**5. Experimental approach**

In order to study the impact of network utilization on closed control loop, the 2-DOF Helicopter control model is built as a NCS. Several nodes are connected through a common communication network. The experiment focuses on network scheduling, and the main objective is to balance the amount of data sent through the network, in order to avoid latency and under sampling.

The NCS for the experiment consists of 8 processors. These real-time kernel processors and the network are simulated using TrueTime [2, 12] based on Matlab/Simulink. The network used is a CSMA/AMP(CAN) with a transmission rate of 80000 bits/second, and not data loss. The NCS model is shown in Fig. 4.

**Figure 4.** Networked Control System to analyze frequency transmission over the network

Four sensor nodes execute periodic tasks to sense control signals, as well as other additional periodic tasks. Each task has a period *pi* and time consumption *ci* (Fig. 4). The sensed control signals are *x* = (*θ*, *ψ*, ˙ *θ*, *ψ*˙). This model has a controller node, depicted on the left side (Fig. 4). This controller takes the control law from the FF+LQR module by means of a task, which activates by event. The time consumption of the controller task is the maximum average time it takes to compute the control law. The controller node uses the values from sensors, and sends control outputs *up* and *uy*, that correspond to the pitch and yaw voltages. Two actuator nodes, located on the bottom right corner (Fig. 4), receive signals from the controller node. Finally, the scheduler node, located on the top right corner (Fig. 4), organizes the activity of the other seven nodes, and it is responsible for periodic allocation bandwidth, used by these nodes. Each node initializes, specifying the number of inputs and outputs of the respective TrueTime kernel block, defining a scheduling policy, and creating periodic tasks for the simulation. These tasks involve parameters about the periodic times and the consumption times. The task periodic times define the time interval between tasks, whereas the consumption times refer to the execution time of the task. Fig. 5 shows the 2-DOF Helicopter model, with a RTDS, where feedback control loop is closed through a communication network.

12 Will-be-set-by-IN-TECH

� 18.9 1.98 7.48 1.53 7.03 0.77 −2.22 19.4 −0.45 11.9 −0.77 7.03

> � − �

*k*15(*θ* − *θd*) +

*k*25(*θ* − *θd*) +

In order to study the impact of network utilization on closed control loop, the 2-DOF Helicopter control model is built as a NCS. Several nodes are connected through a common communication network. The experiment focuses on network scheduling, and the main objective is to balance the amount of data sent through the network, in order to avoid latency

The NCS for the experiment consists of 8 processors. These real-time kernel processors and the network are simulated using TrueTime [2, 12] based on Matlab/Simulink. The network used is a CSMA/AMP(CAN) with a transmission rate of 80000 bits/second, and not data loss.

S1 S2 S3 S4

**Figure 4.** Networked Control System to analyze frequency transmission over the network

Actuators

Four sensor nodes execute periodic tasks to sense control signals, as well as other additional periodic tasks. Each task has a period *pi* and time consumption *ci* (Fig. 4). The sensed

Network

� .

�

*k*16(*ψ* − *ψd*)

⎤ ⎥ ⎦ .

Scheduler

ctrl\_signals 3

*k*26(*ψ* − *ψd*)

*k*<sup>11</sup> *k*<sup>12</sup> *k*<sup>13</sup> *k*<sup>14</sup> *k*<sup>21</sup> *k*<sup>22</sup> *k*<sup>23</sup> *k*<sup>24</sup>

�

�

Sensors

A1 A2

1

u\_pitch1

2

u\_yaw1

Using the adequate Q and R weighting matrices, the control gain is as follows:

*Kf f mheliglcmcosθ<sup>d</sup> Kpp* 0

> ⎤ ⎥ ⎥ <sup>⎦</sup> <sup>−</sup>

⎡ ⎢ ⎣

*k* =

⎡ ⎢ ⎢ ⎣

Controller

3 x

*θ* − *θ<sup>d</sup> ψ* − *ψ<sup>d</sup>* ˙ *θ ψ*˙

Thus, the FF+LQR+I controller is:

**5. Experimental approach**

The NCS model is shown in Fig. 4.

u\_pitch

u\_yaw 1 2

and under sampling.

� *up uy* � = �

**Figure 5.** Networked control integrated into closed control loop of the 2DOF Helicopter

Changes on the real-time task parameters of the RTDS commonly impact on network utilization, and therefore, on the control performance [8, 9]. The problem to tackle, thus, is to find a proper way to schedule the common communication network of the RTDS, based on managing an accurate sampling period, capable of keeping both, the network load and required integrated performance.

A criteria to quantify the system's quality performance is the integral of the absolute value of the error (commonly expressed as IAE) is used:

$$IAE = \int\_{t\_0}^{t\_f} |e(t)| \, dt \approx \sum\_{k=k\_0}^{k\_f} |r(kh) - y(kh)|\tag{5}$$

where *r*(*t*) is reference signal or setpoint, *y*(*t*) is system output signal, *t*0(*k*0) and *tf*(*k <sup>f</sup>*) are the initial and final continuous(discrete) times of evaluation period [15].
