An interactive parameter space method for robust performance in mixed sensitivity problems

Besson, V.; Shenton, A.T.

doi:10.1109/9.769389

Cited by 21 publications

(12 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Application to the robust performance problem (4) and use of a more general three term controller along with the PID controller structure is reported in Saeki and Hirayama [33] and Saeki and Kimura [34] where a CAD system for automated computation has also been presented. Similar results have also been reported by Besson and Shenton [29,35] for a slightly more general, second-order controller structure. B .…”

Section: Design For Robust Performancesupporting

confidence: 86%

See 1 more Smart Citation

Links between the parameter space and frequency domain methods of robust control

Güvenç

Ackermann

2001

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

SUMMARYTwo main approaches to robust control are the parametric and frequency domain approaches. The aim of this paper which starts with tutorial sections on both approaches is to compare and establish links between the parameter space method of the parametric approach and frequency domain methods, with special emphasis on the structured singular value (SSV) method. In an effort to combine the useful properties of both approaches, two SSV minimization based design techniques in controller parameter space are presented here. A simple interpretation of real SSV in plant parameter space and its further implications for analysis and design are also presented.

show abstract

Section: Design For Robust Performancesupporting

confidence: 86%

“…The m D SC 51:2, 1.0 and 0.98 regions are shown in Figure 7 for the plant with time delay [35] PðsÞ ¼ …”

Section: Ssv-optimal Design In Parameter Spacementioning

confidence: 99%

Links between the parameter space and frequency domain methods of robust control

Güvenç

Ackermann

2001

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…The second objective is to introduce a design method based on shaping the IMC controller Q(s) to obtain robust performance by minimizing the left-hand side of (4). This loop-shaping approach to achieving robust performance differs from the technique given in [6], which is based on condition (2) and involves shaping L( jω) using the coefficients of cascaded second-order transfer functions forming the controller K(s). Another related approach in [5] incorporates a lowpass filter in Q(s) and selects its cutoff frequency so that (4) is satisfied.…”

Section: (S)g(s))mentioning

confidence: 99%

“…The controller K(s) = 400/(10s + 1) 6 is designed such that the resulting loop gain |L( jω)| shown in Figure 4(a) satisfies the performance constraint at low frequency and the stability robustness constraint at high frequency. However, the rolloff of |L( jω)| at medium frequencies is not steep enough to satisfy the robustness constraint.…”

Section: Example: Loop-shaping Design For a First-order Plantmentioning

confidence: 99%

The fundamental tradeoff between performance and robustness - A new perspective on loop shaping - Classic control revisited part II

2007

IEEE Control Syst.

View full text Add to dashboard Cite

C ontrol systems must fundamentally trade off performance with robustness to plant uncertainty. For example, increasing the controller gain is desirable for improving tracking and disturbance rejection, but only up to a point at which uncertainty in the plant gain can potentially render the closed-loop system unstable. Plant uncertainty arises from the inevitable discrepancy between the true plant and its model. Hence, controller design aims at achieving an acceptable tradeoff between the conflicting goals of tracking or regulation performance versus robustness to plant uncertainty.Gain and phase margins are used in loop-shaping controller design as a measure of robustness. For the loop transfer function L(s) = K(s)G(s), where K(s) is the controller and G(s) is the nominal plant model, which is assumed here to be stable, a large gain margin obtained with a small |L( jω)| means that the control system is robust to gain uncertainty. But this robustness typically comes at the cost of lower tracking accuracy. Thus, a loop-shaping design seeks an acceptable balance between gain and phase margins and tracking performance.For plant models with additive or multiplicative uncertainty, gain and phase margins do not adequately characterize the resulting stability or performance robustness of the feedback control system. For these types of uncertainty, a more detailed frequency domain analysis is needed to characterize the tradeoff between performance and robustness. In this article, only stable plants are considered, and a stable additive plant uncertainty model is used as shown in Figure 1. By stable system, we mean a system that is bounded-input, bounded-output stable or, equivalently, a system that is asymptotically stable and whose transfer function is proper. For closed-loop systems, stable means internally bounded-input, bounded-output stable. To facilitate the discussion, every system represented by a transfer function is assumed to be causal.The performance versus robustness tradeoff is an important aspect of the development of H ∞ control theory during the 1980s [1], [2]. One of the original motivations for H ∞ control theory is to minimize the magnitude of the weighted nominal sensitivity W e (s)S(s),

show abstract

“…This enables a fair comparison to be made which will highlight any differences in robustness and performance. Controller design is carried out using a weighted sensitivity parameter space method [15,16]. The reasons for choosing this method are that it allows design for robust performance in an explicit and non-conservative manner for the unstructured, nonparametric uncertainties and pure time delays that are present in the idle speed control problem.…”

Section: Controller Designmentioning

confidence: 99%

Linear Robust Control of Identified State-Space Non-Linear Inverse Compensated SI Engine

Petridis

Shenton

2002

Inverse Problems in Engineering

Self Cite

View full text Add to dashboard Cite

This paper presents a non-linear inverse compensation methodology based on a technique similar to Horowitz's non-linear quantitative feedback theory. A causal inverse is found based on an identified nonlinear plant model. Linear identification of the non-linear identified inverse compensated system is carried out in order to achieve a reduction in the unstructured uncertainty representation. Subsequent robust control design results in an improvement in robust stability and robust performance over the uncompensated system. Using a parameter space linear robust control design technique, the method is applied to the automotive Spark ignition (SI) engine idle speed control problem and is experimentally validated using an electric dynamometer.

show abstract

An interactive parameter space method for robust performance in mixed sensitivity problems

Cited by 21 publications

References 6 publications

Links between the parameter space and frequency domain methods of robust control

Links between the parameter space and frequency domain methods of robust control

The fundamental tradeoff between performance and robustness - A new perspective on loop shaping - Classic control revisited part II

Linear Robust Control of Identified State-Space Non-Linear Inverse Compensated SI Engine

Contact Info

Product

Resources

About