vậy c d 40 6 67 10 2 41 67
Nonlinear Model Predictive Control: Theory and Algorithms (repost)
... 25 1 25 1 2 56 26 0 26 4 26 6 26 9 27 1 27 2 10 Numerical Optimal Control of Nonlinear Systems 10. 1 Discretization of the NMPC Problem 10. 2 Unconstrained Optimization 10. 3 Constrained ... max 2 τ β(r, t2 − τ ) τ ∈[0,t2 ] = max max 2 τ β(r, t2 − τ ), max 2 τ β(r, t2 − τ ), τ ∈[0 ,d/ 2] max −τ τ ∈ [d, t2 ] τ ∈ [d/ 2 ,d] β(r, t2 − τ ) ≤ max β(r, t2 − d/ 2) , 2 d/ 2 β(r, t2 − d) , max 2 τ d β(r, ... Applications to industrial processes Automatica 14, 413 – 428 (1978) 26 Schittkowski, K.: Numerical Data Fitting in Dynamical Systems Applied Optimization, vol 77 Kluwer Academic, Dordrecht (20 02) Chapter...
- 372
- 569
- 0
Báo cáo hóa học: "Research Article Neural Network Adaptive Control for Discrete-Time Nonlinear Nonnegative Dynamical Systems" ppt
... Scienti c Research under Grant no FA9550- 06- 1-0 24 0 and the National Science Foundation under Grant no ECS- 060 1311 Wassim M Haddad et al 29 References T Hayakawa, W M Haddad, J M Bailey, and ... less conservative ultimate bounds for neuroadaptive controllers as compared to ultimate bounds derived using classical boundedness and ultimate boundedness notions Specifically, consider the discrete-time ... 1 /2 ex c ≤ c for a, b > and c > −1 Now, ≤ R1 /2 ex T 2ex AT P e ≤ c 2 P 1 /2 ex s , c 1 P 1 /2 e 2 A .21 , and rearranging terms in A .20 yields ΔVe ex k , ez k , W k ≤− μ1 P 1 /2 ex k P 1 /2 ex k c 2...
- 29
- 361
- 1
ON STABILITY ZONES FOR DISCRETE-TIME PERIODIC LINEAR HAMILTONIAN SYSTEMS ˘ VLADIMIR RASVAN Received potx
... lin´aires du second ordre a e e e e [22 ] ` coefficients p´riodiques, Comptes Rendus Math´ matique Acad´ mie des Sciences paris 128 (1899), e e e 108 5 108 8 [23 ] Vl R˘ svan, Stability zones for discrete ... Hamiltonian difference systems: disconjugacy and Jacobi-type conditions, Journal of Mathematical Analysis and Applications 199 (19 96) , no 3, 804–8 26 [3] M Bohner and O Doˇl´ , Disconjugacy and transformations ... on discrete-time Hamiltonian systems is considered to be that of Hartman [ 16] (because it deals with disconjugacy, principal solutions, etc., which are directly connected with book’s topics),...
- 13
- 216
- 0
Báo cáo sinh học: " Heritability of longevity in Large White and Landrace sows using continuous time and grouped data models" ppsx
... 3.08 censored 3.55 2. 52 4.09 2 . 62 LPL at last litter (days) 503 4 56 595 481 non-censored 531 467 61 5 490 censored 401 397 485 4 12 Piglets born alive per parity 10. 57 1 . 62 9. 96 1.47 non-censored 10. 35 ... of censored: 26 7 4; btotal number of records: 9833, number of non- censored: 83 32, number of censored: 1501 was 26 . 4% in the Large White and 22 .3% in the Landrace database Landrace sows lived 92 ... J Dairy Sci 20 02, 85:1 563 -1577 16 Yazdi MH, Rydhmer L, Ringmar-Cederberg E, Lundeheim N, Johansson K: Genetic study of longevity in Swedish Landrace sows Livest Prod Sci 20 00, 63 :25 5- 26 4 17 Damgaard...
- 13
- 250
- 0
Adaptive control and neural network control of nonlinear discrete time systems
... containing the delayed states can be matched and canceled [24 – 26 ] In practice, there may be some nonsmooth, nonlinear input constraint, such as dead zone, backlash and hysteresis, which are common ... becomes much more difficult, since we cannot decide the direction along which the control operates Moveover, in discrete-time adaptive control the control directions are usually required to avoid ... adaptive control design In Section 3.3, we consider more complicated case of unmatched uncertainties Auxiliary states including both parametric and nonparametric uncertainties are introduced to facilitate...
