Prof. Bo Cai
'%3e%3cpath%20d='M22.1642%2019.0924C21.7317%2018.068%2021.1041%2017.1375%2020.3163%2016.3527C19.5309%2015.5656%2018.6006%2014.9381%2017.5766%2014.5048C17.5674%2014.5002%2017.5582%2014.4979%2017.5491%2014.4933C18.9774%2013.4616%2019.9059%2011.7811%2019.9059%209.88504C19.9059%206.74408%2017.3611%204.19922%2014.2201%204.19922C11.0792%204.19922%208.53429%206.74408%208.53429%209.88504C8.53429%2011.7811%209.46282%2013.4616%2010.8912%2014.4956C10.882%2014.5002%2010.8728%2014.5025%2010.8636%2014.5071C9.83652%2014.9404%208.91487%2015.5617%208.1239%2016.355C7.33685%2017.1404%206.70933%2018.0707%206.276%2019.0947C5.85031%2020.0972%205.62072%2021.172%205.59967%2022.2609C5.59905%2022.2853%205.60335%2022.3097%205.61229%2022.3325C5.62123%2022.3553%205.63465%2022.376%205.65174%2022.3935C5.66883%2022.4111%205.68926%2022.425%205.71182%2022.4345C5.73437%2022.444%205.7586%2022.4489%205.78308%2022.4489H7.15868C7.25956%2022.4489%207.3398%2022.3686%207.3421%2022.2701C7.38795%2020.5001%208.09868%2018.8425%209.35506%2017.5861C10.655%2016.2862%2012.3814%2015.5709%2014.2201%2015.5709C16.0588%2015.5709%2017.7852%2016.2862%2019.0852%2017.5861C20.3415%2018.8425%2021.0523%2020.5001%2021.0981%2022.2701C21.1004%2022.3709%2021.1807%2022.4489%2021.2815%2022.4489H22.6571C22.6816%2022.4489%2022.7058%2022.444%2022.7284%2022.4345C22.751%2022.425%2022.7714%2022.4111%2022.7885%2022.3935C22.8056%2022.376%2022.819%2022.3553%2022.8279%2022.3325C22.8369%2022.3097%2022.8412%2022.2853%2022.8406%2022.2609C22.8176%2021.165%2022.5907%2020.0989%2022.1642%2019.0924ZM14.2201%2013.8284C13.1678%2013.8284%2012.1773%2013.418%2011.4322%2012.6729C10.6871%2011.9278%2010.2767%2010.9374%2010.2767%209.88504C10.2767%208.83271%2010.6871%207.84227%2011.4322%207.09715C12.1773%206.35204%2013.1678%205.94165%2014.2201%205.94165C15.2724%205.94165%2016.2629%206.35204%2017.008%207.09715C17.7531%207.84227%2018.1635%208.83271%2018.1635%209.88504C18.1635%2010.9374%2017.7531%2011.9278%2017.008%2012.6729C16.2629%2013.418%2015.2724%2013.8284%2014.2201%2013.8284Z'%20fill='%238590A2'/%3e%3c/g%3e%3c/svg%3e)
Co-authors
Following
Followers
Research Focus & Metrics
Explore full metrics on Scilit
Academic Career Length
8Years (2019-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications27 May 2019 in IEEE Transactions on Automatic Control
Journal Article
This paper is concerned with state estimation for a class of hidden semi-Markov jump linear systems governed by a two-layer stochastic process in the discrete-time context. A semi-Markov chain and an observed-mode sequence constitute the lower and upper layer of the process, respectively. With the aid of the emission probability, a novel filter, which is dependent both on the elapsed time within the activated mode and on the observed mode instead of the system mode, is constructed and called observed-mode-dependent (OMD) filter. A modified $\sigma$ -error mean square stability ( $\sigma$ MSS) is proposed by considering the weight of expected operation time in each actual system mode. Based on the new $\sigma$ MSS, together with a class of Lyapunov functions depending on both the system modes and the corresponding observed ones, numerically checkable conditions on the existence of the OMD filter are presented such that the estimation error system is $\sigma$ -MSS with a prescribed H-infinity disturbance attenuation level. A numerical example is presented to demonstrate the theoretical findings.
