Parameter tuning of sliding mode controller using multi-objective particle swarm optimization in electro-hydraulic actuator system

Electro-Hydraulic Actuator (EHA) system is very popular and widely applied in the modern industry applications. This is because of its advantages on the high force to weight ratio, accurate positioning with fast motion and capability in generating large torque. Due to its increasing trends in modern applications, the research to control the EHA system has attract the attentions of many researchers around the world. However, the nonlinear characteristics in the dynamics of the EHA system such as internal leakage have make it difficult to control and hard to produce an accurate output such as position, force, and speed that are required in different applications. Internal leakage existed in the servo valve can degrade the overall performance of the EHA system. Commonly, a control system either open-loop or closed-loop is the key to overcome the aforementioned issue, where researchers had proposed many types of control strategies across the years ranging from classical to advanced controller to control the nonlinear EHA system so that it can suit into different industry applications. In this research, Sliding Mode Controller (SMC) is designed and proposed for the positioning control of the established EHA system. To obtain the optimum performance of the EHA system, Multi-Objective Particle Swarm Optimization (MOPSO) is implemented to the SMC to achieve the highest position output performance with least overshoot and steady-state error. In order to verify the effectiveness of the proposed SMC with MOPSO strategy, comparison study has been implemented to Proportional Integral Derivative (PID) and SMC controllers with conventional Particle Swarm Optimization (PSO) technique. The simulation results show that the proposed control strategy is able to improve the overshoot percentage of the EHA system by 99.78% and 99.64% as compared to the PSO-PID controller and PSO-SMC respectively. Robustness tests show the proposed control strategy achieved least overshoot percentage in all simulation case studies including the mass, pressure and internal leakage variations

A brief review of neural networks based learning and control and their applications for robots

As an imitation of the biological nervous systems, neural networks (NN), which are characterized with powerful learning ability, have been employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification and patterns recognition etc. This article aims to bring a brief review of the state-of-art NN for the complex nonlinear systems. Recent progresses of NNs in both theoretical developments and practical applications are investigated and surveyed. Specifically, NN based robot learning and control applications were further reviewed, including NN based robot manipulator control, NN based human robot interaction and NN based behavior recognition and generation

Modeling, Simulation, and Temperature Control of a Thermal Zone with Sliding Modes Strategy

