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According to statistics, the majority of accidents are attributed to driver negligence, especially when a driver intends to lane change or to overtake another vehicle, which is most likely to cause accidents. In addition, overtaking is one of the most difficult and complex functions for the development of autonomous driving technologies because of the dynamic and complicated task involved in the control strategy and electronic control systems, such as steering, throttle, and brake control. This paper proposes a safe overtaking maneuver procedure for an autonomous vehicle based on time to lane crossing (TLC) estimation and the model predictive control scheme. As overtaking is one of the most complex maneuvers that require both lane keeping and lane changing, a vision-based lane-detection system is used to estimate TLC to make a timely and accurate decision about whether to overtake or remain within the lane. Next, to maintain the minimal safe distance and to choose the best timing to overtake, the successive linearization-based model predictive control is employed to derive an optimal vehicle controller, such as throttle, brake, and steering angle control. Simultaneously, it can make certain that the longitudinal acceleration and steering velocity are maintained under constraints to maintain driving safety. Finally, the proposed system is validated by real-world experiments performed on a prototype electric golf cart and executed in real-time on the automotive embedded hardware with limited computational power. In addition, communication between the sensors and actuators as well as the vehicle control unit (VCU) are based on the controller area network (CAN) bus to realize vehicle control and data collection. The experiments demonstrate the ability of the proposed overtaking decision and control strategy to handle a variety of driving scenarios, including a lane-following function when a relative yaw angle exists and an overtaking function when the approaching vehicle has a different lateral velocity.

Although the antilock braking system (ABS) has been commonly used in electric vehicles (EVs), most of the vehicles still use the traditional hydraulic-based disc brake in which the driving and the braking systems are two individual modules. A novel integrated driving and braking control system with an ABS for EVs was developed, and an electric scooter was used as the experimental object. While braking, the motor acts as a generator. The autonomously generated inertial energy was used to generate a reverse magnetic braking torque and realise an antilock braking control with fast response. Compared with the existing regenerative and short-circuit braking methods, the proposed method uses back electromotive force to yield a reverse magnetic braking torque in a sophisticated manner. In the proposed method, a capacitor-aided regenerative braking strategy was used in an antilock braking controller. For the ABS control design, the slip ratio was maintained within an optimal range for obtaining the best tyre–road surface adhesion using a fuzzy slip ratio controller to prevent the wheel from skidding during emergency braking. For real-world verification, the electric scooter was subjected to various on-road tests to examine the performance of the proposed method.

Remote photoplethysmography (rPPG) has attracted much attention in recent years. This research proposes to apply rPPG to the fitness training scenario, enabling non-contact measurement of the subject's heart rate during training. Currently, most existing approaches suffer from a major weakness, i.e. the subject's body needs to remain stably while conducting measurement, which significantly hinders practical applications of the approach. The main purpose of this paper is to build a training system based on rPPG and fitness machines to provide users with better ergonomic exercise experiences. We have built a spinning bike system that combines a camera and an adaptive controller based on heart rate feedback for tracking the desired exercise intensity. Fuzzy control is introduced in the feedback control loop by considering heart rate and heart rate variability simultaneously for better representation of the physical status. Some preliminary results are briefly presented. This research demonstrates promising performance improvement by combining rPPG heart rate estimation and fitness machine control.

This paper develops a modular multilevel inverter which integrates driving/braking control schemes in a unit for electric vehicles. The multiple driving components are used to balance surg...

A hybrid stepper motor (HSM) can be practically driven by open-loop control, however, it is definitely not enough for the increasing demands on precision control in wide industry applications. In this study, a practical control scheme, consisting of model predictive control (MPC) and extended Kalman filter (EKF), is presented for controlling a sensorless hybrid stepper motor (HSM). Numerical simulations and real-world experiments are conducted to show the performance and effectiveness of the proposed strategy. To extend the practical usage of the presented design, the proposed strategy has been utilized to control an auxiliary adjuster for stereotactic frame fixation system for use in the precise clinical neurosurgery operation.

