2018 Australian & New Zealand Control Conference (ANZCC)最新文献

{"title":"A Robust and Accurate Neural Predictive Model for Foreign Exchange Market Modelling and Forecasting","authors":"Lingkai Xing, Z. Man, J. Zheng, T. Cricenti, M. Tao","doi":"10.1109/ANZCC.2018.8606555","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606555","url":null,"abstract":"In this work, a robust and accurate neural predictive model based on a randomized neural learning scheme is developed for foreign exchange market modelling and forecasting purpose. In our predictive model, a dynamic single-hidden layer feedforward neural network (SLFN) is constructed with tapped-delay-memories applied at its input layer. A modified sigmoid function is designed and input weights and hidden biases are randomly assigned in such a way that highly coupled financial input patterns can be represented in the hidden feature space in a clearer way and sensitivities of the network’s hidden outputs to the changes in the financial input signals are enhanced. Also, a large number of hidden nodes in the hidden layer is used to improve the clarity of input patterns’ representation in the hidden feature space. Output weights of the network are optimized using regularised batch-learning type of least square method to improve robustness of the predictive model against external and internal disturbances. Simulation results show excellent performance of the developed model in both target deviation and directional performance measurements.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126752501","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":"Analysis of CPG gait parameters and velocity of quadruped robot with spine*","authors":"Ke Zhang, Binrui Wang","doi":"10.1109/ANZCC.2018.8606542","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606542","url":null,"abstract":"According to the characteristics of animal’s spine movement and specific speed corresponding to a gait pattern, the relationship between gait parameters and speed is analyzed. First, the Hopf oscillator is used to generate the central pattern generator rhythm signal, and the characteristics of parameters of the Hopf oscillator are analyzed. Secondly, the relationship between the speed and the gait frequency in the trot gait is analyzed, and the relationship between the speed and the stride in the bound gait is analyzed. Then, through the Webots simulation, the results show that the addition of the spine makes the robot speed significantly faster in the bound gait. Finally, the rationality of the relationship between the respective speed and gait parameters in the trot and bound gait is verified by Webots simulation. After analysis, the error of the angular frequency is about 3.4 rad/s, the error of the amplitude of the spine is 0.026 rad.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125905172","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":"Iterative Learning Control for Linear Time-varying Systems with Input and Output Constraints","authors":"Gijo Sebastian, Y. Tan, D. Oetomo, I. Mareels","doi":"10.1109/ANZCC.2018.8606594","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606594","url":null,"abstract":"Due to hardware constraints and safety requirements, many engineering systems have to satisfy input and output constraints. This paper proposes a new feedback-based iterative learning control (ILC) that can ensure the satisfaction of input and output constraints for linear-time-varying (LTV) systems. The proposed control structure consists of an output feedback loop, a feed-forward ILC and a hard constraint for input. A barrier function is used to assist the design of the output feedback in order to satisfy the output constraints. An appropriate saturation function is used in the design of ILC loop to address the input constraints. By using a suitable composite energy function, the main result of this paper shows that the desired trajectory can be learned using the proposed control structure without violating the input and output constraints. Simulation results are presented to demonstrate the effectiveness of the proposed control structure.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126553213","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":"Continuous Human Learning Optimizer based PID Controller Design of an Automatic Voltage Regulator System","authors":"Muhammad Ilyas Menhas, Ling Wang, Noor-ul-Ain Ayesha, Neelam Qadeer, M. Waris, Sohaib Manzoor, M. Fei","doi":"10.1109/ANZCC.2018.8606577","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606577","url":null,"abstract":"In this paper, an intelligent design and tuning method for the proportional-integral-derivate (PID) controller of an automatic voltage regulator (AVR) system using a novel heuristic algorithm termed as the continuous human learning optimizer (CHLO) is presented. The CHLO is inspired by human learning mechanisms wherein a well-defined rule based probabilistic procedure of random learning, individual learning, and social learning leads the search process. The CHLO is implemented in Matlab and identification of the PID parameters for said AVR system is done by stating the design task as an optimization problem. The problem statement is formulated to minimize the integral of absolute error (IAE) criterion with in-built weighted preferences for transient response characteristics. The simulation experiments are devoted both towards the application as well as in exploring the behavioral parameters of the CHLO optimizer. The performance measures such as transient respone indices, root locus analysis, and bode analysis are carried out. The obtained results are compared with other heuristic approaches in terms of percentage improvement in transient response indices. The numerical simulation results endorse competitiveness and better optimization potential of the proposed method than the biography based optimization (BBO), particle swarm optimization (PSO), differential evolution algorithm (DEA), and artificial bee colony (ABC) algorithm in parameter identification of the AVR system.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134086379","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":"Weighted Iterative Tangential Interpolation Algorithms","authors":"Umair Zulfiqar, V. Sreeram","doi":"10.1109/ANZCC.2018.8606550","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606550","url":null,"abstract":"The frequency-weighted model reduction problem is of great importance in control system design due to its applications in obtaining a lower order controller for significantly high order plant. In this paper, two algorithms for frequency-weighted model reduction using Krylov subspace based inter-polatory framework are presented. Numerical examples are presented to signify the efficacy of the proposed algorithms.