Accurate Control of a Pneumatic System using an Innovative Fuzzy Gain-Scheduling Pattern
Due to their high power-to-weight ratio and low cost,
pneumatic actuators are attractive for robotics and automation
applications; however, achieving fast and accurate control of their
position have been known as a complex control problem. A
methodology for obtaining high position accuracy with a linear
pneumatic actuator is presented. During experimentation with a
number of PID classical control approaches over many operations of
the pneumatic system, the need for frequent manual re-tuning of the
controller could not be eliminated. The reason for this problem is
thermal and energy losses inside the cylinder body due to the
complex friction forces developed by the piston displacements.
Although PD controllers performed very well over short periods, it
was necessary in our research project to introduce some form of
automatic gain-scheduling to achieve good long-term performance.
We chose a fuzzy logic system to do this, which proved to be an
easily designed and robust approach. Since the PD approach showed
very good behaviour in terms of position accuracy and settling time,
it was incorporated into a modified form of the 1st order Tagaki-
Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler
uses an input variable which automatically changes the PD
gain values of the controller according to the frequency of repeated
system operations. Performance of the new controller was
significantly improved and the need for manual re-tuning was
eliminated without a decrease in performance. The performance of
the controller operating with the above method is going to be tested
through a high-speed web network (GRID) for research purposes.
[1] Gerard Scorletti, Lauren El Chaoui, "Improved Linear Matrix Inequality
Conditions for Gain Scheduling and Related Control Problems",
International Journal of Robust and Nonlinear Control, issue 8, pp.845-
877, 1998.
[2] Hao Ying, Yongsheng Ding, Shaokan Li, Shihuang Shao, "Comparison
of Necessary Conditions for Typical Tagaki-Sugeno and Mamdani
Fuzzy Systems as Universal Approximators", IEEE Transactions on
Systems, Man and Cybernetics, Vol 29, No 5, September 1999.
[3] Jianfeng Feng, "Effects of Correlated and Synchronised Inputs to Leaky
Integrator Neuronal Model", Computational Neoroscience Laboratory,
The Babraham Institute, Cambridge, UK
[4] King, R., A. Stathaki, "Fuzzy Gain Shceduling Control of Nonlinear
Processes", Department of Electrical and Computer Engineering,
University of Patras, Greece.
[5] Lee, C.-C., "Fuzzy logic in control systems: fuzzy logic controller-parts
1 and 2", IEEE Transactions on Systems, Man, and Cybernetics, Vol. 20,
No. 2, pp 404-435, 1990.
[6] Leith, D., W.E. Leithhead, "Survey of Gain-Scheduling Analysis &
Design" Department of Electronic & Electrical, University of
Strathclyde, Glasgow, Scotland.
[7] L├¡a Garc├¡a-Pérez, José M. Ca├▒as, Mar├¡a C.Garc├¡a-Alegre, Pablo Y├í├▒ez,
Domingo Guinea, ÔÇÿFuzzy control of an electropneumatic actuator-, IEEE
Trans. System, Man and Cybernetics, Jan.1996.
[8] Ming-Chang Shih and Niarn-Liarng Luor, ÔÇÿSelf-Tuning Neural Fuzzy
Control the Position of a Pneumatic Cylinder Under Vertical Load-
,IEEE Trans. on IE, Vol. 39, No. 6, pp. 472-489, 1992.
[9] Moreno Llagostera, "Control of a Pneumatic Servosystem using Fuzzy
Logic", Proceedings of 1st FPNI-PhD Symp. Hamburg 2000, pp 189-
201.
[10] Pauli Viljamaa, "Fuzzy gain Scheduling and Tuning of Multivariable
Fuzzy Control-Methods of Fuzzy Computing in Control Systems", PhD
Thesis, Tampere University of Technology, 2002.
[11] Zhen-Yu Zhao, Masayoshi Tomizuka, "Fuzzy Gain Shceduling of PID
Controllers", IEEE Transactions on Systems, Man and Cybernetics,
vol.23 No5, 1993.
[12] M. J. Mineter, C. H. Jarvis and S. Dowers, "From Stand-alone Programs
Towards GRID-aware Services and Components: a Case Study in
Modelling & Software", Environmental Modelling & Software, vol 18,
issue 4, April 2003, Pages 379-391.
[13] Brian Tierney, William Johnson, Jason Lee and Mary Thompson, " A
Data intensive Distributed Computing Architecture for GRID
Applications", Future Generation Computer Systems, vol 16, Issue 5,
March 2000, p473-481.
[14] Agranat D., "Engineering Web Technologies for Embedded
Applications, Internet Computing", vol 3, No 3, June 1998.
[1] Gerard Scorletti, Lauren El Chaoui, "Improved Linear Matrix Inequality
Conditions for Gain Scheduling and Related Control Problems",
International Journal of Robust and Nonlinear Control, issue 8, pp.845-
877, 1998.
