... lẫn chi (chi khai thác) -Sơ đồ : Đầu tư xâydựngphần sau vừa khai thác vừa đầu tư, nên giai đoạn XDCB đợt có chi, giai đoạn sau có thu (khai thác) lẫn chi (chi đầu tư chi khai thác) 1 .5 Chiphí ... 26.700 5. 700 1.27 3.600 5. 700 1. 58 90.000 23.400 29 .80 0 6.400 1.27 2.400 3.100 1.29 100.000 26.000 32.700 6.700 1.26 2.600 2.900 1.12 1 25. 000 32 .50 0 38. 50 0 6.000 1. 18 6 .50 0 5 .80 0 0 .89 150 .000 37 .50 0 ... B/C hay BCR) sử dụng cho trường hợp Thông thường chiphí lớn nằm thời gian xâydựng (vốn đầu tư xâydựngchiphíban đầu) , sau chủ yếu có chiphí vận hành bảo dưỡng Còn lợi ích tăng dần theo...
... Đưa chiphí vào bảng tổng hợp dựtoánchiphíxây dựng, có kết Bảng tổng hợp dựtoánchiphíxâydựng hình sau: Hình: Bảng tổng hợp dựtoánchiphíxâydựng Đến xác định bảng tổng hợp dựtoánchi ... tư, xác định chiphí vật liệu Att, đưa chiphí vật liệu (Att) vào bảng tổng hợp dựtoánchiphíxâydựng ta có kết tính bảngdựtoán hình sau: Hình: Bảng tổng hợp dựtoánchiphíxâydựng kiểu TPHCM ... bố để lậpdựtoán xác định bảng tổng hợp khối lượng dựtoán Với phương pháp lập đơn giá xâydựng công trình đơn vị lậpdựtoánlập đơn giá xâydựng công trình dựa định mức dựtoánxâydựng công...
... addition of cargo, or due to engine degradation over time) At the same time it would try to achieve good disturbance rejection Clearly, the performance of a good cruise controller should not degrade ... be achieved Considering the system defined by (l.l), an adaptive controller may be defined so that an estimate of is generated, which we will denote If were known, then including a term -8x in ... recently developed systematic approach of adaptive backstepping [1 15] ) It is interesting to note, however, that while there are strong connections to conventional adaptive schemes, there is an additional...
... to (2 . 85 ), then the equilibrium x, = of (2 . 85 ) is asymptotically stable Also, if in this case, D = R” then the equilibrium x, = of (2 . 85 ) is asymptotically stable in the large Example 2. 15 As ... call a set a C R” invariant with respect to (2 . 85 ) if every solution x(&x0) of (2 . 85 ) with x(0, so) E a has x(&x0) E for all t Assume that (2 . 85 ) possesses unique solutions for all x0 E D c R’” ... I;‘(t,x) L -c3(xy c2)$ (2 .56 ) (2 .57 ) for all x E Bh and t 0, then xe = is exponentially stable If there exists a continuously differentiable V(t,x) and Equations (2 .56 ) and (2 .57 ) hold for some c,...
... +4’\- j input layer \ , \ / \ / , , ‘j / /’ / / ,,’ b x2 / x x3 X n 3 .5 Schematic of a mulitlayer perceptron Neural 58 Networks and Fuzzy Systems In a fully connected MLP, each neuron output ... “rule-base” in the “fuzzy controller.” One rule might be “if the current speed is 50 miles per hour and the desired speed is 55 miles per hour then press down on the accelerator a bit more.” Other rules ... each rule be a linear combination of a set of Lipschitz continuous functions, rk(x) E 8, k = 1,2, ) m-1,sothat Ci = gi(X) := ~i,O+ai,lYl(X)+es (3. 35) -+ai,m-2Ym-2(X)+ai,m-1Ym 1(X) i = l, , p In...
... From Theorem 6.1 we now simply need to show that the q dynamics satisfy (6. 58 ) -(6 .59 ) Let Vq = iqf which satisfies (6. 58 ) with ~~1 = yq2 = qt/2 Then T/b = 41 < - (1 -4; - 41 + 1411 - q1” + - 4: ... some positive definite V4 such that (6. 58 ) (6 .59 ) where ~~1 and yQ2 are cla’ssIc,, and yq3, $ are class K When x = the input-to-state stability assumption (6 .59 ) becomes & -y&yl), for all g, thus ... of (6 .52 ) w h en ? VT assuming with x as an input, is E R”, x E R” and t E RS If the q-subsystem, input-to-state stable, that is, there exists some positive definite Vn such that (6. 58 ) -(6 .59 )...
... and Adjustable Approximators 183 II 18 I I I I i I i 0.1 0.2 0.3 0.4 0 .5 0.6 0.7 0 .8 09 7.1 State trajectory when 8( O) = (-), e(O) = -2 ( a), 8( O) = -4 - -), and 8( O) = -6 (- -) ( Figure the ... (7 .56 ) with 7, VA > 0, then the parameter update law (7. 15) with adaptive controller u = F(z ,8) guarantee that the solutions of (7 .55 ) are bounded given B, C B, where B, is defined by (7. 25) ... Notice that Direct 196 15 20 25 30 35 Adaptive 40 Control 45 x (mkec) Figure 7.4 Input membership functions for the fuzzy system When p = 0.4, we find ]w] < as shown in Figure 7 .5 for our choice of...