Swimming, turning, and whip-sweeping propulsion for carangiform locomotion of a fish robot are investigated by means of a 4-link planar tail and an autonomous underwater vehicle (AUV)-like model. It is observed that excellent acceleration occurs when a whip sweeping behavior has been applied to the fish tail. The forward speed can even increases twice to the nominal swimming via the simulation study. The efficient movement is thus incorporated to the fish robot for agile movement. The robot's swimming patterns realize the effect in terms of the forward swimming, turning swimming, acceleration increasing, descended swimming, ascended swimming, depth regulating, and self-stabilization. Verification is accomplished by incorporating the 4-link planar tail, AUV-like model, and a two degree-of-freedom (DOF) barycenter mechanism. The four-link planar tail and 2-DOF barycenter mechanism act, respectively, as the thrust generator and stabilizing actuator for the fish robot. Sliding mode control (SMC) has been applied for three-dimensional (3D) trajectory tracking. Simulation results illustrate satisfactory performances of the fish robot in terms of the fish-like behaviors and maneuverability, which are due to the consequence of the mimicked predator-fish behaviors and performance robustness of the SMC for trajectory tracking under ocean current perturbations and modeling uncertainties.

This paper presents the development of an estimation algorithm for ballistic-target evasive acceleration during the terminal phase of interception. The proposed design is based on an application of the extended state observer, using target information acquired from a seeker to estimate target evasive acceleration. It is applicable to multiple-input multiple-output plants with variable observer gains applied in nonlinear coupled line-of-sight pitch and yaw dynamics. Design and stability analysis are evolved based on the theory of Lyapunov, with noncontinuous, piecewise, smoothly Lyapunov function candidates.

Most electric vehicles use regenerative brakes, since this kind of braking system design recycles electromotive force to increase electric power endurance during braking. This research proposes a sensor-free, integrated driving and braking control system that uses a space-vector-pulse-width module to synthesize stator current by purpose. It calculates the rotor position angle of the motor by detecting variation in the stator current and completes a closed-loop control. When the motor receives a brake command, the controller changes the inverter-switching sequence to generate reverse torque and a magnetic field to complete the driving or braking function using field-oriented control (FOC). This provides a smoother and more accurate motor control than sinusoidal commands with Hall feedback. Compared to the regenerative brake and rheostatic brake, the proposed braking system has a powerful braking torque and shorter reaction time. Comparisons of reaction times for a modified four-wheel electric vehicle equipped with a permanent magnet synchronous motor under neutral-sliding-status, FOC based braking, and short-circuit braking were conducted.

The heart rate of subjects is extracted from video data during exercises and is treated as a negative feedback parameter for the control of fitness devices. The probability distribution in RGB space of the parameters of the skin reflection model is analyzed based on the experimental data taken under a wide range of environmental settings. A novel pulse extraction algorithm is proposed based on this distribution, which sets aside distribution centers as the model parameters for preliminary pulse separation and adopts cascade least mean square adaptive filters to compensate for modeling errors. A Gaussian distribution-based heart rate estimation algorithm is employed for heart rate stabilization. In addition, the concept of heart rate negative feedback control is introduced, e.g., the treadmill speed and incline can be adjusted interactively based on the subject's heart rate. The heart rate measurement accuracy and the control scheme have been evaluated by a self-collected benchmark dataset and a prototype system. The heart rate measurement accuracy is increased over the state-of-the-art algorithms by more than 10% on average. The heart rate negative feedback control improves human–machine interaction performance compared with a traditional control scheme that uses the predefined program regardless of the subjects’ physical state. The proposed technique pioneers new possibilities for the usage of fitness devices.

This study develops a 6-DOF mathematical model for a robotic fish that considers surge, sway, heave, roll, pitch, and yaw. The model considers the conditions of a fish swimming in ocean current perturbations similar to the ocean current perturbations of the slender-body autonomous underwater vehicles. For swimming and turning behaviors, a nonlinear, dynamic, carangiform locomotion model is derived by using a planar four-link model. A 2-DOF barycenter mechanism is proposed to provide body stabilization and to serve as an actuating device for active control design. A barycenter control scheme is developed to change the center of gravity of the robot fish body by moving balancing masses along two axes. The projected torque on x and y axes propel pitch and roll angles to the desired settings. A Stabilizing controller, fish-tail mechanism, rigid body dynamics, and kinematics are incorporated to enable the fish robot to move in three dimensional space. Simulation results have demonstrated maneuverability and control system performance of the developed controller which is proposed to conduct path tracking of the robot fish as it swims under current perturbations.

