Parallel synthesis of robust control systems

Parallel synthesis of robust control systems

Parallel computing is used to evaluate compensator robustness numerically and to automate the design of control systems. Robustness is quantified by Monte Carlo evaluation of the effects of plant-parameter uncertainty, and it is maximized by searching the control-design-parameter space with a genetic algorithm. This design approach requires considerable computation, and parallel computing can r...

Robust Control of Nonlinear Systems Using Model-Error Control Synthesis

A new approach for the robust control of nonlinear systems is presented. This approach employs an optimal real-time nonlinear estimator to determine model error corrections to the control input using a one time-step ahead technique. Control compensation is achieved by using the estimated model error as a signal synthesis adaptive correction to the nominal control input so that maximum performan...

robust control of a high-purity disttilation column using synthesis

A Robust Control Design Technique for Discrete-Time Systems

A robust state feedback design subject to placement of the closed loop eigenvalues in a prescribed region of unit circle is presented. Quantitative measures of robustness and disturbance rejection are investigated. A stochastic optimization algorithm is used to effect trade-off between the free design parameters and to accomplish all the design criteria. A numerical example is given to illustra...

Synthesis of Robust Control Systems under Resource Constraints

We address the problem of synthesizing real-time embedded controllers taking into account constraints deriving form the implementation platform. Specifically, we address the problem of controlling a set of independent systems by using a shared single CPU processor board. Assuming a time-triggered model of computation for control processes and a real-time preemptive scheduling policy, the proble...