How to do interrupted time series analysis using R's plm?

I am trying to model the following interrupted time series model:

y = b0 + b1*time + b2*event + b3*time_since_event

The data, however, is nested inside users (id). Currently, I have the following nlme model specification:

m = lme(y ~ time + event + time_since_event, random=~1+time|id, correlation = corAR1(), data=df)

Is the above model possible in plm at all? I tried the following:

m = plm(
+   y ~ time + event + time_since_event,
+   data = pd_df,
+   model = 'within',
+   effect = 'twoways'
+ )

But it throws the following error:

Error in plm.fit(data, model, effect, random.method, random.models, random.dfcor,  (r_v1.R#361): empty model
Show stack trace

Not sure if I plm is not suited for interrupted time series analysis like the one mentioned here.