Showing papers presented at "International Symposium on Intelligent Control in 2003"
05 Oct 2003
66 citations
05 Oct 2003
63 citations
05 Oct 2003
TL;DR: In this article, a continuous control mechanism that compensates for uncertainty in a class of multi-input nonlinear systems is presented, which is based on limited assumptions on the structure of the system nonlinearities.
Abstract: In this paper, we present a novel continuous control mechanism that compensates for uncertainty in a class of multi-input nonlinear systems. The control strategy is based on limited assumptions on the structure of the system nonlinearities. A Lyapunov-based stability argument is employed to prove semi-global asymptotic tracking. The control mechanism has the interesting feature of "learning" the unknown system dynamics. For the sake of clarity, the proposed control design is initially presented for a first-order, single-input case. Using this result as a stepping stone, the design is then extended to higher-order, multi-input systems.
59 citations
05 Oct 2003
TL;DR: A probabilistic approach to the problem of mission planning for UAVs (Unmanned Aerial Vehicles) flying through an area of multiple sources of threat is introduced and two strategies that lead a UAV to the target through the area of operation is developed.
Abstract: This paper introduces a probabilistic approach to the problem of mission planning for UAVs (Unmanned Aerial Vehicles) flying through an area of multiple sources of threat. As the first step, this new approach is used in path planning. It is assumed that the probabilistic map of the area of operation is available during the mission. Probabilistic map is defined as the risk of exposure to the sources of threat as a function of position. In the path planning, the objective is to go to a target location along the shortest possible path with an acceptable probability of getting disabled or along an acceptably long path with the lowest possible probability of getting disabled. Depending on the definition of threat, a UAV is considered "disabled" by a source of threat when it is detected, hit or shut down. The conditional probability of a UAV getting disabled under the condition that it follows a certain path is defined and formulated based on the probabilistic map of the area. Then, two strategies that lead a UAV to the target through the area of operation is developed. The strategies use the local information of the probabilistic map and the information about the location of the target. They are parameterized to change the weighting on finding a shorter path or finding a path with smaller probability of getting disabled. Finally, the strategies are implemented in a case study to illustrate the application of the probabilistic approach. The paper includes a discussion on using the probabilistic approach in other phases of mission planning for multiple UAVs.
56 citations
05 Oct 2003
TL;DR: In this article, a sliding mode controller is presented to coordinate a team of nonholonomic robots in a leader-following configuration, where a two-vehicle team is required to follow a prescribed trajectory while maintaining a desired formation.
Abstract: In this paper, we present a sliding mode controller to coordinate a team of nonholonomic robots in a leader-following configuration We consider a two-vehicle team that is required to follow a prescribed trajectory while maintaining a desired formation We show that under certain reasonable assumptions the formation is stable; that is, robots are able to maintain a desired distance and relative bearing The stability properties of the closed-loop system are studied using Lyapunov theory Numerical simulations as well as experimental results verify the validity of our approach
53 citations
05 Oct 2003
TL;DR: A simple but feasible Robust PID (RPID) tuning methodology is proposed in this paper andSimulations are presented to demonstrate the advantages of RPID compared with other PIDs.
Abstract: A simple but feasible Robust PID (RPID) tuning methodology is proposed in this paper. Most robust controllers that have been developed in literature by now have complex structures. They are either hard to be implemented or easily broken down. The simplest controller, PID, is chosen to be the prototype of robust controller. Through parameter selection, robust performance is achieved. Minimax criterion guarantees a set of controller parameters to be most optimal to the worst operating condition that may occur within the uncertainty ranges of model parameters. To execute the minimax search, a co-evolutionary algorithm based on Particle Swarm Optimization is advanced. Simulations are presented to demonstrate the advantages of RPID compared with other PIDs.
50 citations
05 Oct 2003
TL;DR: The proposed approach implements a sort of "deterministic learning" in the sense that deterministic features of nonlinear dynamical systems are learned not by algorithms from statistical principles, but in a dynamical, deterministic manner, utilizing results from adaptive systems theory.
