In terms of the process control industry, they buy PID controllers from German manufacturers and use a SCADA front-end. Don't expect this to change any time soon. There are no opportunities to design new and exciting control algorithms for that industry.

However, in robotics, (especially autonomous mobile robotics), there is plenty of scope for advanced control. I would recommend researching the dynamic control of compliant limbs and 'soft' robots, as they will be needed to interact closely with humans without danger of injuries from impacts. Care of the elderly is an obvious application for this.

PS: Oh, and hurry up, I'm not getting any younger here. :-)

In the industrial applications thye most controller type used is the PID. It is simple and it's adjustment is very simple however the advanced control method as Nero and fuzzy and others present a difficulty in the real application especially if you know that you must refers to the PID results for adjust these new controllers.

In other hand you don't found in all the PLC these new controller, that present another difficulty to the industry.

The advanced control theory are applied specially in ROBOTIC or advanced applications as renewable energy, motor control in electrical vehicle and others.

In my publications you can found many advanced methods, i think that can help you in you master or PHD.

In recent years, there has been a growing interest in using finite state models (or `discrete abstractions') for the analysis and synthesis of continuous and hybrid systems. This approach allows one to apply fully automated methods so that continuous and hybrid systems are formally verified, and to design finite state controllers that provably enforce complex, predefined specifications. There are quite some challanges, though, but that fact makes the field even more attractive as a PhD research topic, doesn't it? If you have more questions, let me know via email (i do not visit this site too often)

I totally agree with Nicholas Lee's comments on the large gap between industrial application and academic research.

Quote Nicholas's comment "In terms of the process control industry, they buy PID controllers from German manufacturers and use a SCADA front-end. Don't expect this to change any time soon."

Presently, the US National Science Foundation (NSF) funding support emphasizes the real-life applications and/or industry needs instead of pure theoretical work in control.

"The Control Systems (CS) program supports fundamental research on control theory and control technology driven by real life applications. .... that are motivated and derived from real-life applications and/or industry needs."

http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=13575

Only PID Control and Smith Predictor were listed in the “Leaders of the Pack” InTech’s 50 most influential industry innovators since the year 1774. PID Control was listed twice (the dominant control method in the industrial applications) -- (1) John G. Ziegler and Nathaniel B. Nichols and classical PID Control; (2) Karl Johan Astrom and modern PID Control

Quote Nicholas's comment "There are no opportunities to design new and exciting control algorithms for that industry."

How about combining new and exciting control algorithms with PID control to solve complex industrial control problems?

For example, Quote Ibrahim Jasim's follow-up comment "PID controllers are not suited for others like for example systems with unknown parameters, ... etc". Iterative feedback tuning (IFT) was proposed to tune controller parameters for system with unknown parameters. A linear control model can be used to approximate non-linear system with unknown parameters roughly, and such control plant approximation may exist large deviation from the real non-linear system, which would cause the classical tuning method of PID controller ineffective. IFT was proposed to minimize a given quadratic cost function of the system output error and control effort, thus solving the controller tuning issues caused by plant uncertainty.

By cooperating with researchers worldwide including Stanford University researcher, H. Hjalmarsson integrated iterative feedback tuning with PID controller to solve controller tuning issues caused by plant uncertainty. H. Hjalmarsson was elected to the Class of 2013 IEEE fellow due to his fundamental contribution to iterative feedback tuning.

"Relay auto-tuning of PID controllers using iterative feedback tuning," Automatica 39 (1), January 2003, pp. 149-157.

(1) For industrial control community,

Only PID Control and Smith Predictor were listed in the “Leaders of the Pack” InTech’s 50 most influential industry innovators since the year 1774. Available from the following link.

https://archive.today/2RoSK

PID Control was listed twice (the dominant control method in the industrial applications) -- (1) John G. Ziegler and Nathaniel B. Nichols and classical PID Control; (2) Karl Johan Astrom and modern PID Control (IEEE Medal of Honor, 1993)

http://en.wikipedia.org/wiki/IEEE_Medal_of_Honor

The next popular method is Smith Predictor: Otto J.M. Smith and Smith Predictor.

http://en.wikipedia.org/wiki/Otto_J._M._Smith

A typical PID tuning procedure: (1) Use relay control to estimate the control model (or control plant); (2) Use Z-N formula to initialize Kp and Ki; (3) use trial and error to adjust Kp and Ki or other method such as iterative feedback tuning (IFT), internal model control (IMC), etc.

