Modelling and Control of Nonlinear Processes

فهرست عناوین اصلی در این پاورپوینت

فهرست عناوین اصلی در این پاورپوینت

● Modelling and Control of Nonlinear Processes
● Outline
● Nonlinear Process Example 1
● Nonlinear Process Example 2
● Nonlinear Control
● Empirical Modelling
● 1st Order Volterra Series
● Volterra Series Model
● Identify Volterra Kernels
● Volterra Series Model
● State-affine Model
● Nonlinearity Uncertainty
● Results 1 (modelling)
● Conclusions 1 (modelling)
● G-S PI Design
● Traditional Gain-Scheduling
● G-S PI Design
● Closed-loop System: APS
● Uncertain Parameter
● Robust Stability
● Robust Performance
● Robust Control Design
● Results 2 (Linear PI)
● Results 2 (G-S PI RS)
● Results 2 (G-S PI RP)
● Results 2 (PI)
● Conclusions 2 (Control)
● Conclusions
● Application
● Unconstrained MPC
● MPC Design Parameters
● State-space MPC
● Robust G-S MPC
● Outline
● Nonlinear CSTR
● Results (1)
● Conclusions (1)
● Results (2)
● Conclusions (2)
● Traditional G-S Design

نوع زبان: انگلیسی حجم: 1.03 مگا بایت
نوع فایل: اسلاید پاورپوینت تعداد اسلایدها: 53 صفحه
سطح مطلب: نامشخص پسوند فایل: ppt
گروه موضوعی: زمان استخراج مطلب: 2019/06/05 10:09:36

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عبارات مهم استفاده شده در این مطلب

عبارات مهم استفاده شده در این مطلب

model, ., control, process, nonlinear, controller, series, volterra, pi, affine, state, modelling,

توجه: این مطلب در تاریخ 2019/06/05 10:09:36 به صورت خودکار از فضای وب آشکار توسط موتور جستجوی پاورپوینت جمع آوری شده است و در صورت اعلام عدم رضایت تهیه کننده ی آن، طبق قوانین سایت از روی وب گاه حذف خواهد شد. این مطلب از وب سایت زیر استخراج شده است و مسئولیت انتشار آن با منبع اصلی است.

http://www.eng.uwaterloo.ca/~hbudman/bangkokgs.ppt

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عبارات پرتکرار و مهم در این اسلاید عبارتند از: model, ., control, process, nonlinear, controller, series, volterra, pi, affine, state, modelling,

مشاهده محتوای متنیِ این اسلاید ppt

مشاهده محتوای متنیِ این اسلاید ppt

modelling and control of nonlinear processes jianying meg gao and hector budman department of chemical engineering university of waterloo hello everyone welcome to my presentation today. first i would like to thank you for the invitation to come for a visit at the company. and also for the chance to present part of my phd work to you. i have been working in the field of process control and as you know process control can be very complex in terms of all the mathematics and theories so today i will try to reduce the amount of math and try to make it understandable to everyone. if there are any questions during my talk please feel free to interrupt me and ask me or i can address the questions at the end of my talk. outline motivation nonlinear process examples two major difficulties modelling and control empirical modelling volterra series state affine robust control robust stability rs and robust performance rp proportional integral pi control gain scheduling pi g s pi results and conclusions continuous stirred tank reactor cstr future application motivation modelling volterra series state affine control g s pi rs rp nonlinear process example ۱ fed batch bioreactor mass balance linear process constant motivation modelling volterra series state affine control g s pi rs rp nonlinear process monod output input many processes are nonlinear in both chemical industry and biochemical industry. for example a chemical process is nonlinear because the specific rate is an arrhenious function of t for a biochemical process the growth rate depends on the specific growth rate if the process follows monod kinetics it is … fed batch culture may benefit from active process control. glucose feed rate can be controlled by measuring glucose concentration in the medium or the cer using a feedback controller. nonlinear process example ۲ continuous stirred tank reactor cstr mass balance linear process constant nonlinear process arrhenius motivation modelling volterra series state affine control g s pi rs rp here i am giving an example of a nonlinear process a cstr. pure a comes in and under a ۱st order exothermal reaction a is reacted to produce b and a mixture of a and b come out of the reactor. a cooling jacket is used to remove the heat generated during the reaction and keep the reaction t at the desired value for a desired reaction rate so a is only a small portion in the mixture coming out so the control objective is to maintain t by controlling the cooling water tc. our case study example. nonlinear control ۱st difficulty simple accurate model accurate the model gives a good data fit simple the model structure is simple to apply for control purpose ۲nd difficulty model is never perfect uncertainty model plant mismatch controllers are desired to be robust to model uncertainty robust control takes into account uncertainty motivation modelling volterra series state affine control g s pi rs rp for these control problems there is a strong motivation apply nonlinear controllers. but there are two major difficulties in designing nonlinear controllers the objective of my phd project is to deal with these two problems. first it is desired to obtain a good simple model of the processes under study. different techniques such as volterra series or nonlinear auto regressive moving average models narma are being evaluated to identify reduced order models of the process. the other major difficulty is that models of systems are always inaccurate. control systems which are based on process models have to be designed to deal with this model mismatch. this research deals with the application of robust control theory to advanced control techniques such as gain scheduling control proportional integral pi control and model predictive control mpc . methods for quantifying the model uncertainty from experimental data are studied. so the robust control approach use in our work can be understood in this way. first a nonlinear model is obtained which gives a very good fit with the actual nonlinear process but it is very difficult to base the controller design directly on this model but the model can be divided into two parts the linear part and a nonlinear part which is treated as uncertainty. so robust control approach can be applied. by doing this we have designed a controller which can be applied to a family of models. empirical modelling e y y inlet concentration controller process measurement soft sensor model u motivation modelling volterra series state affine control g s pi rs rp v type first principles model empirical model how mass energy balance input output data choose difficult complex easy in general design of high performance controllers requires accurate mathematical models of the nonlinear processes to be regulated. two types of nonlinear models may be considered ۱ first principle models i.e. models based on mass and energy balances and ۲ empirical models. in many cases it is difficult to find proper first principle models due to the fact that the kinetic properties are very difficult to identify or may change as a function of the operating conditions and thus it is difficult to come up with the right structure of the model. even in cases where the kinetic properties are known accurately the development of first principle models may be impractical for model based control if the model requires a large number of differential equations with a significant number of unknown parameters. unknown metabolism and complex networks for the above reasons an attractive alternative is to use relatively simple and compact empirical models obtained directly from measured input output data. examples of nonlinear empirical models are narma volterra series models and state affine models. this work details an algorithm that may be used to develop nonlinear regression models volterra series models and state affine models from process input output data. here i am showing a simple process control closed loop. a controller is adjusting the process input u based on the error between the output setpoint and the measured output value. during the controller design stage a process model will be used to represent the real process and as i have just explained empirical model will be used. another case …

کلمات کلیدی پرکاربرد در این اسلاید پاورپوینت: model, ., control, process, nonlinear, controller, series, volterra, pi, affine, state, modelling,

این فایل پاورپوینت شامل 53 اسلاید و به زبان انگلیسی و حجم آن 1.03 مگا بایت است. نوع قالب فایل ppt بوده که با این لینک قابل دانلود است. این مطلب برگرفته از سایت زیر است و مسئولیت انتشار آن با منبع اصلی می باشد که در تاریخ 2019/06/05 10:09:36 استخراج شده است.

http://www.eng.uwaterloo.ca/~hbudman/bangkokgs.ppt

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