H∞ Controllers With a PID Structure

1990 ◽  
Vol 112 (3) ◽  
pp. 325-336 ◽  
Author(s):  
M. J. Grimble

A review is given of the new H∞ Observations Weighted (HOW) optimal control law. The conditions under which the H∞ controller has a PID structure are identified and some implications for PID controller design are discussed. The simple form of this H∞ control law makes it easy to analyse and design. Examples are presented of the design procedure which involves the specification of the cost-function weighting transfer functions. The controller may be applied in applications where fast computational procedures are important.

2015 ◽  
Vol 66 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Vojtech Veselý ◽  
Adrian Ilka

Abstract A novel methodology is proposed for robust gain-scheduled PID controller design for uncertain LPV systems. The proposed design procedure is based on the parameter-dependent quadratic stability approach. A new uncertain LPV system model has been introduced in this paper. To access the performance quality the approach of a parameter varying guaranteed cost is used which allowed to reach for different working points desired performance. Numerical examples show the benefit of the proposed method.


2019 ◽  
Vol 70 (6) ◽  
pp. 499-501
Author(s):  
Vojtech Veselý ◽  
Ladislav Körösi

Abstract The paper deals with the problem to obtain robust PID controller design procedure to linear time invariant descriptor uncertain polytopic systems using descriptor system stability theory and H2 criterion approach in the form of quadratic cost function. In the frame of Lyapunov function, H2 quadratic cost function and Bellman-Lyapunov equation the obtained designed novel procedure guarantees the robust properties of closed-loop system with parameter dependent quadratic stability/quadratic stability. In the obtained design procedure, the designer could use controller with different structure like as P, PI, PID, PI-D. For PI-D controllers D-part feedback the designer could choose any available output/state derivative variables of real systems. The effectiveness of the obtained results is demonstrated on the randomly generated examples.


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