H. Hjalmarsson was elected to the Class of 2013 IEEE fellow due to his fundamental contribution to iterative feedback tuning. The key contribution of IFT is tuning controller parameters for those control model (or control plant) whose parameters are difficult to be identified relatively accurately, in other words, iterative feedback tuning was proposed to minimize a given quadratic cost function of the system output error and control effort, thus solving the controller tuning issues caused by plant uncertainty.

H. Hjalmarsson, M. Gevers, S. Gunnarsson, and O. Lequin, "Iterative feedback tuning: theory and applications," IEEE Control Systems Magazine, vol.18, no.4, Aug 1998, pp .26-41,

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=710876

[HHHHD03] W.K. Ho, Y. Hong, A. Hansson, H. Hjalmarsson, and J.W. Deng, "Relay auto-tuning of PID controllers using iterative feedback tuning," Automatica 39 (1), January 2003, pp. 149-157. Available in the following RG Link.

https://www.researchgate.net/publication/223504459_Relay_auto-tuning_of_PID_controllers_using_iterative_feedback_tuning

The paper [SLY17] extends iterative feedback tuning PID controller proposed by [HHHHD03] to enhance the handling and stability performance of an in-wheel motor-driven electric vehicle.

Note that an autonomous car can be classified as an in-wheel motor-driven vehicle.

[SLY17] Y. Shi, Q. Liu, and F. Yu, "Design of an Adaptive FO-PID Controller for an In-Wheel-Motor Driven Electric Vehicle," SAE  International Journal of Commercial Vehicles, 10(1), March 2017, pp. 265-274.http://papers.sae.org/2017-01-0427/

W.K. Ho, T.H. Lee, H.P. Han, and Y. Hong, "Self-Tuning IMC-PID Control with Interval Gain and Phase Margin Assignment," IEEE Transactions on Control Systems Technology, 9(3), May 2001, pp. 535-541. Available in the following RG Link.

H. Nyquist (Sweden) --> K.J. Astrom (Sweden) --> W.K. Ho (Sweden)  

     | Nyquist plot (published in 1932) 

     |  Bell Labs    

    V  Bode plot (published in 1940)

H.W. Bode (Harvard) --> K.S. Narendra (Harvard, Yale) --> T.H. Lee (Yale)

https://www.researchgate.net/publication/3332273_Self-tuning_IMC-PID_control_with_interval_gain_and_phase_marginsassignment

C.C. Hang, K.J. Astrom, and W.K. Ho, "Refinements of the Ziegler-Nichols tuning formula," IEE Proceedings on Control Theory and Applications, 138(2), March 1991, pp.111-118.

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=67610

This paper and selected classic PID tuning methods (co-invented by K.J. Astrom and his student W.K. Ho) have been implemented by Maplesoft Inc. for MapleSim Control Design Toolbox

http://www.maplesoft.com/support/help/MapleSim/view.aspx?path=ControlDesign/GainPhaseMargin

K.J. Astrom, T. Hagglund, C.C. Hang, and W.K. Ho, "Automatic tuning and adaptation for PID controllers - a survey," Control Engineering Practice, 1(4), August 1993, pp.699-714.

http://www.sciencedirect.com/science/article/pii/096706619391394C

K.J. Astrom, C.C. Hang, P. Persson, and W.K. Ho, "Towards intelligent PID control," Automatica, 28(1), January 1992, pp.1-9.

http://www.sciencedirect.com/science/article/pii/000510989290002W

Control theoretic approaches have been applied to model the interactions between an overloaded SIP server and its upstream servers as a feedback control system in two different scenarios - round trip delay control (IEEE ICC 2011) and redundant retransmission ratio control (IEEE Globecom 2010).