[EN] To reduce the energy consumption in buildings is necessary to analyze individual rooms and thermal zones, studying mathematical models and applying new control techniques. In this paper, the design, simulation and experimental evaluation of a sliding mode controller for regulating internal temperature in a thermal zone is presented. We propose an experiment with small physical dimensions, consisting of a closed wooden box with heat internal sources to stimulate temperature gradients through operating and shut down cycles.This investigation was supported by national doctoral program of the Colombian Administrative Department of Science Technology and Innovation (Colciencias), and the agreement "Analysis of the properties, applications and market opportunities of G-cover Coatings" closed between the Universitat Politecnica de Valencia (Spain) and the Mexican company G-cover.Florez, F.; Fernández De Córdoba, P.; Higón Calvet, JL.; Olivar, G.; Taborda, J. (2019). Modeling, Simulation, and Temperature Control of a Thermal Zone with Sliding Modes Strategy. Mathematics. 7(6):1-13. https://doi.org/10.3390/math7060503S11376Delgarm, N., Sajadi, B., & Delgarm, S. (2016). Multi-objective optimization of building energy performance and indoor thermal comfort: A new method using artificial bee colony (ABC). Energy and Buildings, 131, 42-53. doi:10.1016/j.enbuild.2016.09.003Gorni, D., Castilla, M. del M., & Visioli, A. (2016). An efficient modelling for temperature control of residential buildings. Building and Environment, 103, 86-98. doi:10.1016/j.buildenv.2016.03.016Fazenda, P., Lima, P., & Carreira, P. (2016). Context-based thermodynamic modeling of buildings spaces. Energy and Buildings, 124, 164-177. doi:10.1016/j.enbuild.2016.04.068Bacher, P., & Madsen, H. (2011). Identifying suitable models for the heat dynamics of buildings. Energy and Buildings, 43(7), 1511-1522. doi:10.1016/j.enbuild.2011.02.005Ryzhov, A., Ouerdane, H., Gryazina, E., Bischi, A., & Turitsyn, K. (2019). Model predictive control of indoor microclimate: Existing building stock comfort improvement. Energy Conversion and Management, 179, 219-228. doi:10.1016/j.enconman.2018.10.046Fiorentini, M., Wall, J., Ma, Z., Braslavsky, J. H., & Cooper, P. (2017). Hybrid model predictive control of a residential HVAC system with on-site thermal energy generation and storage. Applied Energy, 187, 465-479. doi:10.1016/j.apenergy.2016.11.041Massa Gray, F., & Schmidt, M. (2016). Thermal building modelling using Gaussian processes. Energy and Buildings, 119, 119-128. doi:10.1016/j.enbuild.2016.02.004Ascione, F., Bianco, N., De Stasio, C., Mauro, G. M., & Vanoli, G. P. (2016). Simulation-based model predictive control by the multi-objective optimization of building energy performance and thermal comfort. Energy and Buildings, 111, 131-144. doi:10.1016/j.enbuild.2015.11.033Acosta, A., González, A. I., Zamarreño, J. M., & Álvarez, V. (2016). Energy savings and guaranteed thermal comfort in hotel rooms through nonlinear model predictive controllers. Energy and Buildings, 129, 59-68. doi:10.1016/j.enbuild.2016.07.061Afram, A., & Janabi-Sharifi, F. (2014). Theory and applications of HVAC control systems – A review of model predictive control (MPC). Building and Environment, 72, 343-355. doi:10.1016/j.buildenv.2013.11.016Nagarathinam, S., Doddi, H., Vasan, A., Sarangan, V., Venkata Ramakrishna, P., & Sivasubramaniam, A. (2017). Energy efficient thermal comfort in open-plan office buildings. Energy and Buildings, 139, 476-486. doi:10.1016/j.enbuild.2017.01.043Smarra, F., Jain, A., de Rubeis, T., Ambrosini, D., D’Innocenzo, A., & Mangharam, R. (2018). Data-driven model predictive control using random forests for building energy optimization and climate control. Applied Energy, 226, 1252-1272. doi:10.1016/j.apenergy.2018.02.126Killian, M., Mayer, B., & Kozek, M. (2016). Cooperative fuzzy model predictive control for heating and cooling of buildings. Energy and Buildings, 112, 130-140. doi:10.1016/j.enbuild.2015.12.017Brastein, O. M., Perera, D. W. U., Pfeifer, C., & Skeie, N.-O. (2018). Parameter estimation for grey-box models of building thermal behaviour. Energy and Buildings, 169, 58-68. doi:10.1016/j.enbuild.2018.03.057Lirola, J. M., Castañeda, E., Lauret, B., & Khayet, M. (2017). A review on experimental research using scale models for buildings: Application and methodologies. Energy and Buildings, 142, 72-110. doi:10.1016/j.enbuild.2017.02.060Coutinho, C. P., Baptista, A. J., & Dias Rodrigues, J. (2016). Reduced scale models based on similitude theory: A review up to 2015. Engineering Structures, 119, 81-94. doi:10.1016/j.engstruct.2016.04.016Chew, L. W., Glicksman, L. R., & Norford, L. K. (2018). Buoyant flows in street canyons: Comparison of RANS and LES at reduced and full scales. Building and Environment, 146, 77-87. doi:10.1016/j.buildenv.2018.09.026Chen, S.-Y., & Gong, S.-S. (2017). Speed tracking control of pneumatic motor servo systems using observation-based adaptive dynamic sliding-mode control. Mechanical Systems and Signal Processing, 94, 111-128. doi:10.1016/j.ymssp.2017.02.025Huang, Y., Khajepour, A., Ding, H., Bagheri, F., & Bahrami, M. (2017). An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems. Applied Energy, 188, 576-585. doi:10.1016/j.apenergy.2016.12.033Mironova, A., Mercorelli, P., & Zedler, A. (2016). Robust Control using Sliding Mode Approach for Ice-Clamping Device activated by Thermoelectric Coolers. IFAC-PapersOnLine, 49(25), 470-475. doi:10.1016/j.ifacol.2016.12.067Norton, M., Khoo, S., Kouzani, A., & Stojcevski, A. (2015). Adaptive fuzzy multi‐surface sliding control of multiple‐input and multiple‐output autonomous flight systems. IET Control Theory & Applications, 9(4), 587-597. doi:10.1049/iet-cta.2014.0209Fux, S. F., Ashouri, A., Benz, M. J., & Guzzella, L. (2014). EKF based self-adaptive thermal model for a passive house. Energy and Buildings, 68, 811-817. doi:10.1016/j.enbuild.2012.06.01