... solutions of (8. 51 ) are B, C B, with B, defined by (8. 78) Sec 8. 3 Beyond Proof: the Matching Condition 2 45 Defining the Lyapunov candidate as (8. 76) where E = Q and (8. 77) If (el b, or (81 be where ... +Ti, (8. 57 ) )I for i = 2, ,n - 1, and en = -(Kn + - +&$)en - Sn-l&-l + Sn (An +Fn(H)) (8. 58 ) Sec 8. 3 Beyond the Matching Condition 241 Using the definition of the representation error, (8. 54 ), ... state According to (8. 52 ), the second error state is defined as e2 = 22 - vr, where (8. 82) a,nd K > Using (8. 61) for zr,j, (8. 71) for ~1, (8. 62) for 41, (8. 63) for D1, and (8. 72) for mr,j we find...
... numerical values of the parameters, we obtain from (9.31) fc (0 9&> + 73.4 0 85 sin& - 2. 289 8& = 48. 252 152 = - 109.37 05 (9.46) (9.47) In these equations we use “approximately equal” signs because ... DAFC with disturbance: sloshing water Figure is, we will use it to initialize the parameter matrix as 0.7 8( O) = 10 .8 0.7 0 0 0.7 10 .8 0.7 0.7 10 .8 0.7 0.7 10 .8 0.7 0.7 10 .8 0.7 (9. 68) Notice that ... is given by: ?i = x2,&1 = x3 + blu, k3 = alx2 + a2x3 + bzu, where al = -87 8 85 .84 , u2 = -1416.4, br = 280 .12, and b2 = - 1 85 77.14 If we now let x4 = r we can obtain two more equations which represent...
... estimate x’(i) Sec 10 .8 Output-Feedback Let C“ = with Tracking 355 [Cr~,Cr2rCT3]T, the the third-order and augment the copy of the plant (10.133) compensator, crl = 55 ‘r 52 VT1 = + CT3 (10.134) ... the second-order system 55 1 = x2 ‘c2 = 2; + exp(-xz)u y = Xl, (10. 58 ) for which a globally stabilizing controller is easily found to be u = - exp(xi) (xz + xl + 22) (10 .59 ) In this case the mapping ... identically zero Thus, (10 .88 ), (10 .89 ) is not an observer for the plant (10. 25) in the senseof Definition 10.1 Condition (10.91) plays a role similar to that of (10 .52 ) in Theorem 10.1 In analogy...
... lower-triangular form Example (51 = fl 7x1-1 (5 = f rt-1 (51 21 = fnl i3 - f2 (5, x242(0) Y Kl > + 91 (Cl )&? (6 17 (C) + Qnl-1 Jnl-1) (t) +972, -l (Al(t) (Il7~~~rtn~ l)trl + nl(E)u%) = (5, (11. 58 ) which, letting ... system (11 .86 )-(11 .87 ) is identical to that in Example 10.10, despite the presence of the uncertainty A XT1 XT2 (xrd2 = 7-t’(xr,(r) = + S’l 2xr1xr2 + (52 + , CT3 (11 .88 ) XT3 XT4 - 5 1 CT3 - - ... uniform upper bound 5Yr to the exit time which is independent of qr and 55 , and such that VL(x, (t)) - ~2, for all t E [O ,57 1) and for all < 17l,r/2 E (OJj Ch oose To such that < 57 ’ < Tl Then, in...
... in Figure 13 .5 Discrete-Time 4 68 0 I 0. 05 Figure I 0.1 I 0. 15 I 02 I 0.3 I 0. 25 E I 0. 35 I 04 I 0 45 Systems I 05 Plot of the ultimate bound function 13 .5 where we have chosen K = 0 .8 and W = 0.2 ... 1 I I I- I 0 .5 I I 1 1 .5 I I I I 25 I I I I 3 .5 1 I T=O.lO - - T = 0. 05 +I-' T = 0.01 +I-* 0 15- Ol- 0 05 w2 -0 05- -01 - Figure 13.3 Intersample and T = 0.01 ( s) error q(k) I I 4 .5 with T = 0.1 ... (13 .50 ) and (&x $JTP(&-x-$J - CXTPX - 2xTPy + ;yTPy, (13 .51 ) Sec 13.4 Robust Control of Discrete-Time Systems 455 we may add (13 .50 ) and (13 .51 ) to obtain (x + y)‘P(x + y) (1 + E)ZTPZ + (13 .52 )...
... &y-j d2,l + 42,l j/jzJ 42,l = &Gi with d1,2 = d2,1 = (14. 35) Decentralized 484 -21 I Figure 0.1 I 0.2 I 0.3 I 0.4 I 0 .5 I 0.6 I 0.7 I 0 .8 Systems I 0.9 I Closed-loop trajectory for ~r,i (-) and ... P (l+glC$$$l) + (ii;j +ECi,k Let (14.27) and (14. 28) Decentralized 482 Systems where we choose vi > The smooth function qi will be chosen to achieve diagonal dominance in the composite system ... -7iei,n + fi(yi) + J=(yi, Bi)) (14.49) 488 Decentralized Systems Since fi(Yi> + qyi, a,) = fi(Yi) + F(Yi, = fi(Yi) + F(Yi,ei) ei) - F(Yi, + % i Oi.) + F(Yi, 8i) (Ji - 6”) , one finds T/, < - N nN...