TAILIEUCHUNG - Robot Learning 2010 Part 11

Tham khảo tài liệu 'robot learning 2010 part 11', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Multi-Robot Systems Control Implementation 143 Once we have seen that the respone is unstable we decide to use Model Predictive Control. To work with this kind of control we have to stablish the working point. To do this we examine the Bode diagram of the Fig. 3 and we choose the frecuency of the marked point of this figure. Once we have determined the working point in Fig. 3 we design the reference signal. As it is shown in Fig. 4 using a properly tuned DMC predictive controller for example with the values for its parameters p 5 m 3 y Ằ 1 a right control is obtained. To get this control it has been mandatory to tune the DMC controller. This phase is very expensive in computationally terms but it s carried out only one time. However the computational requirements of DMC controller are great when it s in its working phase due to the operations that it must perform to get the control law and although it obtains set of m control signals only first of them is used in this sample time the rest are ignored. Because of this it would be convenient to have a mechanism that could implement such controller requiring less computational power. Besides it may be necessary to control several subsystems of this kind in each robot of the multi-robot team. An alternative to get this is to use neural networks and more precisely Time Delayed Neural Networks because as the rest of neural networks they are very fast and they have the ability of generalizing their responses. In the literature there are works comparing PID and MPC controllers Voicu et al. 1995 . Now we deal with the concrete problem of getting a neuronal predictive controller that could control the system described by the discrete transfer function of the equation 7 using Time Delayed Neural Networks. Fig. 2. Unstable response of the subsystem under the control of a discrete PID controller. 144 Robot Learning Bode Diagram Frequency rad sec Fig. 3. Bode diagram of the subsystem showing the chosen point. Fig. 4. Control of

TỪ KHÓA LIÊN QUAN
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.