Round-Trip Delay Control (RTDC, implicit SIP overload control) algorithm: Y. Hong, C. Huang, and J. Yan, "Design Of A PI Rate Controller For Mitigating SIP Overload," Proceedings of IEEE ICC, Kyoto, Japan, June 2011.

https://www.researchgate.net/publication/224249824_Design_of_a_PI_Rate_Controller_for_Mitigating_SIP_Overload

RTDC implicit SIP overload control algorithm has been recommended as White Paper by TechRepublic (CBS Interactive)

http://www.techrepublic.com/whitepapers/design-of-a-pi-rate-controller-for-mitigating-sip-overload/25142469

IEEE ICC 2011 presentation slides for RTDC implicit SIP overload control can be downloaded from the following RG link.

https://www.researchgate.net/publication/257945199_Round-Trip_Delay_Control_(RTDC)_For_Mitigating_SIP_Overload_(IEEE_ICC_2011_Slides)

Redundant Retransmission Ratio Control (RRRC, implicit SIP overload control) algorithm: [HHY10] Y. Hong, C. Huang, and J. Yan, "Mitigating SIP Overload Using a Control-Theoretic Approach," Proceedings of IEEE Globecom, Miami, FL, U.S.A, December 2010.

https://www.researchgate.net/publication/221284946_Miigating_SIP_Overload_Using_a_Control-Theoretic_Approach

RRRC implicit SIP overload control algorithm has been quickly adopted by The Central Weather Bureau of Taiwan for their early earthquake warning system.

T.Y. Chi, C.H. Chen, H.C. Chao, and S.Y. Kuo, "An Efficient Earthquake Early Warning Message Delivery Algorithm Using an in Time Control-Theoretic Approach", 2011.

http://link.springer.com/chapter/10.1007%2F978-3-642-23641-9_15#

http://www.ipv6.org.tw/docu/elearning8_2011/1010004798p_3-7.pdf

Short review and comments on RRRC (implicit SIP overload control) algorithm by the former IEEE TAC Associate Editor S. Mascolo (Google Faculty Research Award 2014 ) with reference to three papers [HHY10], [HHY12], and [HHY13]:

L. De Cicco, G. Cofano, and S. Mascolo,"Local SIP Overload Control: Controller Design and Optimization by Extremum Seeking", IEEE Transactions on Control of Network Systems, Vol. 2, Issue 3, September 2015, pp. 267-277.

http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7035079

http://c3lab.poliba.it/images/f/f4/Dcm-tcns15.pdf

Google Faculty Research Award 2014 List

http://services.google.com/fh/files/blogs/googlefras-aug2014.pdf 

IEEE GLOBECOM 2010 presentation slides for RRRC implicit SIP overload control can be downloaded from the following RG link.

https://www.researchgate.net/publication/258555827_Mitigating_SIP_Overload_Using_a_Control-Theoretic_Approach

Journal paper (SIP Overload Control) not only conducts more theoretical analysis of Round trip delay control (RTDC) and Redundant retransmission ratio control (RRRC), but also discusses how to apply RTDC algorithm to mitigate SIP overload for both SIP over UDP and SIP over TCP (with TLS).

[HHY13] Y. Hong, C. Huang, and J. Yan, "Applying control theoretic approach to mitigate SIP overload", Telecommunication Systems, 54(4), December 2013, pp. 387-404.

https://www.researchgate.net/publication/257667871_Applying_control_theoretic_approach_to_mitigate_SIP_overload

http://link.springer.com/article/10.1007/s11235-013-9744-8

Survey on SIP overload control algorithms: [HHY12] Y. Hong, C. Huang, and J. Yan, "A Comparative Study of SIP Overload Control Algorithms", IGI Global, 2012, pp. 1-20.

http://www.researchgate.net/publication/231609451_A_Comparative_Study_of_SIP_Overload_Control_Algorithms

http://www.igi-global.com/chapter/comparative-study-sip-overload-control/67496

Open-source SIP/VoIP project discussion archive

http://lists.sip-router.org/pipermail/sr-users/2013-April/077596.html

IETF-RFC "SIP Overload Control" discussion archive

http://www.ietf.org/mail-archive/web/sip-overload/current/msg00919.html

API-RCP(TCP Congestion Control):Y. Hong and O.W.W. Yang, "Design of Adaptive PI Rate Controller for Best-Effort Traffic in the Internet Based on Phase Margin," IEEE Transactions on Parallel and Distributed Systems, 18(4), April 2007, pp. 550-561.

http://www.researchgate.net/publication/3301176_Design_of_Adaptive_PI_Rate_Controller_for_Best-Effort_Traffic_in_the_Internet_Based_on_Phase_Margin