Modelling of an electro-hydraulic actutor using extended adaptive distance gap statistic approach

The existence of high degree of non-linearity in Electro-Hydraulic Actuator (EHA) system has imposed a challenging task in developing its model so that effective control algorithm can be proposed. In general, there are two modelling approaches available for EHA system, which are the dynamic equation modelling method and the system identification modelling method. Both approaches have disadvantages, where the dynamic equation modelling is hard to apply and some parameters are difficult to obtain, while the system identification method is less accurate when the system’s nature is complicated with wide variety of parameters, nonlinearity and uncertainties. This thesis presents a new modelling procedure of an EHA system by using fuzzy approach. Two sets of input variables are obtained, where the first set of variables are selected based on mathematical modelling of the EHA system. The reduction of input dimension is done by the Principal Component Analysis (PCA) method for the second set of input variables. A new gap statistic with a new within-cluster dispersion calculation is proposed by introducing an adaptive distance norm in distance calculation. The new gap statistic applies Gustafson Kessel (GK) clustering algorithm to obtain the optimal number of cluster of each input. GK clustering algorithm also provides the location and characteristic of every cluster detected. The information of input variables, number of clusters, cluster’s locations and characteristics, and fuzzy rules are used to generate initial Fuzzy Inference System (FIS) with Takagi-Sugeno type. The initial FIS is trained using Adaptive Network Fuzzy Inference System (ANFIS) hybrid training algorithm with an identification data set. The ANFIS EHA model and ANFIS PCA model obtained using proposed modelling procedure, have shown the ability to accurately estimate EHA system’s performance at 99.58% and 99.11% best fitting accuracy compared to conventional linear Autoregressive with External Input (ARX) model at 94.97%. The models validation result on different data sets also suggests high accuracy in ANFIS EHA and ANFIS PCA model compared to ARX model

Visual Servoing

The goal of this book is to introduce the visional application by excellent researchers in the world currently and offer the knowledge that can also be applied to another field widely. This book collects the main studies about machine vision currently in the world, and has a powerful persuasion in the applications employed in the machine vision. The contents, which demonstrate that the machine vision theory, are realized in different field. For the beginner, it is easy to understand the development in the vision servoing. For engineer, professor and researcher, they can study and learn the chapters, and then employ another application method

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored

Development and evaluation of a fault detection and identification scheme for the WVU YF-22 UAV using the artificial immune system approach

A failure detection and identification (FDI) scheme is developed for a small remotely controlled jet aircraft based on the Artificial Immune System (AIS) paradigm. Pilot-in-the-loop flight data are used to develop and test a scheme capable of identifying known and unknown aircraft actuator and sensor failures. Negative selection is used as the main mechanism for self/non-self definition; however, an alternative approach using positive selection to enhance performance is also presented. Tested failures include aileron and stabilator locked at trim and angular rate sensor bias. Hyper-spheres are chosen to represent detectors. Different definitions of distance for the matching rules are applied and their effect on the behavior of hyper-bodies is discussed. All the steps involved in the creation of the scheme are presented including design selections embedded in the different algorithms applied to generate the detectors set. The evaluation of the scheme is performed in terms of detection rate, false alarms, and detection time for normal conditions and upset conditions. The proposed detection scheme achieves good detection performance for all flight conditions considered. This approach proves promising potential to cope with the multidimensional characteristics of integrated/comprehensive detection for aircraft sub-system failures.;A preliminary performance comparison between an AIS based FDI scheme and a Neural Network and Floating Threshold based one is presented including groundwork on assessing possible improvements on pilot situational awareness aided by FDI schemes. Initial results favor the AIS approach to FDI due to its rather undemanding adaptation capabilities to new environments. The presence of the FDI scheme suggests benefits for the interaction between the pilot and the upset conditions by improving the accuracy of the identification of each particular failure and decreasing the detection delays

Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal

Real-time surface formation using a network of interconnected programmable actuators

This research has explored methods for developing a large interactive dynamic 3D surface using an array of interconnected pneumatically actuated cylinders. People can control the surface using body movement, sound or pre-programmed sequences. The main contribution is a method for accurately positioning cylinders without the need for position feedback