26 May 2021 in IEEE Transactions on Fuzzy Systems
Journal Article
ZNZepeng Ning
Zepeng NingBo CaiRWRui Weng
Rui Weng
LZLixian Zhang
Lixian ZhangSSShun-Feng Su
Shun-Feng SuThis article investigates the stochastic stability analysis and stabilization problems for discrete-time Takagi–Sugeno fuzzy semi-Markov jump systems with upper-bounded sojourn time. The fuzzy rules can be different for different system modes. Consequently, the membership functions for fuzzy rules are dependent on the system modes. Allowing for the fact that semi-Markov kernel (SMK) are difficult to fully obtain in practice, the elements in the SMK of the underlying systems are deemed to be partly known, which is more general than both semi-Markov jump systems with completely available SMK and Markov jump systems with unknown transition probabilities. Afterward, the stability and stabilization conditions are established by part of the known SMK information and then by all the known SMK information. In the end, the validity and the superiority of our proposed theoretical results are exemplified via a single-link robot arm and a truck-trailer model.
12 July 2019 in IEEE Transactions on Cybernetics
Journal Article
This paper investigates the stability analysis and fuzzy control problems for a class of discrete-time fuzzy systems with hidden semi-Markov stochastic uncertainties. The nonlinear plant is described via the Takagi-Sugeno (T-S) fuzzy model, and the parameter uncertainties are represented by a hidden semi-Markov chain. Owing to the semi-Markov kernel (SMK), the probability density functions (PDFs) of sojourn time for different modes in describing the stochastic uncertainties can address different types of distributions according to different target modes. A novel Lyapunov function that depends on the hidden mode and the observed mode with the elapsed time is proposed to analyze the stability and the H ∞ performance of the fuzzy system. Then, the sufficient criteria for the elapsed time-dependent and observed-mode-dependent fuzzy controller are achieved by exploiting the observations of hidden modes, ensuring that the closed-loop system is σ-error mean square stable with guaranteed H ∞ performance. A cart-pendulum system is used to demonstrate the effectiveness and applicability of the proposed theoretical results.
27 August 2019 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
Journal Article
Bo CaiJYJianan Yang
Jianan YangSYShuai Yuan
Shuai Yuan
YSYang Shi
Yang ShiLZLixian Zhang
Lixian Zhang13 July 2020 in IEEE Transactions on Cybernetics
Journal Article
This article investigates the state estimation issue of discrete-time Takagi-Sugeno fuzzy Markov jump affine systems that cover both traditional fuzzy Markov jump systems and fuzzy affine systems as two special cases. The original system is transformed into a Markov jump piecewise-affine system that varies with different operating regions. The fuzzy rules are dependent on the system mode, and accordingly, the partition of the state space is mode dependent. To analyze the stochastic stability of the estimation error system, a novel mode-dependent piecewise Lyapunov function is constructed, in which the region indices of both the plant state and the estimator state are mode dependent. Then, the existence for a simultaneously mode-dependent and region-dependent fuzzy affine estimator is investigated by virtue of the S-procedure and ellipsoidal outer approximation such that the estimation error system is stochastically stable with a prescribed H∞ performance. In the end, an illustrative example of a tunnel diode circuit is adopted to showcase the effectiveness and practicability of the developed state estimation strategy.
2 September 2023 in International Journal of Robust and Nonlinear Control
Journal Article
Bo CaiDPDacheng Pei
Dacheng PeiAbout Me
Bo Cai received the Ph. D. degree in control science and engineering from Harbin Institute of Technology, China, in 2019. He was a visiting scholar at the department of mechanical engineering, University of Victoria, Canada, from Sep. 2017 to Oct. 2018. Since Oct. 2019, he has been with Harbin Institute of Technology, where he is currently associate professor. His research interests include hybrid systems, advanced control, and their applications in the field of specialized robots. He has published 1 monograph and 30+ papers in journals including Automatica and IEEE Transactions series, authorized 10+ national patents (3 commercialized), registered 6 software copyrights, and co-developed 1 industry standard. His honors include Wiley Highly Cited Paper Award, Outstanding Reviewer for IEEE Transactions on Cybernetics, and HIT Outstanding Doctoral Dissertation Award. He is a recipient of Heilongjiang Excellent Youth Science Fund.
Prof. Cai serves as an Associate Editor of IEEE SMC Magazine, Optimal Control Applications and Methods, International Journal of Aerospace System Science and Engineering, and served as a Guest Editor of Science China Technological Sciences. He also serves as a Publication Chair of 14th International Conference on Intelligent Control and Information Processing and Session Chairs of many IEEE International Conferences.