Abstract: In this paper, we present an approach for neural networks (NN) based identification of unknown nonlinear dynamical systems undergoing periodic or periodic-like (recurrent) motions Among various types of NN architectures, we use a dynamical version of the localized RBF neural network, which is shown to be particularly suitable for identification in a dynamical framework With the associated properties of localized RBF networks, especially the one concerning the persistent excitation (PE) condition for periodic trajectories, the proposed approach achieves sufficiently accurate identification of system dynamics in a local region along the experienced system trajectory In particular, for neurons whose centers are close to the trajectories, the neural weights converge to a small neighborhood of a set of optimal values; while for other neurons with centers far away from the trajectories, the neural weights are not updated and are almost unchanged The proposed approach implements a sort of "deterministic learning" in the sense that deterministic features of nonlinear dynamical systems are learned not by algorithms from statistical principles, but in a dynamical, deterministic manner, utilizing results from adaptive systems theory The nature of this deterministic learning is closely related to the exponentially stability of a class of nonlinear adaptive systems Simulation studies are included to demonstrate the effectiveness of the proposed approach
49 citations
05 Oct 2003
TL;DR: This paper presents a new radial distortion model with an easy analytical undistortion formula, which also belongs to the polynomial approximation category, and experimental results are presented to show that with this radial distortions model, satisfactory accuracy is achieved.
Abstract: Most algorithms in 3D computer vision rely on the pinhole camera model because of its simplicity, whereas virtually all imaging devices introduce a certain amount of nonlinear distortion, where the radial distortion is the most severe part. Common approach to radial distortion is by the means of polynomial approximation, which introduces distortion-specific parameters into the camera model and requires estimation of these distortion parameters. The task of estimating radial distortion is to find a radial distortion model that allows easy undistortion as well as satisfactory accuracy. This paper presents a new radial distortion model with an easy analytical undistortion formula, which also belongs to the polynomial approximation category. Experimental results are presented to show that with this radial distortion model, satisfactory accuracy is achieved. An application of the new radial distortion model is non-iterative yellow line alignment with a calibrated camera on ODIS, a robot built in our CSOIS.
32 citations
05 Oct 2003
TL;DR: In this paper, a multi-sensor optimal information fusion criterion weighted by covariance is presented in the linear minimum variance sense for the discrete multichannel ARMA (autoregressive moving average) signals with correlated noises.
Abstract: A new multi-sensor optimal information fusion criterion weighted by covariance is presented in the linear minimum variance sense. Based on this optimal fusion criterion, using the measurement white noise filters, a general multi-sensor optimal information fusion distributed Kalman filter is given for the discrete multichannel ARMA (autoregressive moving average) signals with correlated noises. It has a two-layer fusion structure with fault tolerant and robust properties. When all local sensor subsystems are faultless, the precision of the fusion filter is lower than that of the centralized filter. When some sensors are fault, the fusion filter has better reliability. The precision of the fusion filter is higher than that of any local sensor subsystem. Applying it into a double-channel system with three sensors shows its effectiveness.
30 citations
05 Oct 2003
TL;DR: A sliding mode-like fuzzy logic control (SMFC) algorithm for a class of high order nonlinear systems is presented and the fuzzy logic controller obtained is equivalent to a sliding mode controller.
Abstract: A sliding mode-like fuzzy logic control (SMFC) algorithm for a class of high order nonlinear systems is presented. The fuzzy logic controller obtained is equivalent to a sliding mode controller. New adaptive laws for the parameters of the fuzzy logic system (FLS) are adopted in order to self-tune the so-called dead zone parameters. The robustness and the resistance ability to the external perturbations of systems are improved and the chattering of the sliding mode control (SMC) is eliminated. The simulation results of a numerical example show that the control algorithm is efficient and feasible.
30 citations
05 Oct 2003
TL;DR: In this paper, the authors examine the roots of purposive behavior in an agent surrounded by a stationary unknown environment and derive a structure for a behavior generation mechanism (BGM) that would semantically embed an agent in the context of its environment.
