Volume 14, Number 3, 2017
In recent years, theoretical and practical research on event-based communication strategies has gained considerable research attention due primarily to their irreplaceable superiority in resource-constrained systems (especially networked systems). For networked systems, event-based transmission scheme is capable of improving the efficiency in resource utilization and prolonging the lifetime of the network components compared with the widely adopted periodic transmission scheme. As such, it would be interesting to 1) examining how the event-triggering mechanisms affect the control or filtering performance for networked systems, and 2) developing some suitable approaches for the controller and filter design problems. In this paper, a bibliographical review is presented on event-based control and filtering problems for various networked systems. First, the event-driven communication scheme is introduced in detail according to its engineering background, characteristic, and representative research frameworks. Then, different event-based control and filtering (or state estimation) problems are categorized and then discussed. Finally, we conclude the paper by outlining future research challenges for event-based networked systems.
Day by day, networked control system (NCS) methods have been promoted for distributed closed-loop control systems. Interestingly, the integration of control and computing theories enhanced the development of networked control systems through remote control for wide applications employing the internet. Two further directions to networked control technology are Leader-Follower systems and model predictive control systems. Cloud control system is looked at an extension of networked control systems (NCS) using internet of things (IOT) methodologies. In this paper, a comprehensive literature survey of the new technology of control systems application performed on cloud computing is presented.
Breeze/architecture description language (ADL), is an eXtensible markup language (XML) based architecture description language which is used to model software systems at the architecture level. Though Breeze/ADL provides an appropriate basis for architecture modelling, it can neither analyse nor evaluate the architecture reliability. In this paper, we propose a Breeze/ADL based strategy which, by combining generalized stochastic Petri net (GSPN) and tools for reliability analysis, supports architecture reliability modelling and evaluation. This work expands the idea in three directions: Firstly, we give a Breeze/ADL reliability model in which we add error attributes to Breeze/ADL error model for capturing architecture error information, and at the same time perform the system error state transition through the Breeze/ADL production. Secondly, we present how to map a Breeze/ADL reliability model to a GSPN model, which in turn can be used for reliability analysis. The other task is to develop a Breeze/ADL reliability analysis modelling toolɃEXGSPN (Breeze/ADL reliability analysis modelling tool), and combine it with platform independent petri net editor 2 (PIPE2) to carry out a reliability assessment.
In the present work, autonomous mobile robot (AMR) system is intended with basic behaviour, one is obstacle avoidance and the other is target seeking in various environments. The AMR is navigated using fuzzy logic, neural network and adaptive neurofuzzy inference system (ANFIS) controller with safe boundary algorithm. In this method of target seeking behaviour, the obstacle avoidance at every instant improves the performance of robot in navigation approach. The inputs to the controller are the signals from various sensors fixed at front face, left and right face of the AMR. The output signal from controller regulates the angular velocity of both front power wheels of the AMR. The shortest path is identified using fuzzy, neural network and ANFIS techniques with integrated safe boundary algorithm and the predicted results are validated with experimentation. The experimental result has proven that ANFIS with safe boundary algorithm yields better performance in navigation, in particular with curved/irregular obstacles.
This paper presents the reaction torque based satellite base reactionless control or base disturbance minimization of a redundant free-floating space robot. This subject is of vital importance in the study of the free-floating space robot because the base disturbance minimization will result in less energy consumption and prolonged control application. The analytical formulation of the reaction torque is derived in this article, and the reaction torque control can achieve reactionless control and satellite base disturbance minimization. Furthermore, we derive the reaction torque based control of the space robot for base disturbance minimization from both the non-strict task priority and strict task priority control strategy. The dynamics singularity in the proposed algorithm is avoided in this paper. Besides, a real time simulation system of the space robot under Linux/real time application interface (RTAI) is developed to verify and test the feasibility and reliability of the method. The experimental results demonstrate the feasibility of online reaction torque control of the redundant free-floating space robot.
