Files
Control-Project/Experimentation/part2_MPC_controller.m
2021-12-09 17:59:12 -05:00

280 lines
8.5 KiB
Matlab

%% Close Figures, Clear Workspace, and Clear Terminal
close all;
clear;
clc;
%% System Parameters
% Track Information & Reference Trajectory
load("TestTrack.mat");
load('ROB535_ControlProject_part1_Team3.mat');
% Vehicle Parameters (Table 1)
global Nw f Iz a b By Cy Dy Ey Shy Svy m g
Nw = 2;
f = 0.01;
Iz = 2667;
a = 1.35;
b = 1.45;
By = 0.27;
Cy = 1.2;
Dy = 0.7;
Ey = -1.6;
Shy = 0;
Svy = 0;
m = 1400;
g = 9.806;
% Input Limits (Table 1)
global delta_lims Fx_lims
delta_lims = [-0.5, 0.5];
Fx_lims = [-5e3, 5e3];
% Position Limits
global x_lims y_lims
x_lims = [200, 1600];
y_lims = [-200, 1000];
% Initial Conditions (Equation 15)
state_init = [ ...
287; ... % x [m]
5; ... % u [m/s]
-176; ... % y [m]
0; ... % v [m/s]
2; ... % psi [rad]
0; ... % r [rad/s]
];
% Simulation Parameters
global T_s T_p num_preds num_states num_inputs
T_s = 0.01; % Step Size [s]
T_p = 0.5; % Prediction Horizon [s]
num_preds = T_p / T_s;
num_states = 6;
num_inputs = 2;
%% Constraint Functions
function [Lb, Ub] = bound_cons(idx, X_ref, U_ref)
global num_preds num_states num_inputs x_lims y_lims delta_lims Fx_lims
% initial_idx is the index along uref the initial condition is at
Lb = -Inf(num_preds*(num_states+num_inputs), 1);
Ub = Inf(num_preds*(num_states+num_inputs), 1);
for i = 0:(num_preds-1)
start_idx = get_start_idx(i);
% x
Lb(start_idx+1) = x_lims(1) - X_ref(idx+i, 1);
Ub(start_idx+1) = x_lims(2) - X_ref(idx+i, 1);
% y
Lb(start_idx+3) = y_lims(1) - X_ref(idx+i, 3);
Ub(start_idx+3) = y_lims(2) - X_ref(idx+i, 3);
% delta
Lb(start_idx+num_states+1) = delta_lims(1) - U_ref(idx+i, 1);
Ub(start_idx+num_states+1) = delta_lims(2) - U_ref(idx+i, 1);
% F_x
Lb(start_idx+num_states+2) = Fx_lims(1) - U_ref(idx+1, 2);
Ub(start_idx+num_states+2) = Fx_lims(2) - U_ref(idx+1, 2);
end
end
function [c, ceq] = road_obstacle_cons(Z, TestTrack, Xobs)
global num_preds num_states
ceq = [];
c = NaN(1,num_preds);
for i = 1:num_preds
idx = get_start_idx(i);
X = Z(idx+1:idx+num_states);
p = [X(1); X(3)];
[~,bl_idx] = min(vecnorm(TestTrack.bl - p));
[~,br_idx] = min(vecnorm(TestTrack.br - p));
idx_search = 1;
bl_idx_start = clamp(bl_idx-idx_search, 1, size(TestTrack.bl,2));
bl_idx_end = clamp(bl_idx+idx_search, 1, size(TestTrack.bl,2));
br_idx_start = clamp(br_idx-idx_search, 1, size(TestTrack.br,2));
br_idx_end = clamp(br_idx+idx_search, 1, size(TestTrack.br,2));
boundary_pts = [ ...
TestTrack.bl(:,bl_idx_start:1:bl_idx_end), ...
TestTrack.br(:,br_idx_end:-1:br_idx_start) ...
];
xv_road = boundary_pts(1,:);
yv_road = boundary_pts(2,:);
in_road = inpolygon(p(1), p(2), xv_road, yv_road);
if ~in_road
% Point not inside road
c(i) = 1; % c(x) > 0, nonlinear inequality constraint violated
end
if ~isnan(c(i))
% If value set, go to next "i"
continue
end
for j = 1:size(Xobs,2)
xv_obstacle = Xobs{i}(:,1);
yv_obstacle = Xobs{i}(:,2);
[in_obstacle, on_obstacle] = inpolygon(p(1), p(2), xv_obstacle, yv_obstacle);
if in_obstacle || on_obstacle
% Point in or on obstacle
c(i) = 1; % c(x) > 0, nonlinear inequality constraint violated
end
if ~isnan(c(i))
% If value set, skip checking remaining obstacles
break
end
end
if isnan(c(i))
% If value not set, no constraints violated
c(i) = -1; % c(x) <= 0, nonlinear inequality constraint satisfied
end
end
end
%% Kinematic Bike Models
function dXdt = nonlinear_bike_model(X,U)
global Nw f Iz a b m g
[x,u,y,v,psi,r,delta_f,F_x,F_yf,F_yr] = bike_model_helper(X,U);
% Vehicle Dynamics (Equation 1)
dx = u*cos(psi) - v*sin(psi);
du = (1/m)*(-f*m*g + Nw*F_x - F_yf*sin(delta_f)) + v*r;
dy = u*sin(psi) + v*cos(psi);
dv = (1/m)*(F_yf*cos(delta_f) + F_yr) - u*r;
dpsi = r;
dr = (1/Iz)*(a*F_yf*cos(delta_f) - b*F_yr);
dXdt = [dx; du; dy; dv; dpsi; dr];
end
function [A, B] = linearized_bike_model(X_ref,U_ref)
global Nw f Iz a b m g T_s
syms x_var u_var y_var v_var psi_var r_var ... % states
delta_f_var F_x_var ... % inputs
F_yf_var F_yr_var % lateral forces
% Vehicle Dynamics (Equation 1)
dx = u_var*cos(psi_var) - v_var*sin(psi_var);
du = (1/m)*(-f*m*g + Nw*F_x_var - F_yf_var*sin(delta_f_var)) + v_var*r_var;
dy = u_var*sin(psi_var) + v_var*cos(psi_var);
dv = (1/m)*(F_yf_var*cos(delta_f_var) + F_yr_var) - u_var*r_var;
dpsi = r_var;
dr = (1/Iz)*(a*F_yf_var*cos(delta_f_var) - b*F_yr_var);
% Jacobians of continuous-time linearized system
% TODO: Change A_c & B_c computation to regular functions (e.g.,
% using `matlabFunction`)
A_c_symb = [ ...