Abstract: This paper examines the roots of purposive behavior in an agent surrounded by a stationary unknown environment. The investigation focuses on deriving a structure for a behavior generation mechanism (BGM) that would semantically embed an agent in the context of its environment. The BGM is made to adhere to the situated, embodied, intelligent, and emergent requirements that were suggested by Brooks for the construction of intelligent control architectures. Concepts from epistemology, artificial life, hybrid systems, and the potential field approach to planning are used. The suggested BGM utilizes both experience and synergy as drivers of action selection. The BGM is intended for use in the specific case of motion planning for a multidimensional agent of arbitrary shape operating in a multidimensional, unknown environment.
05 Oct 2003
TL;DR: The results from optimization design of IIR digital filters demonstrate that NQEA is superior to other several conventional evolutionary algorithms greatly in quality and efficiency.
Abstract: In this paper, a novel evolutionary algorithm called new quantum evolutionary algorithm (NQEA) is proposed to solve a class of multi-objective optimization problems. The main point of NQEA is that a new quantum logic rotation gate is introduced. NQEA characterizes rapid convergence, good global search capability and short computing time. Then, the convergence of NQEA is also analyzed using random functional theory. The results from optimization design of IIR digital filters demonstrate that NQEA is superior to other several conventional evolutionary algorithms greatly in quality and efficiency.
05 Oct 2003
TL;DR: In this article, the authors demonstrate that for switched systems the optimal switching time instants and the optimal control policy can be solved readily by direct search optimization and demonstrate that this is the case for most of the problems considered in this paper.
Abstract: We demonstrate in this paper that for switched systems the optimal switching time instants and the optimal control policy can be solved readily by direct search optimization. General problem formulation and numerical procedures are presented together with two demonstrative examples previously considered in the literature using other numerical solution methods.
05 Oct 2003
TL;DR: It is proved that any fuzzy concepts of the finite universe of discourse are the EI representations of simple concepts, which can be represented by the sub-perfect relation defined by Kim K.H.
Abstract: In many fuzzy systems, the membership functions of fuzzy concepts are obtained by the expert's experiences. Different persons may have different membership functions for the same fuzzy concept and the current algorithms for determining membership functions are not universal. So that many mathematical tools can not applied to the fuzzy model. In this paper, the mathematical structures of fuzzy concepts have been studied by the EI algebra which is molecular lattice defined by Wang Guojun over some AFS (Axiomatic Fuzzy Set) structures which is super-graph and the fuzzy matrix theory. It is proved that any fuzzy concepts of the finite universe of discourse are the EI representations of simple concepts, which can be represented by the sub-perfect relation defined by Kim K.H.. Applying the AFS theory and the fuzzy matrix theory, the membership functions of the fuzzy concepts can be obtained by the unitive algorithms according to the database. And many powerful mathematical tools such as lattice theory, topological molecular, combinatorics etc. can be applied to study fuzzy model.
05 Oct 2003
TL;DR: The results show that the proposed IM/sup 3/L approach provides not only fast detection and proper identification but also good estimation of the failure extent as well as robust state estimation.
Abstract: In this paper we propose an approach to detect, identify and estimate failures, including partial failures, in a dynamic system The approach (IM/sup 3/L) uses the interacting multiple model (IMM) estimators to detect and identify total and partial failures and the maximum likelihood estimator (MLE) to estimate the extent of failure It provides an effective and integrated framework for fault detection, identification and state estimation The hierarchical structure of the fault model set for FDI is further addressed and a two-level hierarchical IMM (HIMM) is implemented By using an aircraft example, the proposed IM/sup 3/L approach is evaluated and its performance is compared with those of the HIMM and autonomous MM (AMM) The robustness of IM/sup 3/L is analyzed in the presence of the uncertain noise statistics The results show that the proposed approach provides not only fast detection and proper identification but also good estimation of the failure extent as well as robust state estimation
05 Oct 2003
TL;DR: The problem of forcing a nonlinear system to track a desired reference signal is addressed by combining the theory of output regulation and the Takagi-Sugeno fuzzy modelling.