Learning and self-adaptation ability is highly required to be integrated in path planning algorithm for underwater robot during navigation through an unspecified underwater environment. High frequency oscillations during underwater motion are responsible for nonlinearities in dynamic behavior of underwater robot as well as uncertainties in hydrodynamic coefficients. Reactive behaviors of underwater robot are designed considering the position and orientation of both target and nearest obstacle from robot's current position. Human like reasoning power and approximation based learning skill of neural based adaptive fuzzy inference system (ANFIS) has been found to be effective for underwater multivariable motion control. More than one ANFIS models are used here for achieving goal and obstacle avoidance while avoiding local minima situation in both horizontal and vertical plane of three dimensional workspace. An error gradient approach based on input-output training patterns for learning purpose has been promoted to spawn trajectory of underwater robot optimizing path length as well as time taken. The simulation and experimental results endorse sturdiness and viability of the proposed method in comparison with other navigational methodologies to negotiate with hectic conditions during motion of underwater mobile robot.
The Robogymnast is a triple link underactuated pendulum that mimics a human gymnast hanging from a horizontal bar. In this paper, two multi-objective optimization methods are developed using invasive weed optimization (IWO). The first method is the weighted criteria method IWO (WCMIWO) and the second method is the fuzzy logic IWO hybrid (FLIWOH). The two optimization methods were used to investigate the optimum diagonal values for the Q matrix of the linear quadratic regulator (LQR) controller that can balance the Robogymnast in an upright configuration. Two LQR controllers were first developed using the parameters obtained from the two optimization methods. The same process was then repeated, but this time with disturbance applied to the Robogymnast states to develop another set of two LQR controllers. The response of the controllers was then tested in different scenarios using simulation and their performance evaluated. The results show that all four controllers are able to balance the Robogymnast with varying accuracies. It has also been observed that the controllers trained with disturbance achieve faster settling time.
This study focuses on a graphical approach to determine the robust stabilizing regions of fractional-order PIλ(proportional integration) controllers for fractional-order systems with time-delays. By D-decomposition technique, the existence conditions and calculating method of the real root boundary (RRB) curves, complex root boundary (CRB) curves and infinite root boundary (IRB) lines are investigated for a given stability degree. The robust stabilizing regions in terms of the RRB curves, CRB curves and IRB lines are identified by the proposed criteria in this paper. Finally, two illustrative examples are given to verify the effectiveness of this graphical approach for different stability degrees.
This paper considers the output tracking problem for more general classes of stochastic nonlinear systems with unknown control coefficients and driven by noise of unknown covariance. By utilizing the radial basis function neural network approximation method and backstepping technique, we successfully construct a controller to guarantee the solution process to be bounded in probability. The tracking error signal is 4th-moment semi-globally uniformly ultimately bounded (SGUUB) and can be regulated into a small neighborhood of the origin in probability. A simulation example is given to demonstrate the effectiveness of the control scheme.
When a feedback system has components described by non-rational transfer functions, a standard practice in designing such a system is to replace the non-rational functions with rational approximants and then carry out the design with the approximants by means of a method that copes with rational systems. In order to ensure that the design carried out with the approximants still provides satisfactory results for the original system, a criterion of approximation should be explicitly taken into account in the design formulation. This paper derives such a criterion for multi-input multi-output (MIMO) feedback systems whose design objective is to ensure that the absolute values of every error and every controller output components always stay within prescribed bounds whenever the inputs satisfy certain bounding conditions. The obtained criterion generalizes a known result which was derived for single-input single-output (SISO) systems; furthermore, for a given rational approximant matrix, it is expressed as a set of inequalities that can be solved in practice. Finally, a controller for a binary distillation column is designed by using the criterion in conjunction with the method of inequalities. The numerical results clearly demonstrate that the usefulness of the criterion in obtaining a design solution for the original system.
IJAC CiteScore keeps raising in 2018
IJAC receives a CiteScore as high as 2.34 in 2018 which is 1.37 times higher than that in 2017. Being in the top 15%, it ranks #69 among 460 journals in respective categories.
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During the past two years, IJAC has published a series of high-quality papers by famous scholars around the world, including professor Tomaso Poggio from MIT, professor Brian Anderson from Australian National University, professor Yike Guo from Imperial College London, etc.. All the papers are open access, covering topics of Deep Learning, Artificial Intelligence, Neural Networks, and so on. You’ll never miss it!
2019 International Academic Conference List
International Journal of Automation and Computing (IJAC) maintains this list of conferences at the beginning of each year that are highly relevant to current hot research topics, including artificial intelligence, machine learning, computer vision, pattern recognition, robotics and automatic control.