tailieunhanh - Advanced Model Predictive Control Part 14

Tham khảo tài liệu 'advanced model predictive control part 14', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | MBPC - Theoretical Development for Measurable Disturbances and Practical Example of Air-path in a Diesel Engine 379 A pf is the future increment in disturbance. A up is the past increment in control action. A pf is the past increment in disturbance. Thus system predictions are yf Sfs Auf SPs AuP Sfp - Pf SPp aPp ifpredW ySreai k Lp 29 Using equation 23 and 29 and using the optimization tool the result is AWf S ự -ự-Sfs RT R 1 STfi ự-ự- ysp - SPs AuP - SPp ApP - yreal k Lp 30 Thus H is the same as H Matrix but intead of Sf is Sfs. Every step time the controller is applying the first control action and update the data for getting new optimal control every step time. Thus only the first line in the matrix equation should be calculated. Additionally this matrix equation first line can be presented as a Z transform function transfer. This is the application of the fourth basis of MBPC receding horizon policy. It means that every step time a new control action will be calculated by means of updating data in the algorithm. Thus the control algorithm must be presented as In which h z is the first row of the H Matrix. The vector h z has different coefficients which will be multiplied by future set point if the information is available. If the future set point is not available a constant is calculated by adding all the h z vector coefficients. D z1 polynomial in which the coefficients are the result by multiplying h z - Sp. This array is in z-1 because is using past information. All in all the algorithms structure is shown in figure . Fig. 3. DMCDM architecture with receding horizon. When I z-1 is the convolution of two vectors one array is product of h z Spp the second array is A operator. Spp is new matrix calculated as Sp but using Markov coefficients of disturbance of the system. More information is available at Thesis of Garcia 16 . 4. Practical set up and experimental behavior This chapter is presenting the author s experience for tuning the algorithm. Also the .

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