Abstract: In this paper, the problem of forcing a nonlinear system to track a desired reference signal is addressed by combining the theory of output regulation and the Takagi-Sugeno fuzzy modelling The designing of the fuzzy regulator is based on LMI techniques
05 Oct 2003
TL;DR: In this paper, stabilization conditions to design a switching fuzzy controller are derived and to avoid discontinuity of the switching control inputs, a continuity condition of control inputs is derived.
Abstract: This paper presents a controller design condition based on a switching Lyapunov function for a class of nonlinear systems In our previous papers we proposed a switching fuzzy model and a switching Lyapunov function for open-loop systems The switching Lyapunov function is constructed by mirroring structure of the switching fuzzy model In this paper, stabilization conditions to design a switching fuzzy controller are derived To avoid discontinuity of the switching control inputs, we derive a continuity condition of control inputs A design example illustrates the utility of this approach
05 Oct 2003
TL;DR: In this article, the authors derived nonlinear state feedback controllers for constrained systems with and without disturbances via Hamilton-Jacobi equations via non-quadratic functionals and solved it using successive iterations between the control and the cost function.
Abstract: In this paper, we derive nonlinear state feedback controllers for constrained systems with and without disturbances via Hamilton-Jacobi equations In the former case, we show how to formulate the associated Hamilton-Jacobi-Bellman (HJB) equation using nonquadratic functionals then solve it using successive iterations between the control and the cost function The type of constraints considered in this case are input saturation, constrained states, and minimum-time control Later in the paper, we include disturbance into the controller design for constrained input systems only We show how to formulate the associated Hamilton-Jacobi-Isaac (HJI) equation using special nonquadratic supply rates to obtain the nonlinear state feedback H/sub /spl infin// control In both Hamilton-Jacobi equations, the solution is carried over a compact set of the asymptotic stability region of an initial stabilizing control We show through an example for the HJB case how this method enlarges the region of asymptotic stability (RAS) This is an important feature when considering constrained input systems
05 Oct 2003
TL;DR: Vision-based techniques to automatically detect the absence of the fastening bolts that secure the rails to the sleepers in railway maintenance and a new method that produces spatially localized and statistically independent basis vector are presented.
Abstract: In this paper we present vision-based techniques to automatically detect the absence of the fastening bolts that secure the rails to the sleepers. The inspection system uses images from a digital line scan camera installed under a train. This application is part of the most general problem of object recognition. In object recognition as in supervised learning, we often extract new features from original ones for the purpose of reducing the feature space dimensions and achieving better performances. The goal of this paper is to compare two techniques within the context of the hexagonal-headed bolts recognition in railway maintenance. The first technique is Wavelets Transform (WT), the second technique is Independent Component Analysis (ICA), a new method that produces spatially localized and statistically independent basis vector. The coefficients of the new representation in the ICA and WT subspace are supplied as input to a Support Vector Machine (SVM). A SVM classifier analyses the images in order to evaluate the pre-processing technique which could give the highest rate in detecting the presence of the bolts. Results in terms of detection rate and false positive rate are given in the paper.
05 Oct 2003
TL;DR: Modified method can keep the steady outputs of neural networks as feasible solutions for job-shop scheduling problems and avoid Hopfield neural network to converge to local minimum volume.
Abstract: A new method based on Hopfield neural networks for solving job-shop scheduling problems (JSP) is proposed All constraints of job-shop scheduling problems and its permutation matrix express are developed A new calculation energy function included all constraints of job-shop scheduling problems is given A corresponding new Hopfield neural network construction and its weights of job-shop scheduling problems are given To avoid Hopfield neural network to converge to local minimum volume, and to produce some non-feasible scheduling solutions for JSP, simulated annealing algorithm is applied to Hopfield neural network Hopfield neural network converging to minimum volume 0, can keep the steady outputs of neural networks as feasible solution for job-shop scheduling problem This paper improved existing method based on Hopfield neural network for solving job-shop scheduling problems Compared with the method, modified method can keep the steady outputs of neural networks as feasible solutions for job-shop scheduling problems
05 Oct 2003
TL;DR: The solutions, through a control engineering perspective, for the time delay problem encountered in distributing the speed control loop of a Brushless DC motor via an Ethernet network are experiments.