- 217
- 255
- 0
Changes of temperature data for energy studies over time and their impact on energy consumption and CO2 emissions. The case of Athens and Thessaloniki – Greece
... 24 26 20 22 24 26 20 22 24 26 20 22 24 26 20 22 24 26 1983 – 19 92 114 74 43 23 1 86 1 32 87 53 174 121 79 47 84 51 28 13 558 378 23 7 1 36 Period 1993 – 20 02 137 92 56 30 20 5 149 100 62 193 1 36 90 ... 26 6 20 7 151 1 02 3 62 300 23 9 180 125 28 7 23 2 179 130 86 24 9 191 138 91 55 130 85 49 24 10 1 62 5 125 9 930 64 5 415 1983 – 20 02 82 48 25 11 2 06 151 1 02 63 35 340 27 9 21 9 161 109 365 303 24 2 183 128 ... 91 55 29 22 2 1 62 110 69 21 0 151 100 61 113 71 41 21 68 4 475 3 06 180 Period 1993 – 20 02 1 92 138 92 56 27 2 21 1 153 103 25 7 1 96 139 91 131 83 48 25 8 52 62 8 4 32 275 1983 – 20 02 165 114 73 43 24 7 187...
- 14
- 548
- 0
Tài liệu ADVANCES IN DISCRETE TIME SYSTEMS docx
... Bernstein & Haddad (1989) con‐ sidered merely the combined LQG/H ∞ control problem in the special case of Q = C1 T C1 and T R = D1 2 D1 2 andC1T D1 2 = Since the expected cost function J (Ac , Bc , Cc ) equals ... 0.54 96 − 0 .29 03 − 2. 023 7 p1 ,2 = − 0.0451 ± j0.1 8 62 X3>0 0.5398 − 0 .29 18 − 2. 0 363 p1 ,2 = − 0.0459 ± j0 .29 12 X4>0 0. 525 0 − 0 .2 940 − 2. 04 92 p1 ,2 = − 0.0470 ± j0. 368 6 X5>0 0.5 040 − 0 .2 969 − 2. 0 62 4 ... = C1 T C1 and R = D1 2 D1 2 and C1 T D1 2 = arisen from Bernstein & Haddad (1989) and Haddad et al (1991) is a mixed H 2/ H ∞ control problem Based on the above definition, we give sufficient conditions...
- 256
- 373
- 0
Discrete Time Systems Part 1 pdf
... 0. 069 yd2 Pyd2 yd3 Pyd3 yd4 Pyd4 yd5 Pyd5 yd6 Pyd6 yd7 Pyd7 yd8 Pyd8 yd9 yd10 Pyd9 Pyd10 0 .67 5 0.500 0.0 0.370 -0.355 0 .27 7 -0.5 92 0 .2 16 -0. 768 0.175 -0.908 0.145 -1. 023 0. 124 -1. 120 0.1 06 -1.199 ... 0.355 0 .27 7 0.0 0 .23 0 -0 .24 2 0.191 -0. 424 0. 1 62 -0. 569 0.139 -0 .69 0 0. 121 -0.789 0.1 06 1 .21 8 0 .22 3 0.5 92 0 .2 16 0 .24 2 0.191 0.0 0. 166 -0.184 0.145 -0.3 32 0. 129 -0.453 0.114 1.377 0. 169 0. 768 0.175 ... Chapter 26 Discrete Deterministic and Stochastic Dynamical Systems with Delay - Applications 477 Mihaela Neamţu and Dumitru Opriş Chapter 27 Multidimensional Dynamics: From Simple to Complicated 505...
