Robust chaos synchronization of four-dimensional energy resource system via adaptive feedback control

This paper investigates the robust chaos synchronization problem for the four-dimensional energy resource systems with mismatched parameters. Based on the Lyapunov stability theory, the sufficient conditions for the synchronization are obtained analytically and an adaptive feedback control law is derived to make the states of two slightly mismatched chaotic systems asymptotically synchronized. Finally, some numerical simulations are performed to verify the proposed results.     

Robust control of flexible-joint robots using voltage control strategy

So far, control of robot manipulators has frequently been developed based on the torque-control strategy. However, two drawbacks may occur. First, torque-control laws are inherently involved in complexity of the manipulator dynamics characterized by nonlinearity, largeness of model, coupling, uncertainty and joint flexibility. Second, actuator dynamics may be excluded from the controller design. The novelty of this paper is the use of voltage control strategy to develop robust tracking control of electrically driven flexible-joint robot manipulators. In addition, a novel method of uncertainty estimation is introduced to obtain the control law. The proposed control approach has important advantages over the torque-control approaches due to being free of manipulator dynamics. It is computationally simple, decoupled, well-behaved and has a fast response. The control design includes two interior loops; the inner loop controls the motor position and the outer loop controls the joint position. Stability analysis is presented and performance of the control system is evaluated. Effectiveness of the proposed control approach is demonstrated by simulations using a three-joint articulated flexible-joint robot driven by permanent magnet dc motors.     

Fuzzy neural network-based chaos synchronization for a class of fractional-order chaotic systems: an adaptive sliding mode control approach

Nonlinear Dynamics - This paper deals with chaos synchronization problem between two different uncertain fractional-order (FO) chaotic systems with disturbance based on FO Lyapunov stability...     

Stochastic modeling of tire–snow interaction using a polynomial chaos approach

Developing accurate models to simulate the interaction between pneumatic tires and unprepared terrain is a demanding task. Such tire–terrain contact models are often used to analyze the mobility of a wheeled vehicle on a given type of soil, or to predict the vehicle performance under specified operational conditions (as related to the vehicle and tires, as well as to the running support). Due to the complex nature of the interaction between a tire and off-road environment, one usually needs to make simplifying assumptions when modeling such an interaction. It is often assumed that the tire–terrain interaction can be captured using a deterministic approach, which means that one assumes fixed values for several vehicle or tire parameters, and expects exact responses from the system. While this is rarely the case in real life, it is nevertheless a necessary step in the modeling process of a deterministic framework. In reality, the external excitations affecting the system, as well as the values of the vehicle and terrain parameters, do not have fixed values, but vary in time or space. Thus, although a deterministic model may capture the response of the system given one set of deterministic values for the system parameters, inputs, etc., this is in fact only one possible realization of the multitude of responses that could occur in reality. The goal of our study is to develop a mathematically sound methodology to improve the prediction of the tire–snow interaction by considering the variability of snow depth and snow density, which will lead to a significantly better understanding and a more realistic representation of tire–snow interaction. We constructed stochastic snow models using a polynomial chaos approach developed at Virginia Tech, to account for the variability of snow depth and of snow density. The stochastic tire–snow models developed are based on the extension of two representative deterministic tire–snow interaction models developed at the University of Alaska, including the pressure–stress deterministic model and the hybrid (on-road extended for off-road) deterministic model. Case studies of a select combination of uncertainties were conducted to quantify the uncertainties of the interfacial forces, sinkage, entry angle, and the friction ellipses as a function of wheel load, longitudinal slip, and slip angle. The simulation results of the stochastic pressure–stress model and the stochastic hybrid model are compared and analyzed to identify the most convenient tire design stage for which they are more suitable. The computational efficiency of the two models is also discussed.     

Robust synchronization of nonlinear SISO systems using sliding mode control

We present a robust algorithm to synchronize two different single-input/single-output (SISO) nonlinear systems connected in a master/slave scheme, where the relative degree of the master system (r _m) is greater than or equal to the relative degree of the slave (r _s). The sliding mode control technique is used to design the coupling signal. This discontinuous controller renders the closed-loop system robust with respect to matched bounded disturbances. The synchronization objective is to match the first r _s normal coordinates. Depending on the characteristics of the involved systems, the closed loop system can display full or partial, identical or generalized synchronization. The performance of the proposed controlled synchronization is illustrated numerically and experimentally.     

