Parallel processing in optimal control

The established design methodology of linear optimal controllers derived off-line is not very well suited due to parameter variations and optimization of performance over a fairly wide and variable work volume of the robot arms. The real-time algorithms derived here are particularly suitable for such drives. The analytical deviations cover four algorithms: state estimation using Kalman theory, optimal feedback using estimated state variables and dynamic programming, adaptive algorithms, and an optimal inferential controller. Implementation of these algorithms on transputers with the specific aim of studying their load torque disturbance abilities is described. These algorithms were applied for real-time control of a small permanent magnet DC motor to validate both the mathematical concepts and their numerical accuracy