2 double-column pages Review, Comments, and Extensive Evaluation on API-RCP: H. Zhou, C. Hu, and L. He, "Improving the Efficiency and Fairness of eXplicit Control Protocol in Multi-Bottleneck Networks", Elsevier Computer Communications, 36(10-11), June 2013, pp. 1193-1208.

http://www.sciencedirect.com/science/article/pii/S0140366413001059

Real-world Linux implementation of API-RCP: Z. Liu, H. Wang, W. Hu, Y. Hong, O.W.W. Yang, and Y. Shu, "An Implementation and Experimental Study of the Adaptive PI Rate Control Protocol," Proceedings of IEEE HPSR, Paris, France, June 2009. The leading author Zhanliang Liu is Principle Engineer at Baidu, former Principle Engineer at Tencent, former software engineer at Microsoft.

https://www.researchgate.net/publication/224611517_An_implementation_and_experimental_study_of_the_Adaptive_PI_Rate_Control_Protocol

API-RCP (adaptive PI rate control algorithm) has been extended to vehicle traffic congestion management in vehicular ad-hoc networks (or a driveless car network)

B.K. Mohandas, R. Liscano, and O.W.W. Yang, "Vehicle traffic congestion management in vehicular ad-hoc networks", IEEE 34th Conference on Local Computer Networks (LCN 2009), 2009. http://ieeexplore.ieee.org/document/5355052/

API-RCP has been reviewed by the milestone paper [HCLMMWY10] which highligts AUTO21 research projects.

[HCLMMWY10] E. Hossain, G. Chow, V.C.M. Leung, R.D. McLeoda, J. Mišićd, V.W.S.Wong, and O. Yang, "Vehicular telematics over heterogeneous wireless networks: A survey", Computer Communications, 33(7), May 2010, pp. 775-793. http://www.sciencedirect.com/science/article/pii/S0140366410000022

Industry Canada has announced a five-year $145-million Automotive R&D Partnership Initiative to help the automotive sector address its innovation, productivity and competitiveness challenges. NRC is one of the main players in this initiative, investing an additional $30 million over the next five years in automotive R&D projects. https://www.nrc-cnrc.gc.ca/eng/achievements/highlights/2008/canada_automotive_industry.html

(2) For academic control community,

ACC 2012 Plenary and Semi-Plenary Lectures

Plenary: Accomplishments and Prospects of Control

Abstract: There are many success stories and major achievements in control, something remarkable for a field as young as 50 years. In this talk we will sample these accomplishments and speculate about the future prospects of control. While there are examples of feedback from ancient times, extensive use of feedback paralleled industrialization: steam, electricity, communication, transportation etc. Control was established as a field in the period 1940-1960, when the similarities of control in widely different fields were recognized. Control constituted a paradigm shift in engineering that cut across the traditional engineering disciplines: mechanical, electrical, chemical, aerospace. A holistic view of control systems with a unified theory emerged in the 1950s, triggered by military efforts during the Second World War. The International Federation of Automatic Control (IFAC) was formed in 1956. Education in control spread rapidly to practically all engineering disciplines. Conferences and journals also appeared. A second phase, driven by the space race and the emergence of computers, started around 1960. Theory developed dramatically as did industrial applications. A large number of sub-specialties appeared and perhaps due to this, the holistic view of the field was lost. In my opinion we are now entering a third phase driven by the ubiquitous use of control and a strong interest in feedback and control among fellow scientists in physics and biology. There are also new areas driven by networked systems, autonomy and safe design of large complex systems. What will happen next depends largely on how we respond to the new challenges and on how we manage to recapture the holistic view of systems. Key issues will be education and interaction with other disciplines.

Semi-Plenary Lectures also discuss promising research topics.

 http://a2c2.org/conferences/acc2012/plenary.php

8 wonderful presentations in control symposium "Paths Ahead in the Science of Information and Decision Systems", Massachusetts Institute of Technology (MIT), USA, November 12 – 14, 2009.

http://paths.lids.mit.edu/papers_mitter.html

Panel on Future Directions in Control, Dynamics, and Systems, Richard M. Murray (chair), California Institute of Technology, April 2002

http://www.cds.caltech.edu/~murray/cdspanel/

R. Murray, K. Astrom, S. Boyd, R. Brockett, and G. Stein, "Future Directions in Control in an Information-Rich World," IEEE Control Systems Magazine, 23(2), April 2003, pp.20-33.

http://www.stanford.edu/~boyd/papers/cds_panel.html

To celebrate the golden anniversary, IFAC Automatica has published in the 50th volume throughout the year 2014, special survey/overview papers, on selected topics, some tracing the history on some mature topics and areas, others focusing on newly emerging areas, with forecasts into the future. The survey paper published by the 1st issue provides an overview of the developments in the control field from its early days.

