Model-based synthesis of nonlinear PI and PID controllers

Wright, Raymond A.; Kravaris, Costas

doi:10.1016/s1474-6670(17)58630-9

Cited by 6 publications

(5 citation statements)

References 12 publications

(7 reference statements)

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“…Lee et al 15 proposed nonlinear control systems based on parameterized first-order plus time delay process models. Wright et al 16 proposed nonlinear PI controllers based on a nonlinear firstorder model, whose linearized closed-loop systems are the same as internal model control (IMC) PI control systems for given operating points. Brendel et al 17 proposed nonlinear PI controllers based on the nonlinear first-order plus time delay model.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear PI controllers with output transformations

Lee

Edgar

2015

AIChE Journal

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Well-designed nonlinear proportional-integral (PI) controllers are successful for nonlinear dynamical processes like linear PI controllers are for linear processes. Two nonlinear blocks representing proportional and integral terms can be designed so that the linearized controllers perform the same as linear PI controllers for linearized processes at the given operating points. For some nonlinear processes, nonlinear blocks for nonlinear PI controllers can be singular at some operating points, and control performances can be poor for set points near those points. To mitigate such disadvantages, new nonlinear PI controllers that introduce output transformations are proposed. Several examples are given, showing the performance of the proposed nonlinear PI controllers. V C 2015 American Institute of Chemical Engineers AIChE J, 61: [4264][4265][4266][4267][4268][4269] 2015

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Section: Introductionmentioning

confidence: 99%

Nonlinear PI controllers with output transformations

Lee

Edgar

2015

AIChE Journal

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“…Recently, nonlinear PI controllers have been developed for lower-order or specific nonlinear modes, 4,5 and some modelbased design strategies, based on a reduced-order model in the form of a second-order transfer function, have been available for designing PID controllers. 3 Moreover, Wright et al 6 used the model-based technique to synthesize the nonlinear PI and PID configuration for a specific second-order system. Wu 7 used the feed-back linearization technique to synthesize the novel PI and PID configuration for a reduced-order nonlinear system, and Aguilar et al 8 proposed a robust PID control with augmented state estimation for a reduced-order nonlinear process.…”

Section: Introductionmentioning

confidence: 99%

Output Regulation of Self-Oscillating Biosystems: Model-Based Proportional−Integral/Proportional−Integral−Derivative (PI/PID) Control Approaches

Wu¹,

Chang²

2007

Ind. Eng. Chem. Res.

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The output regulation design of two bioreactor systems in the presence of self-oscillating behavior and inlet disturbances is addressed. By virtue of linearization, transformation, tuning parametrization, and some geometric control techniques, explicit formulations of nonlinear proportional−integral (PI) and proportional−integral−derivative (PID) controllers are obtained. For the prescribed second-order nonlinear system, the model-based PI controller connected to a linear transformation-based observer is developed. For the general class of third-order nonlinear systems, a PID-type feed-forward/feed-back controller that is connected to parametrized tracking modes is constructed. Using the numerical approximation for the reconstruction of equilibrium manifold, the simplified model-based PID control can be easily implemented. Finally, closed-loop simulations show the satisfactory output regulation performances.

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“…There has been some research effort toward incorporating nonlinear control tools in the design of PID controllers. For example, in Wright et al17 it is shown that controllers resulting from nonlinear model–based control theory can be put in a form that looks like the PI or PID controllers for first and second‐order systems. Other examples include Benaskeur and Desbiens,18 in whose work adaptive PID controllers are designed using a backstepping procedure, and Chang et al,19 where a self‐tuning PID controller is derived using Lyapunov techniques.…”

Section: Introductionmentioning

confidence: 99%