An optimization-based anti-windup design for MIMO control systems

Chen, Chih-Yuan; Perng, Ming-Hwei

doi:10.1080/002071798222730

Cited by 8 publications

(10 citation statements)

References 9 publications

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“…To ensure a graceful performance degradation in the presence of input saturation, a particular choice of Q 1 and possibly an additional nonlinear element in the form of directionality compensator is often incorporated into the controller as shown in Figure 4. [1][2][3]11,12,21,22,24,27 In this section, a brief review of some of the existing directionality compensator designs is presented within the IMC framework.…”

Section: Directionality Compensators For Multivariable Imcmentioning

confidence: 99%

“…The concept of directional preservation has been shown to be beneficial for some class of constrained multivariable control problems. 1,3,12 A number of optimization based conditioning techniques (OCTs) have also been proposed in the literature. [20][21][22] All these are extensions of the conditioning techniques originally discussed in Ref.…”

Section: Directionality Compensators For Multivariable Imcmentioning

confidence: 99%

“…Control design for processes under input constraints such as actuator saturation nonlinearities has been widely studied either from a antiwindup design approach [1][2][3][4][5][6] or from a model predictive control (MPC) perspective. [7][8][9][10] For multivariable or multi-input multioutput (MIMO) systems, the presence of control input saturation introduces additional problems due to directional change in control action also known as process directionality 11 alongside the widely known controller windup phenomenon.…”

Section: Introductionmentioning

confidence: 99%

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Internal model control design for input‐constrained multivariable processes

Adegbege

Heath

2011

AIChE Journal

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Multivariable plants under input constraints such as actuator saturation are liable to performance deterioration due to control windup and directionality change. A twostage internal model control (IMC) antiwindup design for open loop stable plants is presented. The design is based on the solution of two low-order quadratic programs at each time step, which addresses both transient and steady-state behaviors of the system. For analyzing the robust stability of such systems against any infinity-norm bounded uncertainty, stability test have also been developed. In particular, we note that the controller input-output mappings satisfy certain integral quadratic constraints. Simulated examples show that the two-stage IMC has superior performance when compared with other existing optimization-based antiwindup methods. The stability test is illustrated for a plant with left matrix fraction uncertainty. A scenario where the proposed two-stage IMC competes favorably with a long prediction horizon model predictive control is described.

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Section: Directionality Compensators For Multivariable Imcmentioning

confidence: 99%

Section: Directionality Compensators For Multivariable Imcmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Internal model control design for input‐constrained multivariable processes

Adegbege

Heath

2011

AIChE Journal

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“…[9], [10], [11], [12]). In directionality compensation the controller requires an online solution of a low-order quadratic program at each time step [4], [5], [13], [6], [14]. The resulting controller structure provides a framework for combining the optimality of a convex online optimization with the efficiency of convex offline synthesis of conventional anti-windup at moderate computational overhead.…”

Section: Introductionmentioning

confidence: 99%

Robust synthesis for directionality compensation

Adegbege¹,

Heath

2016

IET Control Theory & Applications

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We develop new robust synthesis procedures for directionality compensation for linear exponentially stable multivariable plants incorporating both plant uncertainties and input saturations. The control structure is similar to those of anti-windup controls but requires the online solution of a low-order convex optimization. The condition for the existence of a compensator can be expressed as a feasibility problem involving a set of linear matrix inequalities (LMIs). We demonstrate the effectiveness of the design compared to several schemes using a highly ill-conditioned benchmark simulation example.

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“…This approach is restricted to a class of control problems and may not necessarily be optimal. Other optimization based schemes have been suggested (Hanus and Kinnaert, 1989;Walgama and Sternby, 1993;Peng et al, 1998;Chen and Perng, 1998;Soroush and Valluri, 1999). While these schemes offer optimal dynamic behaviour, their performances deteriorate significantly in steady state especially when the constraints are active.…”

Section: Introductionmentioning

confidence: 99%