mirror of
https://github.com/ROB-535-F21-Team-3/Control-Project.git
synced 2025-08-24 03:02:45 +00:00
5534819d90
- Add 1/2 coefficient to cost function - Move `MPC_Class.m` to "Deliverables" folder - Modify `part2_test_controller.m` plotting style a bit - Rename `part2_MPC_controller.m` to `sravan_MPC_controller.m`
280 lines
8.5 KiB
Matlab
280 lines
8.5 KiB
Matlab
%% Close Figures, Clear Workspace, and Clear Terminal
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close all;
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clear;
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clc;
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%% System Parameters
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% Track Information & Reference Trajectory
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load("TestTrack.mat");
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load('ROB535_ControlProject_part1_Team3.mat');
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% Vehicle Parameters (Table 1)
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global Nw f Iz a b By Cy Dy Ey Shy Svy m g
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Nw = 2;
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f = 0.01;
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Iz = 2667;
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a = 1.35;
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b = 1.45;
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By = 0.27;
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Cy = 1.2;
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Dy = 0.7;
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Ey = -1.6;
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Shy = 0;
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Svy = 0;
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m = 1400;
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g = 9.806;
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% Input Limits (Table 1)
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global delta_lims Fx_lims
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delta_lims = [-0.5, 0.5];
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Fx_lims = [-5e3, 5e3];
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% Position Limits
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global x_lims y_lims
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x_lims = [200, 1600];
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y_lims = [-200, 1000];
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% Initial Conditions (Equation 15)
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state_init = [ ...
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287; ... % x [m]
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5; ... % u [m/s]
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-176; ... % y [m]
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0; ... % v [m/s]
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2; ... % psi [rad]
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0; ... % r [rad/s]
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];
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% Simulation Parameters
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global T_s T_p num_preds num_states num_inputs
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T_s = 0.01; % Step Size [s]
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T_p = 0.5; % Prediction Horizon [s]
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num_preds = T_p / T_s;
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num_states = 6;
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num_inputs = 2;
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%% Constraint Functions
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function [Lb, Ub] = bound_cons(idx, X_ref, U_ref)
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global num_preds num_states num_inputs x_lims y_lims delta_lims Fx_lims
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% initial_idx is the index along uref the initial condition is at
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Lb = -Inf(num_preds*(num_states+num_inputs), 1);
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Ub = Inf(num_preds*(num_states+num_inputs), 1);
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for i = 0:(num_preds-1)
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start_idx = get_start_idx(i);
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% x
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Lb(start_idx+1) = x_lims(1) - X_ref(idx+i, 1);
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Ub(start_idx+1) = x_lims(2) - X_ref(idx+i, 1);
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% y
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Lb(start_idx+3) = y_lims(1) - X_ref(idx+i, 3);
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Ub(start_idx+3) = y_lims(2) - X_ref(idx+i, 3);
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% delta
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Lb(start_idx+num_states+1) = delta_lims(1) - U_ref(idx+i, 1);
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Ub(start_idx+num_states+1) = delta_lims(2) - U_ref(idx+i, 1);
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% F_x
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Lb(start_idx+num_states+2) = Fx_lims(1) - U_ref(idx+1, 2);
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Ub(start_idx+num_states+2) = Fx_lims(2) - U_ref(idx+1, 2);
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end
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end
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function [c, ceq] = road_obstacle_cons(Z, TestTrack, Xobs)
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global num_preds num_states
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ceq = [];
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c = NaN(1,num_preds);
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for i = 1:num_preds
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idx = get_start_idx(i);
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X = Z(idx+1:idx+num_states);
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p = [X(1); X(3)];
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[~,bl_idx] = min(vecnorm(TestTrack.bl - p));
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[~,br_idx] = min(vecnorm(TestTrack.br - p));
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idx_search = 1;
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bl_idx_start = clamp(bl_idx-idx_search, 1, size(TestTrack.bl,2));
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bl_idx_end = clamp(bl_idx+idx_search, 1, size(TestTrack.bl,2));
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br_idx_start = clamp(br_idx-idx_search, 1, size(TestTrack.br,2));
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br_idx_end = clamp(br_idx+idx_search, 1, size(TestTrack.br,2));
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boundary_pts = [ ...
