Non-linear optimization in R - non-linear constraints

Question

I'm new to optimization in R and to R at all, Trying to implement the following set of equations - to find the Maximum, Minimum and intersections and maximum and minimum values for intersect points. a specific form of the function is:

P = 1.8X+2.55Y+3.2Z

where the constraints are:

X + Y + Z = 1 
X, Y, Z =>0
1.8X = 2.55Y = 3.2Z

I'm using nlcoptim trying to implement it the following way: library(NlcOptim)

objective function

obj = function(x){
  return(1.8 * x[1] + 2.55 * x[2] + 3.2 * x[3])
}

constraint function:

con = function(x){
  f = NULL
  f = rbind(f, x[1] + x[2] + x[3] - 1)
  f = rbind(f, x[1] >= 0)
  f = rbind(f, x[1] <= 1)
  f = rbind(f, x[2] >= 0)
  f = rbind(f, x[2] <= 1)
  f = rbind(f, x[3] >= 0)
  f = rbind(f, x[3] <= 1)
  return(list(ceq = NULL, c = f))
}

setting initial value for x:

x0 = c(0, 0, 0)

solving using solnl:

solnl(x0, objfun = obj, confun = con)

I keep getting an error. What am I doing wrong?