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APPC of Servo Systems With Continuously Differentiable Friction Model 63
Moreover, according to (4.3), we can further rewrite the friction dynamics
−T F (x 2 ) as
T
−T F (x 2 ) = α φ(x 2 ) (4.16)
T
where α =[α 1 ,α 2 ,α 3 ] are the friction coefficients and φ =[−(tanh(β 1x 2 )−
T
tanh(β 2x 2 )),−tanh(β 3x 2 ),−x 2 ] is a vector.
T T T T T T
Define =[W ,α ] and =[ ,φ ] , then one can represent
error Eq. (4.14)as
T
s ˙ = r + ε + gu (4.17)
In (4.17), the friction dynamics shown in (4.16) are lumped into the
T
NN approximation (4.15) resulting in a more compact form . More-
T
over, we define an unknown scalar θ = as the lumped adaptive param-
eter of HONN (4.15) and friction (4.16), and then a scalar θ (independent
ˆ
of the number of NN nodes) rather than the vectors W and α is updated
online, such that the computational costs can be reduced significantly. This
is different to conventional NN controllers, e.g., [7], [22], and [9].
4.3.2 Control Design and Stability Analysis
The control u can be specified as
2
k 1s θs T ˆ ε s
ˆ
u =− − − (4.18)
r 2η 2 ˆ ε|s|+ σ 1
2
˙ s T
θ = r − σ 2 θ ˆ (4.19)
ˆ
2η 2
˙ ˆ ε = r a |s| − σ 3 ˆε (4.20)
where > 0, a > 0, k 1 > 0, η> 0, and σ 1, σ 2,and σ 3 > 0are design
parameters.
We have the following result:
Theorem 4.1. Consider adaptive control system consisting of plant (4.1)with
the error transform (4.10), control (4.18) and adaptive laws (4.19)–(4.20), then:
i) All signals in the closed-loop system are semi-globally uniformly ultimately
bounded (SGUUB);
ii) The prescribed control performance (4.6)ispreserved.
Proof. i) Select a Lyapunov function as
1 2 g 2 g 2
V = s + θ ˜ + ˜ ε (4.21)
2 2 2 a