- 30
- 500
- 1
Discrete Time Systems Part 2 potx
... (sec) CP TCPU FLP TCPU PFF TCPU 0.1 72 0 .29 8 0.384 0.500 0 .65 6 0.187 0.305 0.4 52 0 .60 2 0.754 0.8 26 1.475 1. 863 2. 5 52 3.137 1. 024 1.743 2. 454 3.3 06 4 .20 3 0.185 0. 310 0 .405 0.550 0 .69 1 0 .20 0 0. 340 ... k ⎦ d Γ44 ζk P A − LC − P + Q T Γ 12 = A − LC P Ad − Ld C Γ13 = M T (K1 , , Kq ) + A − LC T Γ14 = A − LC 22 = Ad − L d C T 23 = Ad − L d C T PΣ P d T Γ34 = Σ PΣ T P d ζk = d ζk = (67 ) (69 ) (71) ... (71) ( 72) d Γ44 = (Σ ) PΣ − Υ d (65 ) (70) Γ33 = Σ T PΣ − Υ T (64 ) (68 ) PΣ d d 24 = N T (K1 , , Kq ) + Ad − L d C (63 ) (66 ) P Ad − Ld C − Q d T ( 62 ) (73) d (74) T T T T [ζ 11 , , ζ 1s1 , ζ 21 ,...
- 30
- 291
- 0
Discrete Time Systems Part 3 ppt
... Proc 2nd European Control Conference: ECC’93, Groningen, Holland, pp 2 26 6 22 70 Hou, M & Müller, P C (1994) Disturbance decoupled observer design: a unified viewpoint, IEEE Trans Automatic Control, ... Pt (2, 1) − Pt and (1,1) (2, 1) (2, 2) Mt Ct T − Ht Rt Ct T − Ht Rt Ct Pt Ct T + Rt Ct Pt Ct T + Rt Ct T Ct Pt Ct T + Rt (2, 2) = Pt (2, 1) − Pt −1 −1 −1 (1,1) Ct Pt Ct T Ct Pt Ct T + Rt (1,1) Ct Pt ... + Pt Ct T Ct Pt Ct T + Rt (2, 1) ˆ ˆ θt+1/t+1 = θt/t + Pt Ct T (2, 1) Pt+1 = and (2, 1) Pt (2, 2) (2, 1) − Pt (2, 2) Pt+1 = Pt Ct Pt Ct T + Rt Ct T (2, 1) − Pt −1 −1 Ct Pt Ct T + Rt Ct T ˆ (yt − Ct xt/t...
- 30
- 281
- 0
Discrete Time Systems Part 4 pptx
... P1 2c, k := P 12, k|k−1 + P11,k|k−1 Mk P 12, k|k−1 , (60 ) T P2 2c, k := P 22, k|k−1 + P 12, k|k−1 Mk P 12, k|k−1 , (61 ) S1,k := P1 1c, k − P1 2c, k , ( 62 ) S2,k := P1 2c, k − P2 2c, k , (63 ) S3,k := T S1,k − S2,k (64 ) ... Ψ1,k T Ck Sk Ck + 2, k † , (69 ) ∗ † Φ∗ = Ak + ( Ak − Kk Ck ) P1 2c, k P2 2c, k − I , k (70) where † T Sk := P1 1c, k − P1 2c, k P2 2c, k P1 2c, k , Ψ1,k := 2, k := (71) T T Bw,k Wc,k Dw,k + Bv,k Vc,k Dv,k ... (mechanical, electrical, aerospace, civil and chemical), physics, economics, mathematics and biology Simon (20 06) A typical system dynamics can be represented as a transfer function or using the space-state...
- 30
- 314
- 0
Discrete Time Systems Part 5 potx
... [-Ad,iYi(k )C2 d, i'(k)-Mi(k)(Hd,iHd,i’πi(k)+ C2 d, iYi(k )C2 d, i’)]Mi’(k) ∑ pd ,ij [-Ad,iYi(k )C2 d, i'(k)+ Ad,iYi(k )C2 d, i’]Mi’(k) i∈J ( k ) = i∈J ( k ) = i∈J ( k ) =0 which concludes the proof (Q.E .D. ) References ... Hybrid Systems: Computation and Control: 12th Conference, HSCC 20 09, San Francisco, CA, USA, April, 20 09, Proceedings, LNCS 5 469 , R Majumdar & P Tabuada (Eds.), pp 455-459, Springer, 3 -64 2- 0 060 19, ... J d ( rd ) and the dynamics can be written as follows: x(k+1)=Ad,m(k)(k)x(k)+Gd,m(k)(k) d( k)+B 2d, m(k)(k) ud ,c (k)+ r d ,c (k) where r d ,c (k)=B 2d, m(k){Du,m(k)(k)rd(k) +D u,m(k)(k)Em(k)( c (k+1),k)}+B 3d, m(k)(k)rd(k)...
