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This brief proposes a simple control approach for a class of uncertain nonlinear systems with unknown time delays in strict-feedback form. That is, the dynamic surface control technique, which can solve the 'explosion of complexity' problem in the backstepping design procedure, is extended to nonlinear systems with unknown time delays. The unknown time-delay effects are removed by using appropriate Lyapunov--Krasovskii functionals, and the uncertain nonlinear terms generated by this procedure as well as model uncertainties are approximated by the function approximation technique using neural networks. In addition, the bounds of external disturbances are estimated by the adaptive technique. From the Lyapunov stability theorem, we prove that all signals in the closed-loop system are semiglobally uniformly bounded. Finally, we present simulation results to validate the effectiveness of the proposed approach. Index Terms--Dynamic surface control, function approximation technique, uncertain nonlinear systems, unknown time delays.

In this paper, we propose a high-resolution time--frequency-domain reflectometry technique as a methodology of detection and estimation of faults on a wire. This method adopts the time--frequency cross-correlation characteristics of the observed signal in both the time and frequency domains simultaneously. The accuracy of the proposed method is verified with experiments using a radio-guide-type coaxial cable and comparing it with traditional time-domain as well as frequency-domain reflectometry methods. It is clearly shown here that the proposed algorithm produces excellent results compared to the conventional methods for single as well as multiple fault cables. Index Terms--Chirp signal, fault detection, fault estimation, time--frequency cross-correlation function, time--frequency-domain reflectometry (TFDR), resolution.

In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances. Index Terms--Adaptive observer, dynamic surface control (DSC), flexible-joint electrically driven (FJED) robots, output feedback, robust control, self-recurrent wavelet neural network (SRWNN).

An improved pinch detection algorithm is proposed for low-cost antipinch window control systems. Apart from previous works, the proposed algorithm makes use of torque rate information to sense pinched conditions and to perform safety precautions. The motivation for this approach comes from the idea that the torque rate is less sensitive to motor parameter uncertainty than the torque or the angular velocity. The pinch estimator is designed by applying steady-state Kalman filter recursion to the augmented system model which includes the motor dynamics model and an additional torque rate state. The external torque rate is estimated using angular velocity measurements calculated from the Hall sensor output. A systematic way to set a reasonable threshold of the torque rate estimates under pinched conditions is suggested through deterministic estimation error analysis. Therefore, the proposed algorithm is able to prevent performance degradation due to the empirical threshold level as well as due to motor parameter variations. Experimental results show that our method satisfies EU legal requirements and guarantees robustness against parametric uncertainties. Index Terms--Kalman filter, power window control, road vehicle electronics, torque estimation, vehicular safety systems.

The robust stabilization method via the dynamic surface control (DSC) is proposed for uncertain nonlinear systems with unknown time delays in parametric strict-feedback form. That is, the DSC technique is extended to state time delay nonlinear systems with linear parametric uncertainties. The proposed control system can overcome not only the problem of "explosion of complexity" inherent in the backstepping design method but also the uncertainties of the unknown time delays by choosing appropriate Lyapunov-Krasovskii functionals. In addition, we prove that all the signals in the closed-loop system are semiglobally uniformly bounded. Finally, an example is provided to illustrate the effectiveness of the proposed control system. Index Terms--Dynamic surface control (DSC), nonlinear time delay system, parametric uncertainty.

A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system. Index Terms--Dynamic surface control (DSC), flexible-joint robots, robust control, self-recurrent wavelet neural network (SRWNN).

This paper sharpens the recently developed linear-matrix-inequality-based digital redesign (LMI-based DR) technique. The motivation comes from the fact that some unexpected state matching performance might be experienced as a sampling period approaches zero. To improve the state matching performance for that case, a refined LMI-based DR is proposed by using the delta operator that creates rapprochement between the differential and the shift operators. It is proved that the analog control performance is recovered by the refined DR scheme in the fast sampling limit. Index Terms--Delta-operator, digital redesign, linear matrix inequality, performance recovery, stability.

