Open-loop controller

About: Open-loop controller is a research topic. Over the lifetime, 16148 publications have been published within this topic receiving 224014 citations. The topic is also known as: non-feedback controller & open-loop control law.

Linear and nonlinear state-space controllers for magnetic levitation

Abstract: The problem of precisely controlling (within sensor resolution) the height of a steel ball above the ground by levitating it against the force of gravity using an electromagnet is considered. The state variables used to model the system are the ball's position below the magnet, the ball's speed and the current in the electromagnet. Two state-space controllers are compared in terms of their performance in controlling the ball's position. The first controller is based on feedback linearization where a nonlinear state-space transformation along with nonlinear state feedback is used to linearize the system exactly. A linear controller is then used on the resulting system to control the ball's position. As a direct measurement of ball speed is not available, a nonlinear observer with linear error dynamics is used to estimate the speed. The second controller is a standard linear state feedback controller whose design is based on a linear model found by perturbing the nonlinear system model about an operating po...

Min-max feedback model predictive control for distributed control with communication

Abstract: This paper concerns a distributed model predictive control (DMPC) strategy in which each controller views the signals from other subsystems as disturbance inputs in its local model. The DMPC controllers exchange predictions on the bounds of their state trajectories and incorporate this information into their local DMPC problems. They also impose their own predicted state bounds as constraints in subsequent DMPC iterations to guarantee their subsystem satisfies the bounds broadcast to the other controllers. Each controller solves a local min-max problem on each iteration to optimize performance with respect to worst-case disturbances. Parameterized state feedback is introduced into the DMPC formulation to obtain less conservative solutions and predictions. The paper presents sufficient conditions for feasibility and stability. The approach is illustrated with an example.

Minimally invasive surgical system

Abstract: A control system for a minimally invasive surgical system. In one aspect the control system is a distributed system. A control and transform processor receives data from a master arm controller, an instrument controller, an imaging system controller, and a guide tube controller and distributes data received from one controller to the other controllers. The other controllers use the received data, along with received optimization goals, to control associated slave arms in a distributed but coordinated way. In another aspect, the control system is centralized, in which a motion coordinator receives master inputs, sensor inputs from the slave arms, and optimization inputs. The motion coordinator uses the received inputs to output control signals to an instrument, an imaging system, and a guide tube controller.

Swing up control of the Acrobot

Abstract: Investigates the problem of swing up control of the Acrobot, a two-link, underactuated robot that is a useful vehicle to study problems in nonlinear control The author develops a swing up strategy based on partial feedback linearization The algorithm works by creating "unstable zero dynamics" which drives the first link of the Acrobot away from its open loop stable equilibrium toward the inverted position Control is switched to a linear controller, designed to balance the arm about the inverted configuration, whenever the swing up controller moves the Acrobot into the near vertical position Simulation results are presented showing the performance of the system >