This research proposes a new type of robust stability – mean robust asymptotic stability for linear time-varying (LTV) uncertain systems and its extension in robust asymptotic stability analysis. The system will feature this kind of stability if its state mean varies towards an equilibrium point. Robust input–output finite-time stability of the LTV uncertain system over a bounded time interval is first analysed by proposing a criterion to characterize the stability condition. The possible cases of steady-state error and state oscillation are then considered and tackled. Finally, some case studies are presented to demonstrate superiority of the proposed work.

It is quite common that the network environment may exhibit time-varying time delays which is the major source of queue oscillation and may destroy stability for a closed-loop connection. This study proposes a transmission congestion control strategy in large-scale wired/wireless network with transmission control protocol under random early detection. The task of time-delay compensation is accomplished here by introducing a pseudo disturbance, named extended network disturbance (END), which characterises the time-delay effect on the system behaviour, and extending to END-based control design. A feedback controller for the purpose is proposed to stabilise the large-scale system. The developed method has been verified using the network simulator.

This paper presents a novel synthesizing genetic logic circuit design based on an existing synthetic genetic oscillator, which provides a function of frequency multiplier to synthesize a clock signal whose frequency is a multiple of that of the genetic oscillator. In the renowned literature, the synthetic genetic oscillator, known as a repressilator, has been successfully built in Escherichia coli to generate a periodic oscillating phenomenon through three repressive genes repress each other in a chain. On the basis of this fact, our proposed genetic frequency multiplier circuit utilizes genetic Buffers in series with a waveform-shaping circuit to reshape the genetic oscillation signal into a crisp logic clock signal. By regulating different threshold levels in the Buffer, the time length of logic high/low levels in a fundamental sinusoidal wave can be engineered to pulse-width-modulated (PWM) signals with various duty cycles. Integrating some of genetic logic XOR gates and PWM signals from the output of the Buffers, a genetic frequency multiplier circuit can be created and the clock signal with the integer-fold of frequency of the genetic oscillator is generated. The synthesized signal can be used in triggering the downstream digital genetic logic circuits. Simulation results show the applicability of the proposed idea.

This research studies a novel method of realizing a nonmechanical antilock braking system (ABS) controller for electric scooters (ESs) based on regenerative, kinetic, and short-circuit braking mechanisms. In which, a boundary layer speed control is proposed for a guarantee of the optimal slip ratio between tires and road surface. The antilock braking controller, combined with this controller, drives a low-side driving circuit to induce either an open-circuit or a short-circuit loop on the motor stator's coil to a load; it thus produces braking actions analogous to those in the conventional ABS control. The proposed ABS controller is practically realized. Improvement of the braking performance for the ABS action is further addressed via real-world experiments.

The potential of the clock lies in its role of triggering logic reaction for sequential biological circuits. This research introduces an idea of designing a genetic clock generator by Fourier series based on the genetic oscillators. The authors generalise the design idea using a combination of fundamental sinusoidal signals. Since biochemical reaction of the biological system is extremely slow, however, transition between minimal and maximal levels is instantaneous for an ideal clock signal; it is thus not directly realisable in biological systems. That means it would be hard to directly synthesize a square wave generator for use as a genetic clock. They apply Fourier series to represent a square wave as a finite summation of sinusoidal waves generated by some genetic oscillators with different harmonic oscillating frequencies, in which the amplitude alternates at a constant frequency between the fixed minimal and maximal levels with the same duration of time.

This paper studies congestion control in local wireless networks supporting transmission control protocol (TCP) under random early detection (RED). In general, congestion delays may cause instability of the routers running active queue management (AQM) protocols such as RED. Moreover, its management efficiency could be reduced by serious queue oscillation. To improve these two drawbacks, we propose a robust congestion controller focusing on the queue oscillation suppression and time-delay compensation based on an idea of nonlinear extended network disturbance (NEND). The time-delay compensation is further performed via the NEND rejection. Furthermore, the proposed strategy has been validated on NS2 showing their applicability.

This paper deals with the problem of sliding mode control to achieve chaotic synchronization for the controlled driven system with an input nonlinear term – the term commonly ignored in the published literature. However, the problem does possess importance in practical applications while hardware limits imposed on the actuating devices need to be considered. The major contribution here is the development of a new adaptive control scheme instead of directly computing the magnitudes of overall nonlinear dynamics for compensation as that commonly adopted in the published literature. In the influence of control input nonlinearity, the adaptive sliding mode control scheme, possessing time-varying feedback gains, can compensate unmatched nonlinear dynamics without knowing their magnitudes. In addition, it is unnecessary to determine these time-varying feedback gains in advance but apply adaptive tuning according to suitably updated rules. Based on the Lyapunov stability analysis, a new condition ensuring stable synchronization is established. Case study and numerical simulations are given to verify effectiveness of the presented scheme.