diff(dx, x_var), diff(dx, u_var), diff(dx, y_var), diff(dx, v_var), diff(dx, psi_var), diff(dx, r_var);
diff(du, x_var), diff(du, u_var), diff(du, y_var), diff(du, v_var), diff(du, psi_var), diff(du, r_var);
diff(dy, x_var), diff(dy, u_var), diff(dy, y_var), diff(dy, v_var), diff(dy, psi_var), diff(dy, r_var);
diff(dv, x_var), diff(dv, u_var), diff(dv, y_var), diff(dv, v_var), diff(dv, psi_var), diff(dv, r_var);
diff(dpsi,x_var), diff(dpsi,u_var), diff(dpsi,y_var), diff(dpsi,v_var), diff(dpsi,psi_var), diff(dpsi,r_var);
diff(dr, x_var), diff(dr, u_var), diff(dr, y_var), diff(dr, v_var), diff(dr, psi_var), diff(dr, r_var);
];
B_c_symb = [ ...
diff(dx, delta_f_var), diff(dx, F_x_var);
diff(du, delta_f_var), diff(du, F_x_var);
diff(dy, delta_f_var), diff(dy, F_x_var);
diff(dv, delta_f_var), diff(dv, F_x_var);
diff(dpsi,delta_f_var), diff(dpsi,F_x_var);
diff(dr, delta_f_var), diff(dr, F_x_var);
];
% Substitute values from reference trajectory into symbolic Jacobians
A_c = @(i) double( ...
subs( ...
A_c_symb, ...
[x_var, u_var, y_var, v_var, psi_var, r_var, delta_f_var, F_x_var, F_yf_var, F_yr_var], ...
bike_model_helper(X_ref(i,:), U_ref(i,:)) ...
) ...
);
B_c = @(i) double( ...
subs( ...
B_c_symb, ...
[x_var, u_var, y_var, v_var, psi_var, r_var, delta_f_var, F_x_var, F_yf_var, F_yr_var], ...
bike_model_helper(X_ref(i,:), U_ref(i,:)) ...
) ...
);
% Discrete-time LTV system
A = @(i) eye(6) + T_s*A_c(i);
B = @(i) T_s * B_c(i);
end
%% Helper Functions
function clamped_val = clamp(val, min, max)
clamped_val = val;
if clamped_val < min
clamped_val = min;
elseif clamped_val > max
clamped_val = max;
end
end
function [x,u,y,v,psi,r,delta_f,F_x,F_yf,F_yr] = bike_model_helper(X,U)
global Nw a b By Cy Dy Ey Shy Svy m g
% Get state & input variables
x = X(1);
u = X(2);
y = X(3);
v = X(4);
psi = X(5);
r = X(6);
delta_f = U(1);
F_x = U(2);
% Front and rear lateral slip angles in radians (Equations 8 & 9)
alpha_f_rad = delta_f - atan2(v + a*r, u);
alpha_r_rad = -atan2(v - b*r, u);
% Convert radians to degrees for other equations
alpha_f = rad2deg(alpha_f_rad);
alpha_r = rad2deg(alpha_r_rad);
% Nonlinear Tire Dynamics (Equations 6 & 7)
phi_yf = (1-Ey)*(alpha_f + Shy) + (Ey/By)*atan(By*(alpha_f + Shy));
phi_yr = (1-Ey)*(alpha_r + Shy) + (Ey/By)*atan(By*(alpha_r + Shy));
% Lateral forces using Pacejka "Magic Formula" (Equations 2 - 5)
F_zf = (b/(a+b))*(m*g);
F_yf = F_zf*Dy*sin(Cy*atan(By*phi_yf)) + Svy;
F_zr = (a/(a+b))*(m*g);
F_yr = F_zr*Dy*sin(Cy*atan(By*phi_yr)) + Svy;
% Limits on combined longitudinal and lateral loading of tires
% (Equations 10 - 14)
F_total = sqrt((Nw*F_x)^2 + (F_yr^2));
F_max = 0.7*(m*g);
if F_total > F_max
F_x = (F_max/F_total)*F_x;
F_yr = (F_max/F_total)*F_yr;
end
% Apply input limits (Table 1)
delta_f = clamp(delta_f, delta_lims(1), delta_lims(2));
F_x = clamp(F_x, Fx_lims(1), Fx_lims(2));
end
function idx = get_start_idx(i)
global num_states num_inputs
idx = (i-1)*(num_states+num_inputs);
end