Although it's not hard to find papers like you have shown at 13 mins 25 seconds if possible kindly include the paper links in the description below the video. Thanks
Thanks Rasit. Model Reference Adaptive Control (MRAC) principle will be posted on June 29 with the title Reference Point vs Reference Model. In that video, I will explain the importance of MRAC. The following videos will build upon the MRAC principle based on its advantages to be discussed on the June 29th video and its Matlab example to be posted on the July 2nd video. So stay tuned for MRAC ;) About Model Identification Adaptive Control (MIAC), here is my brief explanation: 1) Consider dx/dt=Ax+Bu. Say A and B are unknown. 2) In a MIAC scheme, we first estimate A and B in an adaptive way. 3) Then, say, for each A and B estimate, we solve linear quadratic cost function to come up with stabilizing gain K. 4) The main assumptions are 4a) Initial gain K is a stabilizing choice and 4b) If the system is Persistently Exciting (PE), then we improve this K because A and B estimates will converge to their unknown values under the PE condition. 5) Now, without PE, closed-loop performance can be poor. 6) In contrast to MIAC, you don't need PE to achieve closed-loop system error (the error between actual states and reference model states) converge to zero. 7) From this standpoint, I always found MRAC to be more practical than MIAC. Finally, let me know if you want to follow up ;)
Hİ Professor @Tansel Yucelen . Thank you for your valuable comment! Maybe in MIAC processes, we can incorporate a recursive identification method such as RLSE to enhance the accuracy of finding system parameters. Is this statement correct? Although I do not directly work on Adaptive & Robust control, I specialize in Optimal control, which was the focus of my MSC thesis. However, I thoroughly understood every detail in your explanation. I will eagerly await your video.
👍 Yes, all theoretical topics will include explicit codes, where codes will be fully visible on videos. For example, on this Thursday, I will cover the very first adaptive control law. On Sunday, its numerical example will be published with a code on it. I will proceed like this for other upcoming topics.