K.J. Astrom and P.R. Kumar, "Control: A Perspective," Automatica, 50(1), January 2014, pp. 3-43.

http://www.sciencedirect.com/science/article/pii/S0005109813005037

(3) Control Theory developed in the twentieth century: 25 Seminal Papers selected by IEEE Control Society in 2000

Control Theory: Twenty-Five Seminal Papers (1932-1981), Edited by T.S. Basar, Wiley-IEEE Press, 2000. 

http://www.ebay.com/ctg/Control-Theory-Twenty-Five-Seminal-Papers-1932-1981-by-Inc-Staff-IEEE-2000-Hardcover-/1776728

http://www.amazon.ca/Control-Theory-Twenty-Five-Seminal-1932-1981/dp/0780360214

IEEE Control Systems Award

http://en.wikipedia.org/wiki/IEEE_Control_Systems_Award

IFAC Giorgio Quazza Medal

http://www.ifac-control.org/awards/major-medals

4 co-authors of 25 Seminal Papers (1932-1981) awarded IEEE Medal of Honor (the highest IEEE award): Nyquist(1960), Kalman(1974), Bellman(1979), Astrom(1993), i.e., NBA (Sweden) and Kalman

http://www.ieee.org/about/awards/medals/medalofhonor.html

R.E. Bellman and K.J. Astrom, "On structural identifiability," Mathematical Biosciences, 7(3-4), 1970, pp. 329–339.

http://www.sciencedirect.com/science/article/pii/002555647090132X

Richard E. Bellman Control Heritage Award for US control systems engineers and scientists (US citizenship only)

http://a2c2.org/awards/richard-e-bellman-control-heritage-award

Ragazzini's notable students are Rudolf Kalman (see Kalman filters), Eliahu Ibraham Jury (see Z-transform) and Lotfi Asker Zadeh (see Fuzzy sets and Fuzzy logic).

https://en.wikipedia.org/wiki/John_Ragazzini

K. Astrom, E.I. Jury, and R. Agniel, "A numerical method for the evaluation of complex integrals," IEEE Transactions on Automatic Control, vol.15, no.4, Aug 1970, pp.468-471.

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1099492

"To control theorists, Nyquist is no doubt best known as the inventor of the Nyquist diagram, defining the conditions for stability of negative feedback systems. This has become a foundation stone for control theory the world over, applicable in a much wider range of situations than that for which it was originally enunciated." Hendrik W. Bode, Harvard University, USA, 1977.

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1101666

Biography of Harry Nyquist, University of Cambridge, UK, 2003

"Between 1920 and 1940 he published a series of papers on research in telecommunications which are arguably the most outstanding set of scientific contributions since Newton (apart from Einstein!)."

http://babylon.acad.cai.cam.ac.uk/students/study/engineering/engineer03l/cenyquist.htm

http://babylon.acad.cai.cam.ac.uk/students/study/engineering/engineer03l/ceframes.htm

K.J. Astrom, "Harry Nyquist (1889-1976): A Tribute to the Memory of an Outstanding Scientist," Royal Swedish Academy of Engineering Sciences, 2003.

American Society of Mechanical Engineers (ASME) Nyquist Lecturer Award

https://www.asme.org/about-asme/get-involved/honors-awards/unit-awards/nyquist-lecturer

Article Design of Adaptive PI Rate Controller for Best-Effort Traffi...

Article Self-tuning IMC-PID control with interval gain and phase mar...

Conference Paper Mitigating SIP Overload Using a Control-Theoretic Approach.

Article Relay auto-tuning of PID controllers using iterative feedback tuning

Conference Paper Design of a PI Rate Controller for Mitigating SIP Overload

Conference Paper An implementation and experimental study of the Adaptive PI ...

