TY - GEN

T1 - Robust PIP control of multivariable stochastic systems

AU - Taylor, C. James

AU - Chotai, Arunkumar

AU - Young, Peter

PY - 1997/10/17

Y1 - 1997/10/17

N2 - This paper discusses the development of robust versions of multivariable Non-Minimal State Space (NMSS) design procedures, for the Proportional-Integral-Plus (PIP) control systems previously introduced by Young et al. Robust control design aims to ensure good closed loop performance under difficult conditions, such as model uncertainty and 'worst case' disturbance inputs. In this regard, the practical utility of the PIP controllers are evaluated on two systems, namely a multivariable coupled drive rig and the IFAC93 benchmark. The first of these examples is a laboratory scale plant representing a materials handling system, where control of speed and tension is required; while the latter is a stochastic simulation, whose parameters vary randomly within specified ranges.

AB - This paper discusses the development of robust versions of multivariable Non-Minimal State Space (NMSS) design procedures, for the Proportional-Integral-Plus (PIP) control systems previously introduced by Young et al. Robust control design aims to ensure good closed loop performance under difficult conditions, such as model uncertainty and 'worst case' disturbance inputs. In this regard, the practical utility of the PIP controllers are evaluated on two systems, namely a multivariable coupled drive rig and the IFAC93 benchmark. The first of these examples is a laboratory scale plant representing a materials handling system, where control of speed and tension is required; while the latter is a stochastic simulation, whose parameters vary randomly within specified ranges.

U2 - 10.1049/ic:19971286

DO - 10.1049/ic:19971286

M3 - Conference contribution/Paper

BT - IEE Colloquium on Robust Control, Digest No. 97/380

PB - Institution of Electrical Engineers (IEE)

ER -