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TestTrack.bl(:,bl_idx_start:1:bl_idx_end), ...
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TestTrack.br(:,br_idx_end:-1:br_idx_start) ...
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];
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xv_road = boundary_pts(1,:);
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yv_road = boundary_pts(2,:);
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in_road = inpolygon(p(1), p(2), xv_road, yv_road);
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if ~in_road
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% Point not inside road
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c(i) = 1; % c(x) > 0, nonlinear inequality constraint violated
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end
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if ~isnan(c(i))
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% If value set, go to next "i"
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continue
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end
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for j = 1:size(Xobs,2)
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xv_obstacle = Xobs{i}(:,1);
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yv_obstacle = Xobs{i}(:,2);
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[in_obstacle, on_obstacle] = inpolygon(p(1), p(2), xv_obstacle, yv_obstacle);
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if in_obstacle || on_obstacle
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% Point in or on obstacle
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c(i) = 1; % c(x) > 0, nonlinear inequality constraint violated
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end
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if ~isnan(c(i))
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% If value set, skip checking remaining obstacles
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break
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end
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end
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if isnan(c(i))
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% If value not set, no constraints violated
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c(i) = -1; % c(x) <= 0, nonlinear inequality constraint satisfied
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end
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end
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end
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%% Kinematic Bike Models
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function dXdt = nonlinear_bike_model(X,U)
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global Nw f Iz a b m g
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[x,u,y,v,psi,r,delta_f,F_x,F_yf,F_yr] = bike_model_helper(X,U);
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% Vehicle Dynamics (Equation 1)
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dx = u*cos(psi) - v*sin(psi);
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du = (1/m)*(-f*m*g + Nw*F_x - F_yf*sin(delta_f)) + v*r;
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dy = u*sin(psi) + v*cos(psi);
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dv = (1/m)*(F_yf*cos(delta_f) + F_yr) - u*r;
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dpsi = r;
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dr = (1/Iz)*(a*F_yf*cos(delta_f) - b*F_yr);
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dXdt = [dx; du; dy; dv; dpsi; dr];
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end
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function [A, B] = linearized_bike_model(X_ref,U_ref)
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global Nw f Iz a b m g T_s
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syms x_var u_var y_var v_var psi_var r_var ... % states
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delta_f_var F_x_var ... % inputs
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F_yf_var F_yr_var % lateral forces
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% Vehicle Dynamics (Equation 1)
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dx = u_var*cos(psi_var) - v_var*sin(psi_var);
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du = (1/m)*(-f*m*g + Nw*F_x_var - F_yf_var*sin(delta_f_var)) + v_var*r_var;
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dy = u_var*sin(psi_var) + v_var*cos(psi_var);
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dv = (1/m)*(F_yf_var*cos(delta_f_var) + F_yr_var) - u_var*r_var;
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dpsi = r_var;
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dr = (1/Iz)*(a*F_yf_var*cos(delta_f_var) - b*F_yr_var);
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% Jacobians of continuous-time linearized system
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% TODO: Change A_c & B_c computation to regular functions (e.g.,
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% using `matlabFunction`)
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A_c_symb = [ ...
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diff(dx, x_var), diff(dx, u_var), diff(dx, y_var), diff(dx, v_var), diff(dx, psi_var), diff(dx, r_var);
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diff(du, x_var), diff(du, u_var), diff(du, y_var), diff(du, v_var), diff(du, psi_var), diff(du, r_var);
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diff(dy, x_var), diff(dy, u_var), diff(dy, y_var), diff(dy, v_var), diff(dy, psi_var), diff(dy, r_var);
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diff(dv, x_var), diff(dv, u_var), diff(dv, y_var), diff(dv, v_var), diff(dv, psi_var), diff(dv, r_var);
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diff(dpsi,x_var), diff(dpsi,u_var), diff(dpsi,y_var), diff(dpsi,v_var), diff(dpsi,psi_var), diff(dpsi,r_var);
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diff(dr, x_var), diff(dr, u_var), diff(dr, y_var), diff(dr, v_var), diff(dr, psi_var), diff(dr, r_var);
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];
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B_c_symb = [ ...