This paper presents a generalized complete coverage path planning (CCPP) algorithm and its implementation for a mobile robot. The proposed planner contains two concerns: 1) low working time or low energy consumption, and 2) high human safety. For the first concern, we design the optimal path by incorporating two factors: time and energy costs. Describing the working time and energy in terms of a turning parameter simplifies the optimal path design either for minimizing the time or energy cost. For obstacle avoidance in the CCPP, fixed or moving objects are avoided by proposing a field method describing the effects of factors such as working dangerousness and difficulty on the current robot navigation. The human safety is simultaneously guaranteed by this method. Furthermore, a backstepping controller considering constraints imposed on the control input is established to track the optimal route. An implementation of the proposed CCPP for the experimentally mobile robot equipped with this controller is presented; the verification results demonstrate significant performance and practicality of the proposed strategy.

Gene networks in biological systems are highly complicated because of their nonlinear and stochastic features. Network dynamics typically involve crosstalk mechanism and they may suffer from corruption due to intrinsic and extrinsic stochastic molecular noises. Filtering noises in gene networks using biological techniques accompanied with a systematic strategy is thus an attractive topic. However, most states of biological systems are not directly accessible. In practice, these immeasurable states can only be predicted based on the measurement output. In the lab experiment, green fluorescent protein (GFP) is commonly adopted as the reporter protein since it is able to reflect intensity of the gene expression. On this basis, this study considers a nonlinear stochastic model to describe the stochastic gene networks and shows that robust state estimation using Kalman filtering techniques is possible. Stability of the robust estimation scheme is analyzed based on the Ito’s theorem and Lyapunov stability theory. Numerical examples in silico are illustrated to confirm performance of the proposed design.

Recently, design of electric scooters (ESs) has commonly adopted brushless DC motors (BLDCMs) in place of brushed DC motors. This invention develops a new anti-lock braking system (ABS), based on a slip-ratio estimator, for ES utilizing the braking force generated by the BLDCM when electrical energy releases to the load yielding an analogous effect of ABS control in gas-engine vehicles. Comparing to mechanical ABS, the design possesses the advantages of rapid torque responses due to fast actuating response. The electrical ABS is realized by associating with kinematic and Short-circuit braking. A current controller is used to adjust the braking force, while the sliding mode control strategy is adopted to regulate the slip ratio for best road adhesion while braking. Real-world experiments have been conducted for functional and performance verification.

Nonlinear equations of motion for fish-robot have been derived based on three basic motion behaviors, swimming, orientating, and driving. By incorporating the fish-tail mechanism, 2-DOF barycenter mechanism, and autonomous underwater vehicle-like dynamics model, the fish robot motion and maneuverability are considered in north-east-down frame. A sliding mode controller for swimming, orientating, and tracking control of a fish robot in three-dimensional motion is designed. Simulation results demonstrate excellent maneuverability and tracking performance of the fish-robot in three-dimensional swimming, which shows effectiveness of the controller against modeling uncertainty and ocean's current turbulence.

Power line communication (PLC) has been used to transmit and receive digital data via power line in wide application. However, power lines weren’t built for data transmission originally. In practice, data transmission is commonly subjected to switching noise by the multi-path effect. The objective of this research is to establish a platform for easily tune the controller for motor control system under the PLC environment. We build up a dynamic model to simulate the power line environment for communication and propose a frequency-shift keying (FSK) technique to modulate and demodulate the signal for the purpose of network control in the disturbed feedback control loop. A modified proportional-integralderivative controller (PID controller) on positioning control a DC servo motor is proposed to against noise corruption while achieving tracking performance.

Unlike taking the same external electrical stimulation to discuss chaotic synchronization in the literature, the synchronization between two uncouple FitzHugh–Nagumo (FHN) neurons with different ionic currents and external electrical stimulations is considered. The main contribution of this study is the application of a robust adaptive sliding-mode controller instead of the active elimination. The proposed sliding mode controller associated with time varying feedback gains cannot only tackle the system uncertainties and external disturbances, but also compensate for the mismatch nonlinear dynamics of synchronized error system without direct cancellation. Meanwhile, these feedback gains are not determined in advance but updated by the adaptive laws. Sufficient conditions to guarantee the stable synchronization are given in the sense of the Lyapunov stability theorem. In addition, numerical simulations are also performed to verify the effectiveness of presented scheme.

