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Speeding up top-down attention control learning by using full observation knowledge

Speeding up top-down attention control learning by using ful...

引用

2009 ieee International symposium on computational intelligence in Robotics and automation, CIRA 2009

作者： Noori, N. Nili Ahmadabadi, M. Mirian, M.S. Araabi, B.N. Control and Intelligent Processing Center of Excellence Department of Electrical and Computer Engineering University of Tehran Tehran Iran

We present a general mathematical description of the top-down attention control problem. Three important components are identified in the model: context extraction, attention focus and decision making. The context gives a coarse blurry representation of the whole input;the attention module models the focus of attention on a limited part of input, and the decision making component accounts the final decision of the agent for its motory actions. In order to achieve a faster convergence of attention learning in the online phase, an offline optimization step is performed in advance. To do so, we incorporate the knowledge of a full observer agent that has approximately learned the optimal decision making of the task. The simulation results show that by employing our algorithm, the learning speed is improved.

关键词： Decision making

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Biomimetic hybrid feedback feedforword adaptive neural control of robotic arms

Biomimetic hybrid feedback feedforword adaptive neural contr...

引用

ieee symposium on computational intelligence in control and automation, cica

作者： Yongping Pan Haoyong Yu Department of Biomedical Engineering National University of Singapore Singapore

ISBN: (纸本)9781479945290

This paper presents a biomimetic hybrid feedback feedforword (HFF) adaptive neural control for a class of robotic arms. The control structure includes a proportional-derivative feedback term and an adaptive neural network (NN) feedforword term, which mimics the human motor learning and control mechanism. Semiglobal asymptotic stability of the closed-loop system is established by the Lyapunov synthesis. The major difference of the proposed design from the traditional feedback adaptive approximation-based control (AAC) design is that only desired outputs, rather than both tracking errors and desired outputs, are applied as NN inputs. Such a slight difference leads to several attractive properties, including the convenient NN design, the decrease of the number of NN inputs, and semiglobal asymptotic stability dominated by control gains. Compared with previous HFF-AAC approaches, the proposed approach has two unique features: 1) all above attractive properties are achieved by a much simpler control scheme; 2) the bounds of plant uncertainties are not required to be known. Simulation results have verified the effectiveness and superiority of this approach.

关键词： Artificial neural networks Asymptotic stability Function approximation Uncertainty Vectors Manipulators

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Glucose level regulation for diabetes mellitus type 1 patients using FPGA neural inverse optimal control

Glucose level regulation for diabetes mellitus type 1 patien...

引用

ieee symposium on computational intelligence in control and automation, cica

作者： Jorge C. Romero-Aragon Edgar N. Sanchez Alma Y. Alanis Unidad Guadalajara Col. El Bajio CINVESTAV Jalisco Mexico CUCEI Universidad de Guadalajara Col. Las Aguilas Jalisco Mexico

In this paper, the field programmable gate array (FPGA) implementation of a discrete-time inverse neural optimal control for trajectory tracking is proposed to regulate glucose level for type 1 diabetes mellitus (T1DM) patients. For this controller, a control Lyapunov function (CLF) is proposed to obtain an inverse optimal control law in order to calculate the insulin delivery rate, which prevents hyperglycemia and hypoglycemia levels in T1DM patients. Besides this control law minimizes a cost functional. The neural model is obtained from an on-line neural identifier, which uses a recurrent high-order neural network (RHONN), trained with an extended Kalman filter (EKF). A virtual patient is implemented on a PC host computer, which is interconnected with the FPGA controller. This controller constitutes a step forward to develop an autonomous artificial pancreas.

关键词： Mathematical model Field programmable gate arrays Optimal control Vectors Covariance matrices Sugar Kalman filters

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Approximation and Complexity Trade-off by TP model transformation in controller Design: A case study of the TORA system

Approximation and Complexity Trade-off by TP model transform...

引用

8th International symposium of Hungarian Researchers on computational intelligence and Informatics, CINTI 2007

作者： Petres, Zoltán Baranyi, Péter System and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Hungary

The main objective of the paper is to study the approximation and complexity trade-off capabilities of the recently proposed Tensor Product Distributed Compensation (TPDC) based control design framework. The TPDC is the combination of the TP model transformation and the Parallel Distributed Compensation (PDC) framework. The TP model transformation includes an HOSVD based technique to solve the approximation and complexity trade-off. In this paper we generate TP models with different complexity and approximation properties, and then we derive controllers for them. We analyze how the trade-off effects the model behavior and control performance. All these properties are studied via the state feedback controller design of the Translational Oscillations with an Eccentric Rotational Proof Mass Actuator (TORA) System.

关键词： controllers

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Sound direction recognition using a condenser microphone array

Sound direction recognition using a condenser microphone arr...

引用

2003 ieee International symposium on computational intelligence in Robotics and automation, CIRA 2003

作者： Song, Kai-Tai Chen, Jian-Liang Department of Electrical and Control Engineering National Chian Tung University 1001 Ta Hsueh Road Hsinchu300 Taiwan

ISBN: (纸本)0780378660

This paper presents a sound direction recognition system for intelligent mobile robots. We studied the analysis, design, and circuit realization of a standalone sound recognition system using multiple condenser microphones. Sound signals from three condenser microphones are integrated in a circuit to resolve the source direction. The minimum recognition angle of a triangular configuration is derived. A new decode method is proposed in this paper to resolve the sound direction. The proposed scheme uses a circuit to obtain direction information, an improvement to the conventional computer-based approaches. The recognition circuitry has been implemented using UMC 0.5/spl mu/m IC chip fabrication technology. Both simulation and practical experiments validate the desired performance. Experimental results show that the system recognizes sound direction with an accuracy of /spl plusmn/5/spl deg/. The sound recognition system has been integrated to a multi-robot system to investigate various robot control applications using whistle sound in a noisy environment. Experimental results demonstrate the effectiveness of the proposed method. © 2003 ieee.

