{"title":"Robust adaptive estimator based on a novel objective function—Using the L1-norm and L0-norm","authors":"Sihai Guan , Chuanwu Zhang , Guofu Wang , Bharat Biswal","doi":"10.1016/j.jai.2023.06.004","DOIUrl":"https://doi.org/10.1016/j.jai.2023.06.004","url":null,"abstract":"<div><p>To fully take advantage of LMS, LMAT, and SELMS, a novel adaptive estimator using the L1-norm and L0-norm of the estimated error is proposed in this paper. Then based on minimizing the mean-square deviation at the current time, the optimal step-size, parameters <span><math><mi>δ</mi></math></span> and <span><math><mi>θ</mi></math></span> of the proposed adaptive estimator are obtained. Besides, the stability and computational complexity of the mean estimation error is analyzed theoretically. Experimental results (both simulation and real mechanical system datasets) show that the proposed adaptive estimator is more robust to input signals and a variety of measurement noises (Gaussian and non-Gaussian noises). In addition, it is superior to LMS, LMAT, SELMS, the convex combination of LMS and LMAT algorithm, the convex combination of LMS and SELMS algorithm, and the convex combination of SELMS and LMAT algorithm. The theoretical analysis is consistent with the Monte-Carlo results. Both of them show that the adaptive estimator has an excellent performance in the estimation of unknown linear systems under various measurement noises.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 2","pages":"Pages 105-117"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xinxin Shang , Songlin Zhuang , Tianyu Tan , Yang Shi
{"title":"Error reachable set based stabilization of switched linear systems with bounded peak disturbances","authors":"Xinxin Shang , Songlin Zhuang , Tianyu Tan , Yang Shi","doi":"10.1016/j.jai.2023.06.001","DOIUrl":"https://doi.org/10.1016/j.jai.2023.06.001","url":null,"abstract":"<div><p>This paper investigates the error reachable set based stabilization problem for a class of discrete-time switched linear systems with bounded peak disturbances under persistent dwell-time (PDT) constraint. A double-clock-dependent control scheme is presented that can split the disturbed switched system into a nominal system and an error system, and assign to each system a controller scheduled by a clock. A necessary and sufficient convex stability criterion is presented for the nominal system, and is further extended to the stabilization controller design with a nominal clock. In the presence of bounded peak disturbances, another stabilization controller with an error clock is developed for the error system, with the purpose of “minimizing” the reachable set of the error system by the ellipsoidal techniques. It is demonstrated that the disturbed system is also globally exponentially stable in the sense of converging to an over approximation of the reachable set of the error system, i.e., a union of a family of bounding ellipsoids, that can also be regarded as the cross section of a tube containing the trajectories of the disturbed system. Two numerical examples are provided to verify the effectiveness of the developed results.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 2","pages":"Pages 87-98"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evolutionary games and spatial periodicity","authors":"Te Wu , Feng Fu , Long Wang","doi":"10.1016/j.jai.2023.05.001","DOIUrl":"https://doi.org/10.1016/j.jai.2023.05.001","url":null,"abstract":"<div><p>Spatial interactions are considered an important factor influencing a variety of evolutionary processes that take place in structured populations. It still remains an open problem to fully understand evolutionary game dynamics on networks except for certain limiting scenarios such as weak selection. Here we study the evolutionary dynamics of spatial games under strong selection where strategy evolution of individuals becomes deterministic in a fashion of winners taking all. We show that the long term behavior of the evolutionary process eventually converges to a particular basin of attraction, which is either a periodic cycle or a single fixed state depending on specific initial conditions and model parameters. In particular, we find that symmetric starting configurations can induce an exceedingly long transient phase encompassing a large number of aesthetic spatial patterns including the prominent kaleidoscopic cooperation. Our finding holds for any population structure and a broad class of finite games beyond the Prisoner’s Dilemma. Our work offers insights into understanding evolutionary dynamics of spatially extended systems ubiquitous in biology and ecology.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 2","pages":"Pages 79-86"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spline adaptive filtering algorithm based on different iterative gradients: Performance analysis and comparison","authors":"Sihai Guan , Bharat Biswal","doi":"10.1016/j.jai.2022.100008","DOIUrl":"https://doi.org/10.1016/j.jai.2022.100008","url":null,"abstract":"<div><p>Two novel spline adaptive filtering (SAF) algorithms are proposed by combining different iterative gradient methods, i.e., Adagrad and RMSProp, named SAF-Adagrad and SAF-RMSProp, in this paper. Detailed convergence performance and computational complexity analyses are carried out also. Furthermore, compared with existing SAF algorithms, the influence of step-size and noise types on SAF algorithms are explored for nonlinear system identification under artificial datasets. Numerical results show that the SAF-Adagrad and SAF-RMSProp algorithms have better convergence performance than some existing SAF algorithms (i.e., SAF-SGD, SAF-ARC-MMSGD, and SAF-LHC-MNAG). The analysis results of various measured real datasets also verify this conclusion. Overall, the effectiveness of SAF-Adagrad and SAF-RMSProp are confirmed for the accurate identification of nonlinear systems.