Revisiting the Ziegler–Nichols step response method for PID control

Hägglund, Tore; Åström, Karl Johan

doi:10.1016/j.jprocont.2004.01.002

Cited by 796 publications

(345 citation statements)

References 16 publications

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“…From another point of view, or according to the attention paid to improving control performance ( (Åström & Hagglund, 2004), (Heertjes et al, 2009) , (Sekara et al, 2009)), the tuning methods can be summarized as follows.…”

Section: The Methods Based On Improving the Control Performancementioning

confidence: 99%

The New Design Strategy on PID Controllers

Wang¹

2012

PID Controller Design Approaches - Theory, Tuning and Application to Frontier Areas

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Section: The Methods Based On Improving the Control Performancementioning

confidence: 99%

The New Design Strategy on PID Controllers

Wang¹

2012

PID Controller Design Approaches - Theory, Tuning and Application to Frontier Areas

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“…The first one regards the design of a PID controller based on Ziegler-Nichols tuning formula (Xue et al, 2007). Ziegler and Nichols presented two methods: the step response method and the frequency response method (Astrom and Hagglund, 2004). The first method is presented in this work and it is applied to three different plants.…”

Section: Jcsmentioning

confidence: 99%

Optimal Control Algorithms for Second Order Systems

Pelusi¹

2013

Journal of Computer Science

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Proportional Integral Derivative (PID) controllers are widely used in industrial processes for their simplicity and robustness. The main application problems are the tuning of PID parameters to obtain good settling time, rise time and overshoot. The challenge is to improve the timing parameters to achieve optimal control performances. Remarkable findings are obtained through the use of Artificial Intelligence techniques as Fuzzy Logic, Genetic Algorithms and Neural Networks. The combination of these theories can give good results in terms of settling time, rise time and overshoot. In this study, suitable controllers able of improving timing performance of second order plants are proposed. The results show that the PID controller has good overshoot values and shows optimal robustness. The genetic-fuzzy controller gives a good value of settling time and a very good overshoot value. The neural-fuzzy controller gives the best timing parameters improving the control performances of the others two approaches. Further improvements are achieved designing a real-time optimization algorithm which works on a genetic-neuro-fuzzy controller.

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“…The structure of the PID controller structure has been applied widely (Gao, 2002;Astrom and Hagglund, 2004;Hanafi, 2010). To perform suspension travel regulation, the suspension travel reference signal, R i is set to zero so that the error between the reference and the suspension travel tends to zero as t→∞ (Gao, 2002).…”

Section: Pid Suspension Travel Control Loop Designmentioning

confidence: 99%

Proportional-integral-derivative control of nonlinear half-car electro-hydraulic suspension systems

Ekoru

Pedro

2013

J. Zhejiang Univ. Sci. A

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This paper presents the development of a proportional-integral-derivative (PID)-based control method for application to active vehicle suspension systems (AVSS). This method uses an inner PID hydraulic actuator force control loop, in combination with an outer PID suspension travel control loop, to control a nonlinear half-car AVSS. Robustness to model uncertainty in the form of variation in suspension damping is tested, comparing performance of the AVSS with a passive vehicle suspension system (PVSS), with similar model parameters. Spectral analysis of suspension system model output data, obtained by performing a road input disturbance frequency sweep, provides frequency response plots for both nonlinear vehicle suspension systems and time domain vehicle responses to a sinusoidal road input disturbance on a smooth road. The results show the greater robustness of the AVSS over the PVSS to parametric uncertainty in the frequency and time domains.

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Revisiting the Ziegler–Nichols step response method for PID control

Cited by 796 publications

References 16 publications

The New Design Strategy on PID Controllers

The New Design Strategy on PID Controllers

Optimal Control Algorithms for Second Order Systems

Proportional-integral-derivative control of nonlinear half-car electro-hydraulic suspension systems

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