- 30
- 448
- 0
Discrete Time Systems Part 6 pptx
... ˆ ˆ ˆ Wc = ∅, Wc = {Wc1 ∈ Rn×n , Wc2 ∈ Rm×n : Wc1 > 0, c < 0} where − ˆ ˆ ˆ A = Tc ATc , B = Tc B, Wc1 = and ˆ Wc2 = Wc21 , Wc11 ∈ Rl ×l , c = Wc11 , Wc 22 Wc 22 ∈ R( n−l )×( n−l ), Wc21 ∈ Rm×l ... (38) Kc = {Kc = Wc2Wc11 ∈ Rm×n : (Wc1, Wc2 ) ∈ Wc } 148 and where c = Discrete Time Systems Wc = {Wc1 ∈ Rn×n , Wc2 ∈ Rm×n : Wc1 > 0, c < 0} (39) −Wc1 AWc1 + BWc2 T Wc1 A T + Wc2 B T −Wc1 − ˜ Ko ... 0. 063 4 0 . 62 54 ⎢ Ao = ⎢ 0.0901 0. 722 8 0.5133 ⎢ ⎣ 0 .69 67 0.0337 0.5757 0.1471 0 .69 57 0 .28 72 ⎡ 0.9505 ⎢ 0.31 82 ⎢ Bo = ⎢ 0. 26 5 9 ⎢ ⎣ 0. 061 1 0.3 328 Co = 0.8 927 0.09 26 0 .29 25 0. 821 9 0.994 ⎤ 0. 067 8 0.9731...
- 30
- 344
- 0
Discrete Time Systems Part 7 ppt
... parameter-dependent discrete-time Riccati equation (21 ) to get ⎡18. 523 8 3. 829 5 0. 166 4 ⎤ ⎢ ⎥ X∞ = ⎢ 3. 829 5 51. 321 2 23 . 32 26 ⎥ > , ⎢ 0. 166 4 23 . 32 26 22 .7354 ⎥ ⎣ ⎦ ⎡ 0. 729 2 −0.0 560 −0.0 024 ⎤ 60 9 .64 41 723 .0571 ... 0. 5 62 5 [ 21 .9 6. 7 − 0.3 − 2 .6 − 1.9] 0. 363 3 0.5 26 4 [ 23 .4 8 .6 0 .2 − 1.9 − 1.9] 0. 364 1 2 .63 43 [−9.0 26 . 4 0 .2 − 2. 5 − 1.9] −1 .67 68 2. 5959 [−9.0 25 .9 0 .2 − 2. 5 − 1.9] −1. 560 2 Table The observer design ... −0.0 560 0 .24 96 −0.3 410 ⎥ > , U = ⎢ ⎥, ⎢ ⎥ ⎣ 723 .0571 863 . 568 3 ⎦ ⎢ −0.0 024 −0.3 410 0 .66 76 ⎥ ⎣ ⎦ ⎡ 14 .22 74 −0.0 723 ⎢ T ρ I − H KU H K = ⎢ −0.0 723 14 .20 20 ⎢ ⎣ 0 ⎤ ⎥ ⎥>0 14 .28 84 ⎥ ⎦ 1 76 New Trends in...
- 30
- 365
- 0
Discrete Time Systems Part 8 pot
... a2 ( k ) γ e2 ( k ) c c Dc ( k ) ˜ ¯ ¯ ˜ ¯ ¯ +[ θ T (k − n )φ(k − 1) + g T (k − n )u(k − n )] e(k) ≤ 2ac (k) c Dc ( k ) a2 ( k ) γ e2 ( k ) 2ac (k) c e2 (k) c c − Dc ( k ) Dc ( k ) 2ac (k) c ... uncertainty can be dealt with by feedback?, IEEE Transactions on Automatic Control 45( 12) : 22 03 22 17 22 8 Discrete Time Systems Xu, J.-X & Huang, D (20 09) Discrete-time adaptive control for a class ... both hand sides of (48), we obtain ∞ ∑ γ c (2 − γ c ) k =0 a2 ( k ) e2 ( k ) c ≤ Vc (0) − Vc (∞) Dc ( k ) 21 7 Discrete-Time Adaptive Predictive Control with Asymptotic Output Tracking which implies...
