Pub Date : 2016-09-01DOI: 10.1109/ROMA.2016.7847809
E. Hasan, Rosdi bin Ibrahim, S. Ali, HassanSabo Miya, Syed Faizan Gilani
A key and critical challenge in Industrial processes is real-time system identification. This has prompted a lot of research efforts towards the development of model based adaptive identification methods. Their key advantage is that system parameters are tuned adaptively and online. This paper proposes online identification of Air Flow Plant using adaptive U-Model. The recently developed model is based on a polynomial structure. It adaptively corresponds to uncertain system parameters to adjust them online. U-Model method has shown promising results in terms of system identification. The proposed method is verified by simulation. Being control oriented in nature, an effective control strategy based upon U-Model can easily be developed.
{"title":"U-Model based online identification of Air Flow Plant","authors":"E. Hasan, Rosdi bin Ibrahim, S. Ali, HassanSabo Miya, Syed Faizan Gilani","doi":"10.1109/ROMA.2016.7847809","DOIUrl":"https://doi.org/10.1109/ROMA.2016.7847809","url":null,"abstract":"A key and critical challenge in Industrial processes is real-time system identification. This has prompted a lot of research efforts towards the development of model based adaptive identification methods. Their key advantage is that system parameters are tuned adaptively and online. This paper proposes online identification of Air Flow Plant using adaptive U-Model. The recently developed model is based on a polynomial structure. It adaptively corresponds to uncertain system parameters to adjust them online. U-Model method has shown promising results in terms of system identification. The proposed method is verified by simulation. Being control oriented in nature, an effective control strategy based upon U-Model can easily be developed.","PeriodicalId":409977,"journal":{"name":"2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115438964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-09-01DOI: 10.1109/ROMA.2016.7847812
Kishore Bingi, R. Ibrahim, M. N. Karsiti, Tran Duc Chung, S. Hassan
pH control plays an important role in a wide range of industrial applications for waste management. The high non-linearity in pH neutralization processes and the uncertainty of the plant dynamics are key challenges that cannot be effectively addressed using PID controllers tuned with conventional methods. Some of the available and quite often tuning methods used for designing PID controllers are Cohen-Coon, Ziegler-Nichols (ZN), and Tyreus-Luyben. To address these problems, particle swarm optimization (PSO) is employed to tune the PID controller for a pH neutralization plant. The PSO algorithm is one of the most powerful methods for resolving non-smooth global optimization problems. In this paper, the mathematical model of pH process is developed taking into consideration of the overall plant's dynamics. The PSO based PID controller is then implemented and evaluated by comparing its performance with that of ZN-PID.
{"title":"Optimal PID control of pH neutralization plant","authors":"Kishore Bingi, R. Ibrahim, M. N. Karsiti, Tran Duc Chung, S. Hassan","doi":"10.1109/ROMA.2016.7847812","DOIUrl":"https://doi.org/10.1109/ROMA.2016.7847812","url":null,"abstract":"pH control plays an important role in a wide range of industrial applications for waste management. The high non-linearity in pH neutralization processes and the uncertainty of the plant dynamics are key challenges that cannot be effectively addressed using PID controllers tuned with conventional methods. Some of the available and quite often tuning methods used for designing PID controllers are Cohen-Coon, Ziegler-Nichols (ZN), and Tyreus-Luyben. To address these problems, particle swarm optimization (PSO) is employed to tune the PID controller for a pH neutralization plant. The PSO algorithm is one of the most powerful methods for resolving non-smooth global optimization problems. In this paper, the mathematical model of pH process is developed taking into consideration of the overall plant's dynamics. The PSO based PID controller is then implemented and evaluated by comparing its performance with that of ZN-PID.","PeriodicalId":409977,"journal":{"name":"2016 2nd IEEE International Symposium on Robotics and Manufacturing Automation (ROMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130171094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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