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134621294","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":"Method for Coloring Night-vision Imagery Based on Multispectral Semantic Segmentation","authors":"Weiwen Zhang, Xiaojing Gu, Xingsheng Gu","doi":"10.1109/ANZCC.2018.8606609","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606609","url":null,"abstract":"Color night vision can map natural colors to nighttime images of multiple bands (e.g., visible and long-wave infrared (LWIR)). These colors can assist the observers in better and faster understanding images, thus improving their situational awareness and shortening the reaction time. In this paper, we present an effective method combining deep learning and category colors. It utilizes the semantic segmentation for image segmentation first, and then colorize the image according to categories to avoid the same color scheme and unnatural colors. We compare our method with some others quantitatively and qualitatively, such as global colorization by single lookup table, where we show significant improvements. In addition, it can be expanded according to different environments and applications because of the fixed category colors.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131491997","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":"Robust Trajectory Tracking Control Design for Nonholonomic Mobile Robot (NMR)","authors":"Bilal M. Yousuf, A. Memon","doi":"10.1109/ANZCC.2018.8606548","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606548","url":null,"abstract":"This paper addresses the problem of trajectory tracking for kinematic model of unicycle-type nonholonomic mobile robot. These robots are difficult to stabilize and control due to their non-integrable constraints. Due to this problem, it is difficult to establish a systematic model for tracking. In this paper, the proposed controller is defined in a two-step process. First, a robust state feedback point-to-point stabilization control is designed using Sliding Mode Controller (SMC). In the second step, the controller is modified so as to address the tracking problem for the constant as well as time-varying reference trajectories. The proposed control scheme is shown to provide for desired robustness properties in presence of the parametric variations, in the region of interest. The state-feedback control scheme is then extended to output feedback by incorporating a High Gain Observer. With the help of Lyapunov analysis and appropriate simulations, it is shown that the proposed output feedback control scheme achieves the required control objectives and provides for the desired performance in the presence of parametric variations.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114192600","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":"Design of Discrete Time Output Feedback Control System with Adaptive Parallel Feedforward Compensator","authors":"Seiya Fujii, I. Mizumoto","doi":"10.1109/ANZCC.2018.8606562","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606562","url":null,"abstract":"This paper deals with a design problem of an output feedback control system with a parallel feedforward compensator (PFC) for discrete-time systems. A design scheme of an almost strictly positive real (ASPR) based output feedback control system with an adaptively adjusting PFC is proposed. In the proposed method, the parameters of a PFC are adaptively adjusted for remaining the ASPR-ness of the resulting augmented system in order to guarantee the stability of the designed control system. The method makes it possible to design a PFC without using some kind or another priori information about the controlled system. The stability of the obtained control system is analyzed theoretically and the effectiveness of the proposed method will be confirmed through numerical simulations.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121525920","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":"AUV navigation with seabed acoustic sensing*","authors":"A. Miller, B. Miller, Gregory B. Miller","doi":"10.1109/ANZCC.2018.8606561","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606561","url":null,"abstract":"Autonomous Underwater Vehicle (AUV) being a powerful tool for exploring and investigating ocean resources can be used in a large variety of oceanographic, industry and defense applications. AUV navigation is still a challenging task and it is one of the fundamental elements in the modern robotics, because the ability of AUV to correctly understand its position and attitude within the underwater environment is determinant for success in different applications. Due to the absence of external reference sources, AUV navigation is usually based only on the information obtained from Doppler Velocity Loggers (DVL), Inertial Navigation Systems (INS), etc. But this type of navigation is subjected to a continuously growing error because of the absence of absolute position measurements (for example, received from the GPS or GLONASS). These measurements might be provided by observation of so-called feature points like in the case of the Unmanned Aerial Vehicles (UAV). But the big difference between acoustical and optical images makes this problem much more difficult in the AUV case, and to solve it one needs the detailed preliminary mapping of the operational seabed area. The modern advances in the acoustic imaging give rise to AUV navigation approaches based on the absolute velocity measurements. The one we propose in the present paper is analogous to the optical flow techniques for UAV navigation. It is based on the extraction of information related to the AUV absolute motion from seabed map evolution measurements. The principal advantage of the proposed method is that the fusion of the acoustic mapping and the INS data makes it possible to estimate the absolute velocity of the vehicle with respect to the seabed. In this sense the suggested method is close to the multi-beam DVL measurement, but it is based on another physical principles and thus operates better in different environment. While DVL by design operates perfectly over the flat surface [1], the appropriate environment for the suggested method implicates the seabed relief, because it extracts the velocity information from the evolution of the measured distance between the sensor and the seabed.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"45 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126007167","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":"Fuzzy filtering design for positive T-S fuzzy systems with Markov jumping parameters","authors":"Shuqian Zhu, Fengwei Pan, Jun‐e Feng","doi":"10.1109/ANZCC.2018.8606601","DOIUrl":"https://doi.org/10.1109/ANZCC.2018.8606601","url":null,"abstract":"This paper solves the positivity-preserving l1-gain fuzzy filtering design problem of a positive T-S fuzzy system with Markov jumps. With a fuzzy Markov jumping filter, the resulting system is rewritten as an augmented fuzzy Markov jump system. By linear programming technique, a filtering design result is developed to ensure the resulting system to be positive and stochastically internally stable with prescribed l1-gain performance. The design validity is confirmed by a numerical example.","PeriodicalId":358801,"journal":{"name":"2018 Australian & New Zealand Control Conference (ANZCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130903829","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}