- 30
- 354
- 0
Discrete Time Systems Part 9 ppt
... Perturbed Measures for Complex Dynamics - Case Study: Unmanned Underwater Vehicles 25 7 The vehicle dynamics is described as (see Jordán & Bustamante, 20 0 9c; cf Fossen, 1994) v= M −1 C [v]v− D [|v|]v−g[η] ... Journal of Control 79 (10) : 127 7– 128 4 Xie, L L & Guo, L (20 00) How much uncertainty can be dealt with by feedback?, IEEE Transactions on Automatic Control 45( 12) : 22 03 22 17 Yang, C. , Dai, S.-L., ... Decentralized Adaptive Control of Discrete-Time Multi-Agent Systems 25 3 Acknowledgments This work is partially supported by National Nature Science Foundation (NSFC) under Grants 61 0 0405 9, 61 0 0413 9...
- 30
- 315
- 0
Discrete Time Systems Part 10 pdf
... Underwater Vehicles 27 5 and the mass variations are MbΔ+ = diag (10, 10, 10, 0 . 62 50, 4 .22 50, 3 .6) ( 86) MbΔ− = diag (20 , 20 , 20 , 1 .25 , 1 .25 , 0) (87) MaΔ+ = diag (6. 3, 15.4, 0.115, 0.115, 0. 26 1 , 0 .2 76) (88) ... Approach to Discrete-Time Adaptive Control Systems with Perturbed Measures for Complex Dynamics - Case Study: Unmanned Underwater Vehicles 26 5 The second component τ 2n of τ n was contained in ... Approach to Discrete-Time Adaptive Control Systems with Perturbed Measures for Complex Dynamics - Case Study: Unmanned Underwater Vehicles 27 1 where f1 ,f2 and f3 are bounded vector functions...
- 30
- 300
- 0
Discrete Time Systems Part 11 potx
... Λ T (W T DiT + F 22 CiT ) ⎥ T T T ⎥ 0 F 12 Cm − (W T DiT + F 22 CiT ) ⎥
- 30
- 340
- 0
Discrete Time Systems Part 12 ppt
... , D1 = 0.1, A2 = 1.1A1 , C2 = 1. 1C1 , Dw2 = 1.1Dw1 Ad2 = 1.1Ad1 B2 = 1.1B1 Cd2 = 1.1Cd1 D2 = 1. 1D1 (97) (98) (99) (100 ) It is desired to design robust state feedback gains for control law (6) ... input delays, Journal of The Franklin Institute 338(1): 101 – 110 URL: http://www.sciencedirect.com/science/article/B6V04- 428 6KHS -9 /2/ 819 7c 8472fdf44 4d1 396b1 961 9d4 dcaf Zhang, H., Xie, L & Duan, D ... i ¯i ¯i ¯i ¯i ¯i ¯i ¯i 22 = ( A 12 ) T P11 A 12 + ( A 22 ) T ( P 12 ) T A 12 + ( A 12 ) T P 12 A 22 + ( A 22 ) T P 22 A 22 ¯i At this point, we declare A 22 is nonsingular from 22 < Otherwise, there is...
- 30
- 387
- 0
Tìm thêm: hệ việt nam nhật bản và sức hấp dẫn của tiếng nhật tại việt nam khảo sát chương trình đào tạo của các đơn vị đào tạo tại nhật bản xác định thời lượng học về mặt lí thuyết và thực tế điều tra với đối tượng sinh viên học tiếng nhật không chuyên ngữ1 khảo sát thực tế giảng dạy tiếng nhật không chuyên ngữ tại việt nam nội dung cụ thể cho từng kĩ năng ở từng cấp độ xác định mức độ đáp ứng về văn hoá và chuyên môn trong ct phát huy những thành tựu công nghệ mới nhất được áp dụng vào công tác dạy và học ngoại ngữ mở máy động cơ lồng sóc các đặc tính của động cơ điện không đồng bộ hệ số công suất cosp fi p2 đặc tuyến hiệu suất h fi p2 đặc tuyến mômen quay m fi p2 đặc tuyến tốc độ rôto n fi p2 đặc tuyến dòng điện stato i1 fi p2 động cơ điện không đồng bộ một pha sự cần thiết phải đầu tư xây dựng nhà máy thông tin liên lạc và các dịch vụ phần 3 giới thiệu nguyên liệu chỉ tiêu chất lượng 9 tr 25