[2] Hao Ying, Yongsheng Ding, Shaokan Li, Shihuang Shao, "Comparison
of Necessary Conditions for Typical Tagaki-Sugeno and Mamdani
Fuzzy Systems as Universal Approximators", IEEE Transactions on
Systems, Man and Cybernetics, Vol 29, No 5, September 1999.
[3] Jianfeng Feng, "Effects of Correlated and Synchronised Inputs to Leaky
Integrator Neuronal Model", Computational Neoroscience Laboratory,
The Babraham Institute, Cambridge, UK
[4] King, R., A. Stathaki, "Fuzzy Gain Shceduling Control of Nonlinear
Processes", Department of Electrical and Computer Engineering,
University of Patras, Greece.
[5] Lee, C.-C., "Fuzzy logic in control systems: fuzzy logic controller-parts
1 and 2", IEEE Transactions on Systems, Man, and Cybernetics, Vol. 20,
No. 2, pp 404-435, 1990.
[6] Leith, D., W.E. Leithhead, "Survey of Gain-Scheduling Analysis &
Design" Department of Electronic & Electrical, University of
Strathclyde, Glasgow, Scotland.
[7] L├¡a Garc├¡a-Pérez, José M. Ca├▒as, Mar├¡a C.Garc├¡a-Alegre, Pablo Y├í├▒ez,
Domingo Guinea, ÔÇÿFuzzy control of an electropneumatic actuator-, IEEE
Trans. System, Man and Cybernetics, Jan.1996.
[8] Ming-Chang Shih and Niarn-Liarng Luor, ÔÇÿSelf-Tuning Neural Fuzzy
Control the Position of a Pneumatic Cylinder Under Vertical Load-
,IEEE Trans. on IE, Vol. 39, No. 6, pp. 472-489, 1992.
[9] Moreno Llagostera, "Control of a Pneumatic Servosystem using Fuzzy
Logic", Proceedings of 1st FPNI-PhD Symp. Hamburg 2000, pp 189-
201.
[10] Pauli Viljamaa, "Fuzzy gain Scheduling and Tuning of Multivariable
Fuzzy Control-Methods of Fuzzy Computing in Control Systems", PhD
Thesis, Tampere University of Technology, 2002.
[11] Zhen-Yu Zhao, Masayoshi Tomizuka, "Fuzzy Gain Shceduling of PID
Controllers", IEEE Transactions on Systems, Man and Cybernetics,
vol.23 No5, 1993.
[12] M. J. Mineter, C. H. Jarvis and S. Dowers, "From Stand-alone Programs
Towards GRID-aware Services and Components: a Case Study in
Modelling & Software", Environmental Modelling & Software, vol 18,
issue 4, April 2003, Pages 379-391.
[13] Brian Tierney, William Johnson, Jason Lee and Mary Thompson, " A
Data intensive Distributed Computing Architecture for GRID
Applications", Future Generation Computer Systems, vol 16, Issue 5,
March 2000, p473-481.
[14] Agranat D., "Engineering Web Technologies for Embedded
Applications, Internet Computing", vol 3, No 3, June 1998.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:55149", author = "M. G. Papoutsidakis and G. Chamilothoris and F. Dailami and N. Larsen and A Pipe", title = "Accurate Control of a Pneumatic System using an Innovative Fuzzy Gain-Scheduling Pattern", abstract = "Due to their high power-to-weight ratio and low cost,
pneumatic actuators are attractive for robotics and automation
applications; however, achieving fast and accurate control of their
position have been known as a complex control problem. A
methodology for obtaining high position accuracy with a linear
pneumatic actuator is presented. During experimentation with a
number of PID classical control approaches over many operations of
the pneumatic system, the need for frequent manual re-tuning of the
controller could not be eliminated. The reason for this problem is
thermal and energy losses inside the cylinder body due to the
complex friction forces developed by the piston displacements.
Although PD controllers performed very well over short periods, it
was necessary in our research project to introduce some form of
automatic gain-scheduling to achieve good long-term performance.
We chose a fuzzy logic system to do this, which proved to be an
easily designed and robust approach. Since the PD approach showed
very good behaviour in terms of position accuracy and settling time,
it was incorporated into a modified form of the 1st order Tagaki-
Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler
uses an input variable which automatically changes the PD
gain values of the controller according to the frequency of repeated
system operations. Performance of the new controller was
significantly improved and the need for manual re-tuning was
eliminated without a decrease in performance. The performance of
the controller operating with the above method is going to be tested
through a high-speed web network (GRID) for research purposes.", keywords = "Fuzzy logic, gain scheduling, leaky integrator,pneumatic actuator.", volume = "1", number = "8", pages = "396-4", }