2,983 research outputs found
Robust shape control in a sendzimir cold-rolling steel mill
The shape control problem for a Sendzimir 20-roll cold rolling steel mill is characterised by operation over a wide range of conditions arising from roll changes, changes in rolling schedules and changes in material gauge, width and hardness. Previous approaches to the problem suggest storing a large number of precompensator matrices to cater for the full range of operating conditions. This paper, on the other hand, attempts to synthesise a controller which is optimally robust to changes in the conditions associated with the rolling cluster, resulting in a reduced storage requirement for the controlling computer. The performance of the robust controller is evaluated via nonlinear simulation
Implementation Of Internal Model Control (IMC) In Continuous Distillation Column.
Distillation columns have been widely used in chemical plants for separation process. The high nonlinearity and dynamic behavior of the column make them hard to control
Proportional-integral-plus (PIP) control of the ALSTOM gasifier problem
Although it is able to exploit the full power of optimal state variable feedback within a non-minimum state-space (NMSS) setting, the proportional-integral-plus (PIP) controller is simple to implement and provides a logical extension of conventional proportional-integral and proportional-integral-derivative (PI/PID) controllers, with additional dynamic feedback and input compensators introduced automatically by the NMSS formulation of the problem when the process is of greater than first order or has appreciable pure time delays. The present paper applies the PIP methodology to the ALSTOM benchmark challenge, which takes the form of a highly coupled multi-variable linear model, representing the gasifier system of an integrated gasification combined cycle (IGCC) power plant. In particular, a straightforwardly tuned discrete-time PIP control system based on a reduced-order backward-shift model of the gasifier is found to yield good control of the benchmark, meeting most of the specified performance requirements at three different operating points
Decoupled Reference Governors for Multi-Input Multi-Output Systems
In this work, a computationally efficient solution for constraint management of square
multi-input multi-output (MIMO) systems is presented. The solution, referred to as
the Decoupled Reference Governor (DRG), maintains the highly-attractive computational
features of scalar reference governors (SRG) compared to Vector Reference
Governor (VRG) and Command Governor (CG). This work focuses on square MIMO
systems that already achieve the desired tracking performance. The goal of DRG is to
enforce output constraints and simultaneously ensure that the degradation to tracking
performance is minimal. DRG is based on decoupling the input-output dynamics
of the system so that every channel of the system can be viewed as an independent
input-output relationship, followed by the deployment of a bank of scalar reference
governors for each decoupled channel. We present a detailed set-theoretic analysis of
DRG, which highlights its main characteristics. A quantitative comparison between
DRG, SRG, and the VRG is also presented in order to illustrate the computational
advantages of DRG. Finally, a distillation process is introduced as an example to
illustrate the applicability of DRG
Application of robust control in unmanned vehicle flight control system design
The robust loop-shaping control methodology is applied in the flight control system
design of the Cranfield A3 Observer unmanned, unstable, catapult launched air vehicle.
Detailed linear models for the full operational flight envelope of the air vehicle are
developed. The nominal and worst-case models are determined using the v-gap metric.
The effect of neglecting subsystems such as actuators and/or computation delays on
modelling uncertainty is determined using the v-gap metric and shown to be significant.
Detailed designs for the longitudinal, lateral, and the combined full dynamics TDF
controllers were carried out. The Hanus command signal conditioning technique is also
implemented to overcome actuator saturation and windup. The robust control system is
then successfully evaluated in the high fidelity 6DOF non-linear simulation to assess its
capability of launch stabilization in extreme cross-wind conditions, control
effectiveness in climb, and navigation precision through the prescribed 3D flight path in
level cruise. Robust performance and stability of the single-point non-scheduled control
law is also demonstrated throughout the full operational flight envelope the air vehicle
is capable of and for all flight phases and beyond, to severe launch conditions, such as
33knots crosswind and exaggerated CG shifts.
The robust TDF control law is finally compared with the classical PMC law where the
actual number of variables to be manipulated manually in the design process are shown
to be much less, due to the scheduling process elimination, although the size of the final
controller was much higher. The robust control law performance superiority is
demonstrated in the non-linear simulation for the full flight envelope and in extreme
flight conditions
Dynamic operability assessment : a mathematical programming approach based on Q-parametrization
Bibliography: pages 197-208.The ability of a process plant to guarantee high product quality, in terms of low variability, is emerging as a defining feature when distinguishing between alternative suppliers. The extent to which this can be achieved is termed a plant's dynamic operability and is a function of both the plant design and the control system design. In the limit, however, the closedloop performance is determined by the properties inherent in the plant. This realization of the interrelationship between a plant design and its achievable closed-loop performance has motivated research toward systematic techniques for screening inherently inferior designs. Pioneering research in the early 1980's identified right-half-plane transmission zeros, time delays, input constraints and model uncertainty as factors that limit the achievable closedloop performance of a process. Quantifying the performance-limiting effect of combinations of these factors has proven to be a challenging problem, as reflected in the literature. It is the aim of this thesis to develop a systematic procedure for dynamic operability assessment in the presence of combinations of performance-limiting factors. The approach adopted in this thesis is based on the Q-parametrization of stabilizing linear feedback controllers and involves posing dynamic operability assessment as a mathematical programming problet? In the proposed formulation, a convex objective function, reflecting a measure of closed-loop performance, is optimized over all stable Q, subject. to a set of constraints on the closed-loop behavior, which for many specifications of interest is convex. A discrete-time formulation is chosen so as to allow for the convenient hand.ling of time delays and time-domain constraints. An important feature of the approach is that, due to the convexity, global optimality is guaranteed. Furthermore, the fact that Q parametrizes all stabilizing linear feedback controllers implies that the performance at the optimum represents the best possible performance for any such controller. The results are thus not biased by controller type or tuning, apart from the requirement that the controller be linear
- …