In this paper, a generalized predictive control (GPC) method based on self-recurrent wavelet neural network (SRWNN) is proposed for stable path tracking of mobile robots. Since the SRWNN has a self-recurrent mother wavelet layer, it can well attract the complex nonlinear system although the SRWNN has less mother wavelet nodes than the wavelet neural network. Thus, the SRWNN is used as a model identifier for approximating on-line the states of the mobile robot. In our control system, since the control inputs, as well as the parameters of the SRWNN identifier are trained by the gradient descent method with the adaptive learning rates (ALRs), the optimal learning rates which are suitable for the time-varying trajectory of the mobile robot can be found rapidly. The ALRs for training the parameters of the SRWNN identifier and those for learning the control inputs are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of the GPC system. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control strategy. Index Terms--Adaptive learning rate (ALR), gradient descent method, generalized predictive control (GPC), mobile robots, self-recurrent wavelet neural network (SRWNN).

A control problem of Takagi--Sugeno fuzzy systems with a time-varying input delay and norm-bounded uncertainties is addressed. The input delay is well-known in making the closed-loop stabilization difficult. A sufficient condition for the robust fuzzy-model-based stabilization is derived based on the Lyapunov--Razumikhin stability theorem, without the assumption of the variation rate on the delay. A constructive design scheme is presented in the form of the iterative convex optimization problem. The effectiveness of the proposed method is demonstrated by a numerical simulation of a nonlinear mass-spring-damper system.

In this paper, the effects of visual feedback and aging on postural sway systems and signals are investigated by analyzing the transient phase difference between 'input' and 'output' which correspond to center of pressure (COP) and center of mass (COM), respectively. In order to analyze the transient phase difference characteristics of COP and COM, a relatively new cross time-frequency analysis technique that provides time-and frequency-localized phase difference information is utilized. The feedback control process in the postural sway is interpreted in terms of a feedback compensator which is characterized in terms of a phase difference. Using the experimental results of the transient phase difference obtained from the cross time-frequency distribution, it is demonstrated that the postural control of young persons are more stable and rely more on visual sensory feedback to stabilize postural control compared to that of the elderly persons. Index Terms--Aging, cross time-frequency distribution, feedback control, phase difference spectrum, postural sway, time-frequency analysis, visual sensory system.

This paper presents a novel approach for navigation of cleaning robots in an unknown workspace. To do so, we propose a new map representation method as well as a complete coverage navigation method. First, we discuss a triangular cell map representation which makes the cleaning robot navigate with a shorter path and increased flexibility than a rectangular cell map representation. Then, we propose the complete coverage navigation and map construction methods which enable the cleaning robot to navigate the complete workspace without complete information about the environment. Finally, we evaluate the performance of our proposed triangular cell map via the existing distance-transform-based path-planning method comparing it to that of the rectangular cell map. Also, we verify the effectiveness of the proposed methods through computer simulations. Index Terms--Cleaning robot, complete coverage, mobile robot, path planning, templates, triangular cell map representation.

In this paper, a fuzzy control scheme, which employs the output feedback control approach, is suggested for the stabilization of nonlinear systems with uncertainties. The uncertain nonlinear system can be represented by uncertain Takagi-Sugeno (TS) fuzzy model structure, which is further rearranged to give a set of uncertain linear systems. A switching-type fuzzy-model-based controller, which utilizes the static output feedback control strategy, is designed based on this preliminary study. Theoretical analysis guarantees that under the control of the proposed technique, the uncertain nonlinear system is stabilizable by the switching-type static output-feedback fuzzy-model-based controller. Finally, two computer simulation examples are provided to show the effectiveness and feasibility of the developed controller design method.