Synthetic biology is highly valued in the recent decade. In a previous study, Elowitz and Leibler ( Nature , vol. 403, pp. 335-338, 2000) have constructed a biological oscillator in consisting of three genes, and found out its mathematical expressions. Designing the optimal transcription rates of mRNA and the decay rates of protein concentration to track desired sinusoidal signal and achieve the best oscillation have been becoming a challenge problem since then. Actually, design of an oscillator can be regarded as a tracking design problem from the control engineer's viewpoint. Genetic algorithm (GA) bears the feature of searching the global optimum for the optimization problem. However, subject to the fixed solution structure, the results may not be the cheap ones. In this paper, we introduce the real structure genetic algorithm (RSGA) to solve the design problem of synthetic biological oscillators. The design approach is shown to be capable of yielding genetic oscillators with a cheaper structure.

This paper presents a new approach with a fuzzified eigensystem realization algorithm for identification of flight vehicle models in low-speed wind tunnel (LSWT) and high-speed wind tunnel (HSWT). A variety of variables in model types and testing environment (such as angle-of-attack, sideslip angle, tunnel wind speed) and profile, elevator, and power system (motor and propeller) of mini unmanned aerial vehicle (mini-UAV) model are considered in a power-on mini-UAV testing system in LSWT and an Advisory Group for Aerospace Research and Development (AGARD) standard calibration model in HSWT. The method based on the fuzzy logic inference structure is simple and effective. The results obtained are compared to those obtained by the conventional wind tunnel testing method. To verify the effectiveness of the proposed methodology, simulations are conducted using real-world experimental results that demonstrate that the working performance of the proposed method correlates well as expected.

A new method is proposed to deal with the dual-axis control of a multi-variables system with two induction motors. Investigation of resolving the cross-coupling problem of dual-axis platform is addressed by a neural net-based decoupling compensator and a sufficient condition ensuring closed-loop stability is derived. An evolutionary algorithm processing the universal seeking capability is proposed for finding the optimal connecting weights of the neural decoupling compensator and the gains of PID controllers. Extensive numerical studies verify the performance and applicability of the proposed design under a variety of operating conditions.

This paper presents a new approach which consists of a fuzzified eigensystem realization algorithm (FERA) to identify the parameters of the designed mini-UAV model performance in the low speed wind tunnel (LSWT) power on testing system. On the basis of the identification scheme, it is able to reduce system operational cost of wind tunnel tests and provide a tool for predicting results without resorting to on-site experiments. A variety of variables in model types and testing environment such as model profile, angle of attack, elevator, tunnel wind speed and power system (motor and propeller) are considered. The method based on logic devices is simple yet effective. The results obtained are compared to those obtained by the conventional wind-tunnel testing method. To verify effectiveness of the proposed methodology, both of simulations and real-world experiments are conducted. The results show that the working performance of the proposed method correlates well with expectation.

This paper presents a method to optimize the train-speed trajectory and control between successive stations for mass rapid transit systems with the cable signaling system. The MAX–MIN ant system is utilized to search for the optimal speed codes of each section while taking track gradient, average speed, restriction of train speed, acceleration and jerk into consideration. The train acceleration is further regulated by a fuzzy-PID gain scheduler to meet the speed commands determined. Satisfactory simulation results show applicability and effectiveness of the proposed approach as a tool for designing an energy-saving mass rapid transit system.

How to filter noises in the noisy gene networks by systematic control strategies and biological techniques are attractive issues to engineers and biologists. However, the internal states of most biological systems might not be directly accessible. One may only estimate the internal unmeasurable states from the measuring output. At present, the green fluorescent protein (GFP), which is a reporter protein, has been used to reflect the reaction's intensity of the gene networks. Here, a robust estimator for state estimation of a class of noisy nonlinear gene networks with uncertain process noise is presented. Quantitative analysis of the estimation performance and stability is conducted. In silico simulations for a real gene network is given to confirm the proposed method.