关键词： Intelligent robots

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New multiagent coordination optimization algorithms for mixed-binary nonlinear programming with control applications

New multiagent coordination optimization algorithms for mixe...

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ieee symposium on computational intelligence in control and automation, cica

作者： Haopeng Zhang Qing Hui Department of Mechanical Engineering Texas Tech University Lubbock TX USA

ISBN: (纸本)9781479945290

Mixed-binary nonlinear programming (MBNP), which can be used to optimize network structure and network parameters simultaneously, has been seen widely in applications of cyber-physical network systems. However, it is quite challenging to develop efficient algorithms to solve it practically. On the other hand, swarm intelligence based optimization algorithms can simulate the cooperation and interaction behaviors from social or nature phenomena to solve complex, nonconvex nonlinear problems with high efficiency. Hence, motivated by this observation, we propose a class of new computationally efficient algorithms called coupled spring forced multiagent coordination optimization (CSFMCO), by exploiting the chaos-like behavior of two-mass two-spring mechanical systems to improve the ability of algorithmic exploration and thus to fast solve the MBNP problem. Together with the continuous version of CSFMCO, a binary version of CSFMCO and a switching version between continuous and binary versions are presented. Moreover, to numerically illustrate our proposed algorithms, a formation control problem and resource allocation problem for cyber-physical networks are investigated by using the proposed algorithms.

关键词： Topology Optimization Linear programming Springs Algorithm design and analysis Multi-agent systems Indexes

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Optimization of engine speed neural network PID controller based on genetic algorithm

Optimization of engine speed neural network PID controller b...

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2011 4th International symposium on computational intelligence and Design, ISCID 2011

作者： Cao, Hua-Yun Peng, Fu-Ming School of Automation Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9780769545004

Engine-Dynamometer system is a two-input, dual output system with nonlinear, time-varying characteristics of large inertia, and exists coupling within the system input and output. Using the traditional PID controller, the control is often difficult to achieve the desired effect. In addition, at the production site, because of being cumbersome and precision tuning effects, the traditional PID parameter tuning methods can lead to poor control of engine speed. In this paper, an engine speed neural network PID controller based on genetic algorithm which use genetic algorithm to optimizate three control parameters of neural network PID and achieving the system input and output decoupling control is studied. Simulation results show that the genetic algorithm optimizating engine speed neural network PID control system can effectively improve the accuracy, enhance stability and fast of the system, and also have increased the engine speed control effect. © 2011 ieee.

关键词： Three term control systems

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Learning policies for attentional control 3

Learning policies for attentional control

引用

3rd ieee International symposium on computational intelligence in Robotics and automation, CIRA 1999

作者： Gonçalves, Luiz M.G. Giraldi, Gilson A. Oliveira, Antonio A.F. Grupen, Rod A. AmherstMA01003 United States CP 68511 RJ Rio de Janeiro21945-970 Brazil

ISBN: (纸本)0780358066

In this work we propose two behavioraly active policies for attentional control. These policies must act based on a multi-modal sensory feedback. Two approaches are used to derive the policies: the first one follows a simple straightforward strategy and the second one uses Q-learning to learn a policy based on the perceptual state of the system. As practical result of both algorithms, a robotic agent is capable to select a region of interest and perform shifts of attention focusing on the selected region. Then, a multi-feature extraction can take place allowing the system to identify or recognize a pattern representing that region of interest. Also, the policies have the desired property that all objects in the environment are visited at least once, although some of them can be visited more. In this way a robotic agent can relate sensed information to actions, abstracting and providing a feedback (categorization and mapping) for environmental stimuli. © 1999 ieee.

关键词： Sensory feedback

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Effects of parameter values and noise on PSO-based predictive control: An empirical study

Effects of parameter values and noise on PSO-based predictiv...

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ieee symposium on computational intelligence in control and automation, cica

作者： Muhammad S. Yousuf Hussain N. Al-Duwaish Department of Electrical Engineering King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

In this paper, a Particle Swarm Optimization (PSO) based Model Predictive control (MPC) scheme is studied through a variety of tests to better understand its behavior and characteristics. The technique has already been presented in the literature. Here, the PSO and MPC parameters are varied to study the effects on the quality of control and system dynamics. Model mismatch and noise are also introduced to test the controller performance. The results from various tests are compared and conclusions are drawn.

关键词： Noise Process control Cost function Time frequency analysis Automatic generation control Optimal control Particle swarm optimization

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Evidence based decision analysis and support

Evidence based decision analysis and support

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ieee symposium on computational intelligence in control and automation, cica

作者： Jian-Bo Yang Dong-Ling Xu Manchester Business School University of Manchester Institute of Science and Technology Manchester UK

The evidential reasoning (ER) approach was developed to support multiple criteria decision analysis (MCDA). It is based on the Dampster's combination rule for criteria aggregation and belief function for treating ignorance. In the original ER approach, however, alternative ranking depends on the accurate estimation of a value function, which may be difficult in certain decision environments. In this paper, the link and difference between the ER algorithm and Dampster's combination rule are analysed first. A new alternative ranking method is then investigated as an integrated part of the enhanced ER approach.

关键词： Erbium Equations Mathematical model Manganese Cognition Artificial intelligence Upper bound

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