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 1","pages":"Pages 1-13"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Autonomous exploration using UWB and LiDAR","authors":"Mingyang Guan , Changyun Wen","doi":"10.1016/j.jai.2022.100006","DOIUrl":"https://doi.org/10.1016/j.jai.2022.100006","url":null,"abstract":"<div><p>In autonomous exploration, a robot navigates itself in an unknown environment while building a 2D map of the environment. This is typically done using a LiDAR sensor, which however is susceptible to error accumulation. To handle this issue, a UWB/LiDAR fusion SLAM is proposed, which can be decoupled into a localization problem and a mapping problem. For localization problem, we firstly apply extended Kalman filter (EKF) to localize all UWB beacons and then use particle filter (PF) to estimate the robot’s state based on the two on-board UWB nodes’ estimated locations. For mapping problem, we firstly fine-tune the robot’s state using a recursive adaptive-trust-region scan matcher, which is termed as RASM, and then construct the map based on the refined robot’s state. We also propose a method to correct UWB beacons’ locations using the robot’s refined location. Furthermore, the information obtained from the proposed fusion SLAM is utilized to sketch the region where the robot is going to explore next. That is, a where-to-explore strategy is proposed to guide the robot to the less-explored areas. Overall, the proposed exploration system is infrastructure-less and avoid mapping error to accumulate over time. Extensive experiments with comparisons to the state-of-the-art methods are conducted in two different environments: a cluttered workshop and a spacious garden in order to verify the effectiveness of our proposed strategy. The experimental tests are filmed and the video is available in the supplementary materials.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 1","pages":"Pages 51-60"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49757504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cost-effective distributed FTFC for uncertain nonholonomic mobile robot fleet with collision avoidance and connectivity preservation","authors":"Xiucai Huang , Zhengguo Li , Frank L. Lewis","doi":"10.1016/j.jai.2023.100021","DOIUrl":"https://doi.org/10.1016/j.jai.2023.100021","url":null,"abstract":"<div><p>In this paper, the fault-tolerant formation control (FTFC) problem is investigated for a group of uncertain nonholonomic mobile robots with limited communication ranges and unpredicted actuator faults, where the communication between the robots is in a directed one-to-one way. In order to guarantee the connectivity preservation and collision avoidance among the robots, some properly chosen performance functions are incorporated into the controller to per-assign the asymmetrical bounds for relative distance and bearing angle between each pair of adjacent mobile robots. Particularly, the resultant control scheme remains at a cost-effective level because its design does not use any velocity information from neighbors, any prior knowledge of system nonlinearities or any nonlinear approximator to account for them despite the presence of modeling uncertainties, unknown external disturbances, and unexpected actuator faults. Meanwhile, each follower is derived to track the leader with the tracking errors regarding relative distance and bearing angle subject to prescribed transient and steady-state performance guarantees, respectively. Moreover, all the closed-loop signals are ensured to be ultimately uniformly bounded. Finally, a numerical example is simulated to verify the effectiveness of this methodology.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 1","pages":"Pages 42-50"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bo Xiao , H.K. Lam , Xiaojie Su , Ziwei Wang , Frank P.-W. Lo , Shihong Chen , Eric Yeatman
{"title":"Sampled-data control through model-free reinforcement learning with effective experience replay","authors":"Bo Xiao , H.K. Lam , Xiaojie Su , Ziwei Wang , Frank P.-W. Lo , Shihong Chen , Eric Yeatman","doi":"10.1016/j.jai.2023.100018","DOIUrl":"https://doi.org/10.1016/j.jai.2023.100018","url":null,"abstract":"<div><p>Reinforcement Learning (RL) based control algorithms can learn the control strategies for nonlinear and uncertain environment during interacting with it. Guided by the rewards generated by environment, a RL agent can learn the control strategy directly in a model-free way instead of investigating the dynamic model of the environment. In the paper, we propose the sampled-data RL control strategy to reduce the computational demand. In the sampled-data control strategy, the whole control system is of a hybrid structure, in which the plant is of continuous structure while the controller (RL agent) adopts a discrete structure. Given that the continuous states of the plant will be the input of the agent, the state–action value function is approximated by the fully connected feed-forward neural networks (FCFFNN). Instead of learning the controller at every step during the interaction with the environment, the learning and acting stages are decoupled to learn the control strategy more effectively through experience replay. In the acting stage, the most effective experience obtained during the interaction with the environment will be stored and during the learning stage, the stored experience will be replayed to customized times, which helps enhance the experience replay process.