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284                                    Autonomous Mobile Robots

                                                 2
                                   Differentiating u z j,n j −1 yields
                                                 d1
                                 d
                                    2                        2
                                    d1
                                                             d1
                                   (u z j,n j −1 ) = 2u d1 ˙u d1 z j,n j −1 + u (−ρ j,n j −3 u d1 z j,n j −2 + u d1 z j,n j
                                 dt
                                                                    )
                                               − ρ j,n j −3 z j,n j −2 ˜u 1 +˜u 1 z j,n j
                                                      3                        2
                                            =−ρ j,n j −3 u z j,n j −2 + (2˙u d1 u d1 z j,n j −1 + u (−ρ j,n j −3 z j,n j −2 ˜u 1
                                                      d1                       d1
                                                          3
                                               +˜u 1 z j,n j  ) + u z j,n j )             (7.58)
                                                          d1
                                where the first term is uniformly continuous since its time derivative is bounded,
                                the other terms tend to zero. From the extended version of Barbalat’s Lemma,
                                                                       3
                                       2
                                (d/dt)(u z j,n j −1 ) tends to zero. Therefore, u z j,n j −2 and u d1 z j,n j −2 tend
                                       d1                              d1
                                to zero.
                                                           2
                                   Taking the time derivative of u z j,i ,2 ≤ i ≤ n j −2 and repeating the above
                                                           d1
                                procedure iteratively, one obtains that u d1 z j,i ,2 ≤ i ≤ n j tends to zero. From
                                                          being a linear combination of z j,i ,2 ≤ i ≤ n j ,
                                (7.25) and considering L h1 z j,n j
                                we know u d2 , Z 2 tends to zero.
                                            ˙
                                   Differentiating u d1 z j,i ,2 ≤ i ≤ n j − 1 yields
                                          d
                                            (u d1 z j,i ) =˙u d1 z j,i + u d1 ˙z j,i
                                          dt
                                                       ˙
                                                               u
                                                   = z j,i h + (−k u 1 d1 z j,i − k u 1 1 z j,i + u d1 ˙z j,i )
                                                                         ˜ u
                                where the first term is uniformly continuous, the other terms tend to zero. From
                                                                     ˙
                                the extended version of Barbalat’s Lemma, z j,i h tends to zero. By condition (ii)
                                in Assumption 7.3 on h, it can be concluded that z j,i tends to zero, which
                                leads to h tending to zero. By examining (7.30), noting ˜u 1 tending to zero and
                                condition (i) in Assumption 7.3, z 1 tends to zero. From (7.25) and condition (i),
                                u d1 tends to zero, therefore u = u d +˜u tends to zero. The theorem is
                                proved.


                                Remark 7.2   In Theorem 7.2, it has been proven that Z is globally asymp-
                                totically stabilizable, and all the signals in the closed-loop are bounded.
                                Accordingly, we can only claim the boundedness of the estimated parameters
                                and no conclusion can be made on its convergence. In general, to guarantee the
                                convergence of the parameter estimation errors, persistently exciting traject-
                                ories are needed [31,36], which is hard to meet in practice. Therefore, for the
                                globally asymptotical stability of Z, it is an advantage to remove the stringent
                                requirement of persistent excitation conditions for parameter convergence in
                                actual implementation.




                                 © 2006 by Taylor & Francis Group, LLC



                                FRANKL: “dk6033_c007” — 2006/3/31 — 16:43 — page 284 — #18
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