How can I arrange the optimization problem in the correct manner to solve using Intlinprog ?

This is the code I have written for a Integer Linear Programming problem.

There is an error at the section where CI is defined inside the optimisation problem.

When I run this, I get "Undefined function or variable 'CI'."

I know that its wrong, but I am kind of struggling to transform the relationship into an optimisation problem here.

Some of the usual equations are,

T_room in the second equation will be used to calculate the CI in equation (1).

Actually I am running the code only for a single time step.

Later I have to modify it for multiple time steps.

Please help me to arrange the optimisation problem in the right manner and to solve it.

Thanks.

clc;
clear all;

%% defining the parameters for each case

%%% Appliance power levels
Appliance_Power  = [2 ; 4 ; 5];  % for [App1 ; App2 : App3]

%%% Lower level of preferred temperature for the appliances

T_lower = [22 ; 20; 21]; % for [App1 ; App2 : App3]

%%% Upper level of preferred temperature for the appliances

T_upper = [28 ; 28; 29];% for [App1 ; App2 : App3]

%% assuming the initial room temperature 
T_room_initial = 33;  %% assume the same for all

%% outside temperature variation
T_ambient = 30;

%% house parameters

L1 = 30; % length
L2 = 10; % width
L3 = 4 ; % breadth

beta = 40; % roof angle

deltaAir = 1.225; % mass of the air


%% calculating the volume of the house

V_house = L1* L2* L3 + tan(beta)* L1* L2 ;

%% mass of air inside the house

M_air = V_house * deltaAir ;


%% Equivalent thermal resistance

R_eq = 3.1965e-6 ; %% the value in the paper was used, did not calculate 


%% thermal capacity of air

c_a = 1.01 ; %% kJ/kg deg C

%% specifications for the air conditioner

COP = 2 ; %% considering the Daikin brand air conditioner

%% for power levels of appliances

K = Appliance_Power./sum(Appliance_Power); %% cumulative power of appliances


%% now trying to develop the optimisation problem

x = optimvar('x' ,3, 'LowerBound', 0, 'UpperBound', 1);  %% 3 x 1 binary variable


%% defining the parameters for alpha and beta

alpha = 0.1 ;

beta = 100 ;

%% problem formulation

prob = optimproblem('Objective', alpha*K(1)*x(1) + beta *CI(1) + alpha*K(2)*x(2) + beta * CI(2) + alpha*K(3)*x(3) + beta *CI(3));

%% CI parameter definition for each
const1 = CI(1) == (2*T_room(1) - T_lower(1) - T_upper(1))./( T_upper(1)- T_lower(1));
const2 = CI(2) == (2*T_room(2) - T_lower(2) - T_upper(2))./( T_upper(2)- T_lower(2));
const3 = CI(3) == (2*T_room(3) - T_lower(3) - T_upper(3))./( T_upper(3)- T_lower(3));

%% room temperature update constants
const4 = T_room(1) == (1- (deltaT/(1000*M_air*c_a*R_eq)))*T_room_initial + (deltaT/(1000*M_air*c_a*R_eq))* T_ambient - x(1)* (COP * Appliance_Power(1) * deltaT/(0.000277*M_air*c_a));
const5 = T_room(2) == (1- (deltaT/(1000*M_air*c_a*R_eq)))*T_room_initial + (deltaT/(1000*M_air*c_a*R_eq))* T_ambient - x(2)* (COP * Appliance_Power(2) * deltaT/(0.000277*M_air*c_a));
const6 = T_room(3) == (1- (deltaT/(1000*M_air*c_a*R_eq)))*T_room_initial + (deltaT/(1000*M_air*c_a*R_eq))* T_ambient - x(3)* (COP * Appliance_Power(3) * deltaT/(0.000277*M_air*c_a));

%% power level constraints

const7 = Appliance_Power(1)* x(1) + Appliance_Power(2)* x(2) + Appliance_Power(3)* x(3) >= 4 ;

prob.Constraints.const1 = const1 ;
prob.Constraints.const2 = const2 ;
prob.Constraints.const3 = const3 ;
prob.Constraints.const4 = const4 ;
prob.Constraints.const5 = const5 ;
prob.Constraints.const6 = const6 ;
prob.Constraints.const7 = const7 ;


problem = prob2struct(prob) ; 


%% solving the problem

[sol, fval, exitflag, output] = intlinprog(problem);