Abstract: Investigations on adapting Ethernet for distributed control systems is an interesting topic in the motion control industry, due to its commercially off the shelf hardware availability and compatibility at a comparatively lower price. Conversely, the communication through shared media in standard Ethernet is non-deterministic resulting in stochastic delays of data transfer. This paper experiments the solutions, through a control engineering perspective, for the time delay problem encountered in distributing the speed control loop of a Brushless DC motor via an Ethernet network. The mean of the control delay (T) is used in standard controller strategies modified for time delayed systems.
05 Oct 2003
TL;DR: The design methodology for Mamdani-type fuzzy logic controllers to regulate the blood glucose level in a Type I diabetic patient is presented and the overall control strategy is based on a two-loop feedback strategy.
Abstract: This paper presents the design methodology for Mamdani-type fuzzy logic controllers to regulate the blood glucose level in a Type I diabetic patient The overall control strategy is based on a two-loop feedback strategy The inner-loop provides the amount of both rapid (Lispro) and slow (NPH) insulin types that the patient has to program in a three-shoots daily basis The combined preparation is then injected to the patient through a subcutaneous route Meanwhile, the outer-loop adjusts the maximum amounts of insulin provided to the patient In this way, it is pursued to optimize the amount of insulin required to maintain a normal glucose level Both controllers were synthesized gathering information about physician treatment of diabetic patients using fuzzy logic
05 Oct 2003
TL;DR: This paper proposes the development of a fuzzy predictive control, where genetic algorithms are used to automatically tune the controller and a recurrent neural network is used to identify the process, and then provides predictions about the process behavior, based on control actions applied to the system.
Abstract: This paper proposes the development of a fuzzy predictive control Genetic algorithms (GA's) are used to automatically tune the controller A recurrent neural network is used to identify the process, and then provides predictions about the process behavior, based on control actions applied to the system These predictions are used by the fuzzy controller, in order to accomplish a better control of an alcoholic fermentation process from chemical industry This problem has been chosen due to its non-linearity and large accommodation time, that make it hard to control by standard controllers Comparison of performance is made with non-predictive approaches(PID and Fuzzy-PD), and also with another predictive approach, GPC(Generalized Predictive Control)
05 Oct 2003
TL;DR: To overcome DPSMO's difficulty in producing a high-quality Pareto front, DPSEA is designed by combining both EA and PSO's information sharing techniques, and is found to be competitive with, or even superior to DMOEA and DPSMO in terms of keeping the diversity of the individuals along the trade-off surface.
Abstract: In this paper, the authors propose two new evolutionary approaches to Multiobjective Optimization Problems (MOPs)-Dynamic Particle Swarm Optimization (DPSMO) and Dynamic Particle Swarm Evolutionary Algorithm (DPSEA). In DPSMO, instead of using genetic operators (e.g., crossover and mutation), the information sharing technique in Partide Swarm Optimization (PSO) is applied to inform the entire population more accurate moving direction and speed as opposed to any generic evolutionary algorithms (EA). Meanwhile, based on the dynamic population strategies, cell-based rank and density estimation and objective space compression strategy used in Dynamic Multiobjective Evolutionary Algorithm (DMOEA), the DPSMO can evolve to an approximately optimal population size while the population is approaching the true Pareto front. To overcome DPSMO's difficulty in producing a high-quality Pareto front, DPSEA is designed by combining both EA and PSO's information sharing techniques. By examining the selected performance measures on one test function, DPSEA is found to be competitive with, or even superior to DMOEA and DPSMO in terms of keeping the diversity of the individuals along the trade-off surface, tending to extend the Pareto front to new areas and finding a well-approximated Pareto optimal front.