A new aiming point guidance (APG) law in 3-dimensional space is derived analytically. The guidance law is capable of guiding the missile (interceptor) to a straight collision course with respect to the target. The missile turning rate command proportional to the error angle between the current missile heading and the predicted aim point is calculated based on the predicted target position. Performance of the APG law is numerically evaluated and compared with the proportional navigation guidance (PNG) law. The result of numerical simulation shows that the APG law is superior to the PNG law in terms of miss distance, time of interception and final stage missile turning rate demand.

The analytical understanding and applications of human postural balance could possibly be extended to understand the postural sway. On the basis of a human body model with nine segments and articulations at the neck, waist, hip, knee, and ankle, a two-stage feedback control law to remain the human body’s upright posture subjected to the subjective verticals is developed. The movement equations for a 24 DOFs body model are determined first. A hybrid control law is then developed for balancing. For the controller, the primary part is designed to track the desired reference trajectory, and the secondary part is developed to compensate for the influences due to modeling uncertainties and external disturbances. The results developed herein are to be served as a basis for stance posture control of bionic robots or motion-aid robots.

PurposeThe purpose of this paper is to develop the multi‐degree‐of‐freedom measurement system to test, verify, and control the nano‐measuring machine.Design/methodology/approachA generic differential model approach is constructed to numerically describe the hysteresis effects of piezoelectric actuators. Based on the generic differential model, a feedforward compensator with a proportional integral (PI) type controller is designed to compensate for the hysteresis nonlinearity of a piezoelectric actuated three degree‐of‐freedom coplanar nanostage which can provide high‐precision applications.FindingsThe Z‐tilts (z, pitch, and roll motion) error compensation stage of the nano‐measuring machine is accomplished. Moreover, a high‐resolution laser interferometer is used to measure position accurately.Originality/valueThis paper contributes to develop a tracking control design method for the piezoelectric motion platform which combines a closed‐loop feedforward compensator with a PI type controller.

This paper deals with the electro-mechanical transfer functions of an ultrasonic wheel system. The objective is to initiate a mode that can produce certain relative dynamic responses in the proposed ultrasonic wheel system. The performance will be parameterized by system inputs in an attempt to obtain an optimal operational configuration. The electro-mechanical transfer function model of the piezoelectric ultrasonic wheel based on the lateral elliptical motion is derived for the control application and certification of its load-characteristic parameters and also predicts the wheel system performance. On this basis, we can determine whether the output of the wheel system will be stable. The contact-dynamics behaviors of the stator are also studied. These derived formulations in this paper are based on the general concept of the constitutive laws governing piezoelectric materials which permit the introduction of kinetic energy, electrical energy, and geometric constraints relating to the deformation variables.

This paper develops an innovative optimization method, real structured genetic algorithm (RSGA), which combines the advantages of traditional real genetic algorithm (RGA) with structured genetic algorithm (SGA), and applies it for digital filter and control design optimization problems. For infinite impulse response (IIR) filter designs, the proposed approach fulfills all types of filters by minimizing the order of the filter and the absolute error of both passband and stopband. Both system structure and parametric variables are simultaneously optimized via the proposed chromosome scheme. The approach has also been extended to deal with robust control design problems. The approach offers an effective method for designing an optimal controller with robust stability. Simulation and experimental results conveys the excellence of the proposed algorithm over traditional approaches in convergence speed, performance, cost effectiveness, and attains simpler structure.

A fuzzy logic-based guidance design for longer engagement in time and beneficial interception attitudes is investigated and proposed here. The integrated fuzzy logic-based guidance scheme consisting of vertical, midcourse and terminal guidance phases can intercept the target from diverse aspects. The engagement strategy in the vertical guidance phase includes general vertical launch to handle the case of longer engagement ranges, and vertical launch with back turn (BT) to handle shorter engagement ranges. Numerical experimental results show excellent engagement performance and defensible volumes.

It has been known that time delays may not only degrade the performance of the closed-loop control systems, but also induce instability due to the introduction of extra phase lag. The focus of this paper is to find out a way to design a robust controller for networked control systems (NCSs) with time-varying communication delays. To this aim, a mixed fuzzy-PID/neural network compensating scheme is proposed so as to alleviate the influence resulting from uncertain communication delays while maintaining system performance. A condition ensuring stability of the NCS is derived from the system's input–output viewpoint. The effectiveness and superiority of our proposed approach are fully verified in an experimentally networked pneumatic control system.