This brief concerns a new digital redesign (DR) technique for an observer-based output-feedback control (OBOFC) system. The term DR involves converting an analog controller into an equivalent digital one in the sense of state-matching. The considered DR problem is viewed as convex minimization problem of the norm distances between linear operators to be matched and its constructive condition is formulated in terms of linear matrix inequalities (LMIs). The main features of the proposed method are that the state estimation error in the plant dynamics is considered for the state-matching condition that was ignored in the earlier works; the stability is guaranteed within the redesign procedure; the separation principle on the DR of the OBOFC is explicitly shown. A numerical example is included for visualizing the feasibility of the proposed technique. Index Terms--Digital redesign, linear matrix inequality (LMI), observer-based output-feedback (OBOF), separation principle, stability.

In this brief, we develop an intelligent digital redesign method for hybrid state space fuzzy-model-based controllers, effective for stabilization of continuous-time uncertain nonlinear systems under discrete-time controller. Takagi-Sugeno (TS) fuzzy model is used to represent the complex system as multiple and uncertain linear state-space models over different local operating regions. A continuous-time fuzzy-model-based controller is then synthesized for stabilization, where the guaranteed-cost design method is utilized to cope with system uncertainties. The local controllers of the continuous-time fuzzy-model-based controller are then converted to equivalent discrete-time counterparts and aggregated through the fuzzy inference system to give a discrete-time fuzzy-model-based controller. Finally, a TS fuzzy model for the chaotic Lorenz system is used as an illustrative example to show the effectiveness and the feasibility of the developed design method. Index Terms--Chaotic Lorenz system, fuzzy-model-based control, guaranteed-cost control, intelligent digital redesign, linear matrix inequality, sampled-data control.

This brief studies dynamic characteristics of a permanent-magnet synchronous motor (PMSM). The mathematical model of the PMSM is first derived, which is fit for carrying out the bifurcation and chaos analysis. Then, the steady-state characteristics of the system, when subject to constant input voltage and constant external torque, are formulated. Three cases are discussed and, for each case, conditions are derived under which the dynamic characteristics of the system are either of steady-state type, limit cycles or chaotic, thus by properly adjusting some system parameters, the system can exhibit limit cycles (LCs) or chaotic behaviors at will. Finally, computer simulations are presented to verify the existence of strange attractors in the PMSM. Index Terms--Chaos, Hopf bifurcation, limit cycle (LC), permanent-magnet synchronous motor (PMSM).

In this paper, a simple and systematic control design method is proposed for a discrete-time Takagi-Sugeno (TS) fuzzy system, which employs the parallel distributed compensation (PDC) to determine the structure of a fuzzy controller so as to make all the Lyapunov exponents of the controlled TS fuzzy system strictly positive. This approach is proven to be mathematically rigorous for anticontrol of chaos for a TS fuzzy system, in the sense that any given discrete-time TS fuzzy system can be made chaotic by the designed PDC controller along with the mod-operation. A numerical example is included to visualize the anticontrol effect. Index Terms--Anticontrol of chaos, Lyapunov exponents, parallel distributed compensation (PDC), TS fuzzy system.

In the above paper [1], a Takagi--Sugeno (T-S) fuzzy-model-based output regulation methodology is proposed. However, since the problem formulation is incorrect, the derived design techniques may not accomplish the control objectives. We illustrate the reasons and show counterexamples. Index Terms--Coordinate transformation, fuzzy control, output regulation.

An approach is proposed for making a given stable continuous-time Takagi-Sugeno (TS) fuzzy-system chaotic, by first discretizing it and then using state feedback control of arbitrarily small magnitude. The feedback controller chosen among several candidates is a simple sinusoidal function of the system states, which can lead to uniformly bounded state vectors of the controlled system with positive Lyapunov exponents, and satisfy the chaotic mechanisms of stretching and folding, thereby yielding chaotic dynamics. This approach is mathematically proven for rigorous generation of chaos from a stable continuous-time TS fuzzy system, where the generated chaos is in the sense of Li and Yorke. A numerical example is included to visualize the theoretical analysis and the controller design.