State space specification of Random Intercept CLPM

Hi, I'm trying to specify a RI-CLPM (Hamaker et al., 2015; Mulder et al. 2021) as a state-space model, but I don't know how to specify the two random intercepts used to capture stable between-individual differences in change. I've tried different ways of including them but none of them worked. Could you please help me identify which matrices should I modify to include the effect of the random intercepts? I leave my code below. Thank you very much for your attention!

### Drift matrix
Amat <- mxMatrix(name="A", nrow=2, ncol=2, free = c(T,T,T,T),
values = c(.5, 0, 0, .5),
labels = c("a11","a21","a12","a22") )

### Input effects on the latent variables
Bmat <- mxMatrix(name = "B", "Zero", 2, 1)

### Measurement model
Cmat <- mxMatrix(name = "C", "Full", 2, 2, free = FALSE, values = c(1,0,0,1),
dimnames = list(c("Y1", "Y2"), c("y1", "y2")) )

### Input effects on the observed variables
Dmat <- mxMatrix("Zero", 2, 1, name = "D")

### Dynamic error
Qmat <- mxMatrix("Full", 2, 2, name = "Q",
free = c(T,T,T,T),
values = c(.6,0,0,.6),
labels = c("y1der","dercv","dercv","y2der"))

### Measurement error
Rmat <- mxMatrix("Zero", 2, 2, F, name = "R")

### Mean vector
x0mat <- mxMatrix("Zero", name='x0', nrow=2, ncol=1)

### Covariance matrix
P0mat<- mxMatrix(name='P0', nrow=2, ncol=2,
free = TRUE,
values=c(1,0,0,1),
labels=c("y1v","y12cv","y12cv","y2Av"))

### Covariates
Umat <- mxMatrix("Zero", 1, 1, name = "u")

### Specification of the time index
Tmat <- mxMatrix('Full', 1, 1, name='time', labels='data.time')

References:
Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. (2015). A critique of the cross-lagged panel model. Psychological methods, 20(1), 102.
Mulder, J. D., & Hamaker, E. L. (2021). Three extensions of the random intercept cross-lagged panel model. Structural Equation Modeling: A Multidisciplinary Journal, 28(4), 638-648.