A self-regulating fuzzy control (SRFC) design method is proposed; this control system uses a gradient rule modification method to regulate the fuzzy rules. Moreover, to reduce the number of fuzzy rules and to strengthen the robustness of SRFC, a self-regulating fuzzy sliding-mode control (SRFSMC) design method is also developed. Both the SRFC and SRFSMC systems contain two sets of fuzzy inference logic, one being the control regulator and the other the rule modifier. The proposed SRFC and SRFSMC systems can automatically regulate the fuzzy rules to achieve satisfactory performance and make the computation easy and, hence, they are suitable for real-time control. Finally, the proposed SRFC and SRFSMC systems are applied to control a forward DC-DC converter to illustrate their effectiveness. A microcontroller-based experimental system is implemented. Experimental results show that the proposed SRFC and SRFSMC systems are robust with regard to different input voltages and load resistance variations for the forward DC-DC converter.

This paper proposes an effective missile radome error compensator by incorporating a nondestructive dither on the missile guidance loop to improve tracking accuracy. The compensation strategy predicts the radome slope error by introducing the dithering techniques along with band-pass filtering mechanism. A new condition is derived to ensure the guidance and control system stability while there is in the presence of the compensation error. As an application, the design methodology is extended to deal with the gimbal friction compensation problem. Simulation study confirms efficacy of our proposed approach.

This paper presents a new approach to deal with the dual-axis control design problem for a mechatronic platform. The cross-coupling effect leading to contour errors is effectively resolved by incorporating a neural net-based decoupling compensator. Conditions for robust stability are derived to ensure the closed-loop system stability with the decoupling compensator. An evolutionary algorithm possessing the universal solution seeking capability is proposed for finding the optimal connecting weights of the neural compensator and PID control gains for the X and Y axis control loops. Numerical studies and a real-world experiment for a watch cambered surface polishing platform have verified performance and applicability of our proposed design.

Human suffering from vertiginous might experience their body tilting and may eventually fall over. The analytical understanding and applications of human posture control could possibly be extended to understand the postural sway. On the basis of a simplified human body model with two stiff segments and articulation at the hip and ankle, this paper presents a two stage feedback control law for assisting balance in the human’s standing posture under interference of subjective verticals. A robust control law is developed from a control-theoretical point of view to guarantee posture stability under disturbances caused by vertigo. In understanding the task of posture control feedback, the control theory based on the human model could be a source of inspiration to physiologists for physiological modeling and understanding of complex mechanical and neurological interactions. The results developed are to be used as a basis for stance posture control of bionic robots and motion-aid robots.

This paper proposes an optimal control approach for a robust control design problem of the neutral type time-delay systems, taking parameter uncertainties and state delay into account. The robust control design problem can be equivalently transformed into an optimal control problem, and the amount of plant uncertainties is indirectly reflected in the performance index. By introducing algebraic manipulations and appropriate uncertainty descriptions, the uncertain dynamical system can not only achieve stability, but can also reach the guaranteed level of performance. A suitable linear state feedback control law is characterized via Lyapunov stability theory to ensure quadratic stability and performance robustness of the closed-loop system. Copyright © 2008 John Wiley & Sons, Ltd.

In practical electro-pneumatic or hydraulic servo mechanism, there is usually an unavoidable operating delay time in the solenoid valves. This may sometimes cause closed-loop instability if the time delay is not treated carefully in the control system designs. Furthermore, pneumatic actuators can offer high performance at low cost, but are often suffered from external disturbances depending on the operating conditions. This paper proposes a non-model-based design approach for pneumatic actuating systems. In the proposed control system, a gain scheduled fuzzy-PID controller ensures tracking performance an adaptable wavelet neuro compensator compensates for time-delay of the control valve, and a disturbance rejecter diminishes influence from load changes. A condition ensuring the closed-loop stability is derived. The proposed design is experimentally verified to show its effectiveness.

This paper presents singularity characterization and optimal path planning for a new three links six degreesof- freedom (DOFs) parallel manipulator. To achieve high speed handling and machining, the base platform is equipped with three linear slideways each one actuated by a linear DC motor, and each extensible vertical link connecting the upper and base platforms is actuated by an inductive AC servo motor. Characterization of workspace, singularity, and development of an optimal path planner are presented. Our special emphases are on characterization of the platform singularity using genetic algorithms (GAs) and singularity avoidance of the path planning based on a DNA evolutionary computing algorithm. We propose a path planning scheme whose coding technique speeds up the execution of search for fast path generation within the feasible workspace.