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diff(dx, delta_f_var), diff(dx, F_x_var);
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diff(du, delta_f_var), diff(du, F_x_var);
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diff(dy, delta_f_var), diff(dy, F_x_var);
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diff(dv, delta_f_var), diff(dv, F_x_var);
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diff(dpsi,delta_f_var), diff(dpsi,F_x_var);
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diff(dr, delta_f_var), diff(dr, F_x_var);
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];
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% Substitute values from reference trajectory into symbolic Jacobians
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A_c = @(i) double( ...
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subs( ...
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A_c_symb, ...
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[x_var, u_var, y_var, v_var, psi_var, r_var, delta_f_var, F_x_var, F_yf_var, F_yr_var], ...
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bike_model_helper(X_ref(i,:), U_ref(i,:)) ...
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) ...
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);
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B_c = @(i) double( ...
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subs( ...
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B_c_symb, ...
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[x_var, u_var, y_var, v_var, psi_var, r_var, delta_f_var, F_x_var, F_yf_var, F_yr_var], ...
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bike_model_helper(X_ref(i,:), U_ref(i,:)) ...
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) ...
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);
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% Discrete-time LTV system
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A = @(i) eye(6) + T_s*A_c(i);
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B = @(i) T_s * B_c(i);
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end
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%% Helper Functions
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function clamped_val = clamp(val, min, max)
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clamped_val = val;
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if clamped_val < min
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clamped_val = min;
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elseif clamped_val > max
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clamped_val = max;
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end
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end
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function [x,u,y,v,psi,r,delta_f,F_x,F_yf,F_yr] = bike_model_helper(X,U)
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global Nw a b By Cy Dy Ey Shy Svy m g
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% Get state & input variables
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x = X(1);
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u = X(2);
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y = X(3);
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v = X(4);
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psi = X(5);
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r = X(6);
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delta_f = U(1);
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F_x = U(2);
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% Front and rear lateral slip angles in radians (Equations 8 & 9)
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alpha_f_rad = delta_f - atan2(v + a*r, u);
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alpha_r_rad = -atan2(v - b*r, u);
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% Convert radians to degrees for other equations
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alpha_f = rad2deg(alpha_f_rad);
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alpha_r = rad2deg(alpha_r_rad);
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% Nonlinear Tire Dynamics (Equations 6 & 7)
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phi_yf = (1-Ey)*(alpha_f + Shy) + (Ey/By)*atan(By*(alpha_f + Shy));
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phi_yr = (1-Ey)*(alpha_r + Shy) + (Ey/By)*atan(By*(alpha_r + Shy));
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% Lateral forces using Pacejka "Magic Formula" (Equations 2 - 5)
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F_zf = (b/(a+b))*(m*g);
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F_yf = F_zf*Dy*sin(Cy*atan(By*phi_yf)) + Svy;
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F_zr = (a/(a+b))*(m*g);
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F_yr = F_zr*Dy*sin(Cy*atan(By*phi_yr)) + Svy;
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% Limits on combined longitudinal and lateral loading of tires
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% (Equations 10 - 14)
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F_total = sqrt((Nw*F_x)^2 + (F_yr^2));
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F_max = 0.7*(m*g);
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if F_total > F_max
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F_x = (F_max/F_total)*F_x;
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F_yr = (F_max/F_total)*F_yr;
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end
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% Apply input limits (Table 1)
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delta_f = clamp(delta_f, delta_lims(1), delta_lims(2));
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F_x = clamp(F_x, Fx_lims(1), Fx_lims(2));
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end
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function idx = get_start_idx(i)
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global num_states num_inputs
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idx = (i-1)*(num_states+num_inputs);
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end |