Article A Comparative Study of SIP Overload Control Algorithms

Article Applying control theoretic approach to mitigate SIP overload

Data Round-Trip Delay Control (RTDC) For Mitigating SIP Overload ...

Data Mitigating SIP Overload Using a Control-Theoretic Approach

I agree with Yang Hong, combining classical PID controller with sort of auto-tuning algorithm would be an interesting topic especially for industrial applications. The auto-tuning could be done in such a way that a degree of robustness to plant uncertainties is preserved. Also, in some applications we might need to optimize the control effort according to some objective(s) and constraints (i.e. actuator limitations). But again the real time applicability pops up as a critical issue whenever the controller structure is manupilated online. Also I think AC drives control is a hot topic, especially in renewable energy.

Application of control theory in making soft computing control based industrial robots could be the right option for your background & interest

From plant modelling perspective, a physical models of automobiles , air crafts etc can be chosen.. In automobile industries, no kind of control algorithm has been implemented. The challenge really lies in taking control algorithms for various real time automotive applications.

For mechanical side hybrid vehicles and hybrid dynamics estimation and control is also interested area.

For a mechatronics graduate...control theory brings very interesting perspective in automobile sector...many non linear controllers can be used for closed loop control of air-fuel ratio, anti lock braking system, electronic clutch control etc....electronic control units(ECU) are there for automatic parking,traction control,cruise control and many such advanced security systems. So in my point of view developing new techniques in these areas will be a good step towards completely automatic vehicles.

@Madan Rayguru : I would disagree with your point maybe.. From a research perspective your ideas would be path-breaking but ideas shouldn't be inside text books alone.. Try to make your algorithms into an implementable one.. And that's how engineering can help the society..

And control algorithm development inside a car / bike is in a very very nascent stages in automobile sectors.. All I could say is advanced control engineering concepts are there in Aerospace sector / unmanned robot development.. Probably control system concepts can be applied in real time..

Despite the efficiency of PID controllers in many applications, they are not suited for others like for example wider operational mode, systems with unknown parameters, systems with time varying parameters...etc. I belive that industry is opt to use this kind of controllers because of its simplicity to be understood. More powerful adaptive control strategies are more efficient and not that costy from the money and computational prospectives. Still they are difficult to be understood by a large number of individuals in industry due to the use of advanced mathematical concepts in its evolution.

Back to the question in hand, there are different fields through which you can find advanced control schemes in industry like for example observer- based fault detection that is currently used in airplane and power systems faults detection, adaptive control strategies that are being used in compliant motion robots, friction estimation,...etc.

Yes , you can use the fuzzy logic for control industrial application and academic research.

I chose Finite-Time control to focus on for my thesis. My advisor, Dr. Chunjiang Qian, has made great strides in implementing this very robust form of control into more industrial/robot applications. It has been around for a few years, but mainly only the in the academic world.

As a control system engineer, i suggested that Optimal Control and Biomechanism is best. But as far as time goes people are used Computational Mechanics for different type of models in Natural Systems.

Stay in the field of mechatronics and modern control theories in nonlinear systems and optimal systems! You have got some suggestions above by Prof. Olfa Boubaker. You are going to be strong for Ph.D. research since You stay in the same research trajectory. Good luck! Results will come!

Sincerely,

Ljubomir Jacic

...Follow your heart, if you want to continue with research. I pressume you have been exposed to a number of control theoretic approaches and applications, we may tell you an area but it is you who decide (remember you will study for some years as PhD student!). It is up to you to decide if you want to move towards a more theoretical research point of view or more practical (applied control to an application). You have background in mechatronics, have you looked? into micro-systems control (relates to mechatronics)...

Thanks  everybody for your answers. Sinc february 2015 I have been pursuing my PhD in systems and control under supervision of prof.dr. Arjan van der Schaft and prof.dr. Bayu Jayawardhana. I am working on tracking control of physical systems. 

Usually people do the following exercise :

1. check recent projects related to non-linear control on the websites of famous universities

2. read the recent papers of highly ranked journals e.g automatica, cybernetics, automatic control, etc.

3. read the news related to recent advancements in the applications of control such as robotics, etc

From my point of view, the applications of control algorithms such as nonlinear, optimal and fuzzy controllers in other fields such as biomedical, medical robotics and nanotechnology along with control of cooperative systems have a long path away and many researches could be done in these areas, but it depends the interest of researchers too.