The feedforward minimal control synthesis algorithm and its application to the control of shaking-tables

2007 ◽  
Vol 221 (3) ◽  
pp. 423-444 ◽  
Author(s):  
D P Stoten ◽  
N Shimizu
Keyword(s):  
Control Synthesis ◽  
Synthesis Algorithm

The Implementation of the Minimal Control Synthesis Algorithm on a Web Control Problem

1994 ◽  
Vol 208 (1) ◽  
pp. 53-60 ◽  
Author(s):  
D P Stoten ◽  
M G Dye ◽  
M Webb
Keyword(s):  
Closed Loop ◽  
Control Synthesis ◽  
Time Varying ◽  
Closed Loop System ◽  
Synthesis Algorithm ◽  
Time Varying Parameters ◽  
Transport Control ◽  
Adaptive Control Strategy ◽  
Web Control ◽  
Experimental Comparisons

The minimal control synthesis (MCS) algorithm is an adaptive control strategy that requires no prior knowledge of plant dynamic parameters, and yet is guaranteed to provide global asymptotic stability of the closed-loop system. The purpose of this paper is to present MCS as applied to web tension und transport control a class of plant that has highly non-linear dynamics and time-varying parameters. The plant is difficult to control by conventional methods over its full operating range. A typical example and model of such a plant is presented along with the implementation of MCS. Experimental comparisons of MCS with conventional control benchmarks are provided. It will be seen that MCS significantly outperforms the conventional controller.

The error-based minimal control synthesis algorithm with integral action

2003 ◽  
Vol 217 (3) ◽  
pp. 187-201 ◽  
Author(s):  
D P Stoten ◽  
S A Neild
Keyword(s):  
Closed Loop ◽  
Control Synthesis ◽  
Closed Loop System ◽  
Synthesis Algorithm ◽  
The Core ◽  
Gain Term ◽  
Integral Action ◽  
Implementation Studies ◽  
Hyperstability Theory ◽  
Integral Gain

This paper presents a new form of the direct adaptive minimal control synthesis (MCS) algorithm. As its name suggests, the error-based minimal control synthesis with integral action (Er-MCSI) algorithm is solely driven by error signals that are generated within the closed-loop system, and contains an explicit integral gain term. The purpose of this new structure is, respectively, to remove the problem of variable adaptive effort with changes in the operating set point, and to remove gain ‘wind-up’ effects due to plant disturbances and signal offsets. The core of this paper contains a proof of stability for Er-MCSI, based on hyperstability theory, together with supporting simulation and implementation studies.

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