This paper presents an advanced aircraft flight control system which is capable of providing failure detection, identification, and adaptive compensation in the event of the damage of control surfaces. The new approach is based on the detection of immediate changes of correlation between pitching, yawing, and rolling rates. The failure compensation mechanism is realized by an adaptive wavelet neural net-based proportional-integral-derivative (PID) controller. The fault-tolerant mechanism is activated to regain effective control of the damaged aircraft whenever a control surface failure is detected. Design of a real-time executive kernel based on the RT-Linux operating system is experimentally conducted to realize and verify functions of our proposed design.

This paper presents singularity characterization and path planning design for a newly developed 3 leg 6 degree‐of‐freedom (DOFs) parallel manipulator. Special emphasis is placed on characterizing the platform singularity and singularity avoidance of path planning based on genetic algorithms. The path planning scheme proposed uses a real‐coded genetic algorithm including a modified crossover and a swap mutation for searching out the shortest moving path in the available workspace.

The paper proposes an integrated controller which combines feedforward, PID and a cross-coupling controller to achieve high accuracy for a dual-axis piezoelectric actuated platform. A Preisach model is created to numerically describe the hysteresis behavior of the piezoelectric actuators. On the basis of the Preisach model, a feedforward compensator is developed to compensate for the hysteresis nonlinearity. A PID controller is introduced to further suppress the tracking error due to the modeling inaccuracy and hence to obtain precision tracking control. Finally, a neural net-based cross-coupling control scheme is proposed to reduce the contour errors, which are very typical in dual-axis tracking control problems. The approach developed is numerically and experimentally verified with a variety of operating conditions.

The aim of this paper is to characterize a mathematical model including canal-otolith interaction to describe biological interaction of the human upright standing posture and biological characteristics. The model explains and describes subjective vertical orientation and angular velocity induced static tilt. On the basis of the model a state feedback control law is presented to assist the balance of the human's standing posture that is interfered by subjective verticals. The subjective verticals involving the subjective visual and postural verticals are treated as the external disturbance, and a robust control law is developed to guarantee the posture stability while there is plant uncertainties caused by the effect of vertigo.

An integrated fuzzy-logic-based missile side force control mechanism is proposed for the interception of ballistic targets in three-dimensional space. Stringent scenarios when the missile intercepts the ballistic target at higher attitudes are considered. Conventional guidance systems with the aerodynamically controlled mechanism alone are usually incapable of engaging a high-speed target at low-air-density layers. To overcome the difficulty because of insufficient manoeuvrability, a fuzzy side force control scheme configured with two additional auxiliary thrusters is proposed to generate extra transverse acceleration and thereby to reinforce the engagement performance. A simulation study proves the effectiveness of the proposed approach.

Currently, most multi-axis in the modern CNC machines manipulate individual axial control in each axis of motion which is separately driven and the control loop only one axis. It is known that modeling uncertainty and nonlinear disturbance significantly affect performance in the tracking control on each axis and the contour cutting in CNC machines. Control design based on the traditional approaches in each axis may be insufficient to handle that kind of task in multi-axis motion platforms. An approach is presented here to improve the CNC cutting performance in contour tracking by incorporating adaptive proportional-integral-derivative (APID) and cross-coupling control (CCC) for the purpose. We propose an improved method for precision multiple motion control by combining individual axis control and CCC in the controller design. It consists of two parts: APID and sliding mode control which is with adjustable PID control gains influenced from a sliding hyper plane to reduce tracking error of each axis.; adaptive CCC works to deal with the tracking error of the individual axis together with the coupling error and applies the combined error to a decoupling controller for contour error minimization. Extensive simulation results based on the three-axis motion is compared to traditional PID control showing the effectiveness of our proposed design.

The usefulness of a genetic clock lies in its role to stimulate a sequence of logic reactions for sequential biological circuits. A clock signal is a periodic square wave, its amplitude alternates at a steady frequency between fixed minimal and maximal levels. Transition between the minimum and the maximum is instantaneous for an ideal square wave; however, the function is unrealisable in physical bio-systems. This research develops a new genetic clock generator based on a genetic oscillator, in which, a sine wave generator is adopted as a signal oscillator. It is shown that combination of a genetic oscillator with a toggle switch is able to generate clock signals forming an efficient way to generate a near square wave. In silico study confirms the proposed idea.