05 Oct 2003
TL;DR: How Internet-like protocols may be used to coordinate and control the usage of a resource by n agents in the presence of time delay is shown.
Abstract: In this paper we show how Internet-like protocols may be used to coordinate and control the usage of a resource by n agents. Lyapunov second method is used to provide sufficient stability conditions of the dynamics of the n agents in the presence of time delay.
05 Oct 2003
TL;DR: A simple accurate and fast inverse kinematics solution is obtained through fuzzy logic which is optimized for real time applications and the simulation results verify the efficiency of the proposed solution.
Abstract: Inverse kinematics is computationally expensive and can result in significant control delays in real time. For redundant robots, since there is infinite inverse kinematics solutions, additional computations are required through optimization schemes. Based on the fact that humans do not compute exact inverse kinematics, but can do precise positioning from heuristics, we developed an inverse kinematics solving method through fuzzy logic which is optimized for real time applications. As a result, a simple accurate and fast inverse kinematics solution is obtained. The simulation results verify the efficiency of the proposed solution.
05 Oct 2003
TL;DR: A new adaptive robust fuzzy control algorithm is presented for a class of nonlinear systems with unstructured uncertainties which are coming from modelling errors and external disturbances, and Takagi-Sugeno type fuzzy logic systems are employed to approximate uncertain functions.
Abstract: A new adaptive robust fuzzy control (ARFC) algorithm is presented for a class of nonlinear systems with unstructured uncertainties which are coming from modelling errors and external disturbances. In the algorithm, without any prior knowledge of the bounding functions of the uncertainties, Takagi-Sugeno type fuzzy logic systems are employed to approximate uncertain functions. A systematic procedure is developed for the synthesis of adaptive robust fuzzy control whose adaptive mechanism has minimal learning parameterizations by use of dissipative theoretical approach and small gain approach. Application example illustrating the method described is included for ship roll system, which is shown that the designed system guarantees the performance of the global asymptotic stability.
05 Oct 2003
TL;DR: In this article, the authors proposed an agent-based planning method for a demand bus system with multiple buses, where an agent exists for each bus, and it solves the routing problem of the bus by a heuristic rule based method, and solves the assignment problem by auctions and negotiations among agents.
Abstract: In the present paper, we propose an on-line operation planning method for a demand bus system with multiple buses It is necessary to solve a passengers assignment problem and a routing problem in real time in operating the demand bus system We propose an agent-based planning method In the proposed method, an agent exists for each bus, and it solves the routing problem of the bus by a heuristic rule based method, and solves the assignment problem by auctions and negotiations among agents By computational experiments, we will examine effectiveness of the proposed method
05 Oct 2003
TL;DR: In this work a procedure to approach the fault detection and isolation problem in nonlinear systems is proposed by deriving several subsystems, each subsystem containing information about specific faults, from the plant under consideration.
Abstract: One of the difficulties to detect and isolate faults in nonlinear systems via observer-based methods is the design of a residual generator. In this work a procedure to approach the fault detection and isolation problem in nonlinear systems is proposed. The result is obtained by deriving several subsystems, each subsystem containing information about specific faults, from the plant under consideration. Takagi-Sugeno modelling is used to design fuzzy observers and generate residuals. The detection and isolation task is solved by evaluating these residuals. The advantage of the proposed approach is that the design condition for the observers is relaxed. Furthermore the potential use of decoupling techniques is reinforced. The design methodology is shown using a laboratory three tank system.
05 Oct 2003
TL;DR: In this paper, the semi-global stabilization problem of singular linear systems subject to input saturation is addressed, and a reduced-order normal system is obtained by a standard coordinate transformation.
Abstract: The semi-global stabilization problem of singular linear systems subject to input saturation is addressed. A reduced-order normal system is obtained by a standard coordinate transformation. It is further shown that the controller that solves the stabilization problem of the reduced-order normal systems also solves the stabilization problem of the original singular systems.