The Future of PID Control

Åström, Karl Johan; Hägglund, Tore

doi:10.1016/s1474-6670(17)38216-2

Cited by 230 publications

(307 citation statements)

References 6 publications

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“…The PI controller is expected to respond appropriately around the tuned parameters, but if the system experiences disturbances that are significantly different the PI controller will not perform optimally [7]. In addition, the PI controller does not take into account uncertainties, such as non-linearities and error in the plant model, therefore restricting its robustness [8].…”

Section: Pid Controllermentioning

confidence: 99%

Evaluation of Control Methods for Thermal Roll Forming of Aerospace Composite Materials.

Land

Sousa

Ratchev

et al. 2016

SAE Int. J. Aerosp.

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With increased demand for composite materials in the aerospace sector there is a requirement for the development of manufacturing processes that enable larger and more complex geometries, whilst ensuring that the functionality and specific properties of the component are maintained. To achieve this, methods such as thermal roll forming are being considered. This method is relatively new to composite forming in the aerospace field, and as such there are currently issues with the formation of part defects during manufacture. Previous work has shown that precise control of the force applied to the composite surface during forming has the potential to prevent the formation of wrinkle defects. In this paper the development of various control strategies that can robustly adapt to different complex geometries are presented and compared within simulated and small scale experimental environments, on varying surface profiles. Results have found that traditional PID control can be utilized, although its robustness under varying conditions reduces performance in situations that are far from the tuned scenario. This causes the PID controller to struggle with geometries containing surfaces with high frequency surface variations. To enable more robust control an H∞ based controller was therefore developed for the thermal roll forming process. Simulated results show that while the individual implementation of both controllers were successful in achieving the desired response, the H∞ based controller was able to perform better across a wider range of desired surface profiles.

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Section: Pid Controllermentioning

confidence: 99%

Evaluation of Control Methods for Thermal Roll Forming of Aerospace Composite Materials.

Land

Sousa

Ratchev

et al. 2016

SAE Int. J. Aerosp.

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“…Therefore, PI structure is preferred rather than only (I) controller. For, the stability in the structure of proportion effect and the integral effect's advantages of decreasing steady state error were combined in PI control [5,6]. In the PI control implementation prepared in this study, the closed cycle Ziegler-Nichols frequency response method was used in the setting of controllers' parameters.…”

Section: Control Of Pmdc Motor With Pi Controllermentioning

confidence: 99%

“…These are expert systems realized as nonlinear adaptive variable structure based on fuzzy logic based, artificial neural networks, slippery mode control, genetic algorithm and conventional control strategies that have PID, PI and PD algorithms [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Effective and Reliable Speed Control of Permanent Magnet DC (PMDC) Motor under Variable Loads

Tuna¹,

Fidan²,

Kocabey³

et al. 2015

Journal of Electrical Engineering and Technology

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-This paper presents the effective and reliable speed control of PMDC motors under variable loads and reference speeds. As is known DC motors are more preferred in industrial practices. This is that, the PMDC motors don't require brush and commutator care and to increase in torque per motor depending on developments in power electronics. In this study, proportional-integral controller (PI) and fuzzy logic controller (FL) have been designed for speed control of PMDC motor. In the design of these controllers, characteristics such as minimum overrun time, response time to the load, settling time and ideal rise time have been taken into consideration for better stability performance. In this design, the best system response was searched by examining the effect of different defuzzification methods onto the fuzzy logic system response. In conclusion, it has been seen that FL controller has a better performance for variable speed-load control of PMDC motor compared to PI controller.

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“…The gradients as in Fig. 5 can easily be derived by considering the explicit formulas for the line segments of the piecewise affine function in (2).…”

Section: Data-based Controller Synthesismentioning

confidence: 99%

“…The control of industrial motion systems is mostly done using linear controllers of the proportional-integral-derivative (PID) type [1,2]. However, it is well-known that many linear control loops suffer from certain inherent performance trade-offs such as the waterbed effect [3,4]: an increase of low-frequency (below the bandwidth) disturbance suppression automatically yields an increase of noise amplification at high frequencies (above the bandwidth).…”

Section: Introductionmentioning

confidence: 99%

Performance optimization of piecewise affine variable-gain controllers for linear motion systems

et al. 2014

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The Future of PID Control

Cited by 230 publications

References 6 publications

Evaluation of Control Methods for Thermal Roll Forming of Aerospace Composite Materials.

Evaluation of Control Methods for Thermal Roll Forming of Aerospace Composite Materials.

Effective and Reliable Speed Control of Permanent Magnet DC (PMDC) Motor under Variable Loads

Performance optimization of piecewise affine variable-gain controllers for linear motion systems

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