Why is my PID controlled state space model always unstable?

My matrix A is a 6x6 matrix and my matrix B is a 6x1 matrix. I tried several different gains and no gain ever works.

The setpoint is a certain position where my system should stabilize.

class PIDController:    def __init__(self, Kc, Ti, Td, setpoint, A, B, C, D):        #initializing, for example:    def compute(self, current_value, current_time):        error = self.setpoint - current_value[0]          delta_time = current_time - self.prev_time        self.prev_time = current_time        # Proportional term        proportional = self.Kc * error        self.proportional_values.append(proportional)          # Integral term        self.integral += error * delta_time        self.integral_values.append(self.integral)  # Store integral term        # Derivative term        self.derivative = (error - self.prev_error) / delta_time        self.derivative_values.append(self.derivative)          self.prev_error = error        pid_output = proportional + self.Kc/self.Ti * self.integral + self.Kc * self.Td * self.derivative        # State-space model simulation        # x_next is most important. output is just a chosen var from via the C matrix        x_next = np.dot(self.A, current_value) + self.B * pid_output        output = np.dot(self.C, current_value) + self.D * pid_output        self.r_values.append(current_value[0])        self.error_values.append(error)        return output, x_next

I tried adjusting gains ranging from 0.001 - 1000. My system will oscillate for around 6-7 iterations and will then go to infinity very quickly.