</p><p>The effectiveness of proposed approach will be verified by simulation examples.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 1","pages":"Pages 20-30"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Towards cognitive navigation: A biologically inspired calibration mechanism for the head direction cell network","authors":"Zhenshan Bing , Dominik Nitschke , Genghang Zhuang , Kai Huang , Alois Knoll","doi":"10.1016/j.jai.2023.100020","DOIUrl":"https://doi.org/10.1016/j.jai.2023.100020","url":null,"abstract":"<div><p>To derive meaningful navigation strategies, animals have to estimate their directional headings in the environment. Accordingly, this function is achieved by the head direction cells that were found in mammalian brains, whose neural activities encode one’s heading direction. It is believed that such head direction information is generated by integrating self-motion cues, which also introduces accumulative errors in the long term. To eliminate such errors, this paper presents an efficient calibration model that mimics the animals’ behavior by exploiting visual cues in a biologically plausible way, and then implements it in robotic navigation tasks. The proposed calibration model allows the agent to associate its head direction and the perceived egocentric direction of a visual cue with its position and orientation, and therefore to calibrate the head direction when the same cue is viewed again. We examine the proposed head direction calibration model in extensive simulations and real-world experiments and demonstrate its excellent performance in terms of quick association of information to proximal or distal cues as well as accuracy of calibrating the integration errors of the head direction. Videos can be viewed at <span>https://videoviewsite.wixsite.com/hdc-calibration</span><svg><path></path></svg>.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 1","pages":"Pages 31-41"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Practical bipartite consensus for multi-agent systems: A barrier function-based adaptive sliding-mode control approach","authors":"Boda Ning , Qing-Long Han , Xiaohua Ge","doi":"10.1016/j.jai.2023.100019","DOIUrl":"https://doi.org/10.1016/j.jai.2023.100019","url":null,"abstract":"<div><p>This paper is concerned with bipartite consensus tracking for multi-agent systems with unknown disturbances. A barrier function-based adaptive sliding-mode control (SMC) approach is proposed such that the bipartite steady-state error is converged to a predefined region of zero in finite time. Specifically, based on an error auxiliary taking neighboring antagonistic interactions into account, an SMC law is designed with an adaptive gain. The gain can switch to a positive semi-definite barrier function to ensure that the error auxiliary is constrained to a predefined neighborhood of zero, which in turn guarantees practical bipartite consensus tracking. A distinguished feature of the proposed controller is its independence on the bound of disturbances, while the input chattering phenomenon is alleviated. Finally, a numerical example is provided to verify the effectiveness of the proposed controller.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 1","pages":"Pages 14-19"},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49743916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Model predictive control for water management and energy security in arid/semiarid regions","authors":"D.M. Bajany , L. Zhang , X. Xia","doi":"10.1016/j.jai.2022.100001","DOIUrl":"10.1016/j.jai.2022.100001","url":null,"abstract":"<div><p>This paper aims to develop a realistic operational optimal management of a water supply system in an arid/semiarid region under climate change conditions. The developed model considers the dynamic variation of water demand, rainfall, weather, and seasonal change in electricity price. It is mathematically developed as a multi-constraint non-linear programming model based on model predictive control principles. The model optimises the quantities of water supplied by each source every month and improves the energy efficiency in a water supply system with multiple types of sources. The effectiveness of the developed MPC model is verified by applying it to a case study and comparing the results with those obtained with an open loop model. Results showed that using the MPC model leads to a 4.16% increase in the water supply cost compared to the open loop model. However, when considering uncertainties in predicting water demands, aquifer recharges, rainfall, and evaporation rate, the MPC model was better than the open loop model. Indeed, the MPC model could meet the water demand at any period due to its predictability of variations, which was not the case with the open loop model. Moreover, a sensitivity analysis is conducted to verify the capacity of the developed model to deal with some phenomena due to climatic changes, such as in rainfall.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"1 1","pages":"Article 100001"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855422000016/pdfft?md5=a33cb644d0b9ca4435716f0923204f10&pid=1-s2.0-S2949855422000016-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77150910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}