimally regulate torque at each wheel based on the control inputs of the high level controller, and distribute required torque between the wheels via actuation system.
A hierarchical control system is designed where a high level controller (supervisor) is responsible for task decision, monitoring states of the vehicle, generating references for low level controllers, etc. and several low level controllers are responsible for attitude and altitude stabilization.
Planning has been traditionally limited to the high level controller of a robot.
A HCS comprises a higher level controller (HLC) and a lower level controller (LLC).
Each lower level controller uses adaptive equivalent consumption minimization strategy (ECMS) for following their velocity profiles, obtained from the higher level controller, in a fuel efficient manner.
The proposed model can be also used as a high level controller for a robotic dextrous hand during learning and execution of grasping tasks.
In designing the high level controller, the complex strip casting dynamics is linearized at an operating point and parameter estimation and uncertainty quantification methods are used.
The first order Sugeno fuzzy inference system is utilized to model the leader robot system and create the high level controller.
Apart from that, the higher level controller of each HEV uses the recuperation information from the lower level controller and provides it the optimal velocity profile by solving its problem in a model predictive control framework.