Control and synchronization of chaos systems using time-delay estimation and supervising switching control

In this paper, we present a new technique, developed using time-delay estimation (TDE) and supervising switching control (SSC), for the control and synchronization of chaos systems. The proposed technique consists of three units: a time-delay estimation unit that cancels system dynamics, a pole placement control unit that shapes error dynamics, and an SSC unit that is activated when the system dynamics are rapidly changing. We prove the stability of the closed-loop system using the Lyapunov analysis method. To verify the control and synchronization performance of the proposed technique (TDE-SSC), we compare it with TDC using numerical simulation. Our results indicate that the proposed scheme is an easily understood, numerically efficient, robust, and accurate solution for the control and synchronization of chaos systems.     

Robust sliding mode control for a class of nonlinear systems using inertial delay control

This paper proposes a robust sliding mode control strategy for an uncertain nonlinear system subjected to time-varying disturbance. The class of system considered includes state-dependent nonlinearity in the input vector (in addition to the plant matrix). The control scheme uses inertial delay control to estimate the lumped uncertainty. The proposed control enforces sliding without using the discontinuous control and without requiring the knowledge of uncertainties or their bounds. The overall stability of the system is proved. The effectiveness of the proposed strategy is verified for model following and robust performance, by simulation of an illustrative example and an application to inverted pendulum system.     

Experimental demonstration of 1.5 GHz chaos generation using an improved Colpitts oscillator

Experimental study of the ultrahigh-frequency chaotic dynamics generated in an improved Colpitts oscillator is performed. Reliable and reproducible chaos can be generated at the fundamental frequency up to 1.5 GHz using the microwave BFG520 type transistors with the threshold frequency of 9 GHz. By the tuning of the supply voltages, we observe complex nonlinear dynamics like period-one oscillation, period-two oscillation, multiple-period oscillation, and chaotic oscillation. Typical time series, autocorrelation, and broadband continuous power spectrum are presented. Furthermore, compared with the corresponding classical Colpitts oscillator, the main advantage of the improved circuit is in the fact that by operating in a chaotic mode it exhibits higher fundamental frequencies and a lower peak side-lobe level.     

Secure communication in wireless sensor networks based on chaos synchronization using adaptive sliding mode control

Due to resource constraints in wireless sensor networks and the presence of unwanted conditions in communication systems and transmission channels, the suggestion of a robust method which provides battery lifetime increment and relative security is of vital importance. This paper considers the secure communication in wireless sensor networks based on new robust adaptive finite time chaos synchronization approach in the presence of noise and uncertainty. For this purpose, the modified Chua oscillators are added to the base station and sensor nodes to generate the chaotic signals. Chaotic signals are impregnated with the noise and uncertainty. At first, we apply the modified independent component analysis to separate the noise from the chaotic signals. Then, using the adaptive finite-time sliding mode controller, a control law and an adaptive parameter-tuning method is proposed to achieve the finite-time chaos synchronization under the noisy conditions and parametric uncertainties. Synchronization between the base station and each of the sensor nodes is realized by multiplying a selection matrix by the specified chaotic signal which is broadcasted by the base station to the sensor nodes. Simulation results are presented to show the effectiveness and applicability of the proposed technique.     

Active control for seismic response reduction using modal-fuzzy approach

An active modal-fuzzy control method using hydraulic actuators is presented for seismic response reduction. In the proposed control system, a new fuzzy controller designed in the modal space produces the desired active control force. This type controller has all advantages of the fuzzy control algorithm and modal approach. Since it is very difficult to select input variables used in fuzzy controller among numerous state variables in the active fuzzy control system, the presented algorithm adopts the modal control algorithm to be able to consider information of all state variables in civil structures that are usually dominated by first few modes. In other words, all information of the whole structure can be considered in the control algorithm evaluated to reduce seismic responses and it can be efficient for civil structures especially. In addition, the presented algorithm is expected to magnify utility and performance caused by efficiency that the fuzzy algorithm can handle complex model more easily. An active modal-fuzzy control scheme is applied together with a Kalman filter and a low-pass filter to be applicable to real civil structures. A Kalman filter is considered to estimate modal states and a low-pass filter was used to eliminate spillover problem. The results of the numerical simulations for a wide amplitude range of loading conditions and for historic earthquake show that the proposed active modal-fuzzy control system can be beneficial in reducing seismic responses of civil structures.     

Robust adaptive speed control of uncertain hybrid electric vehicle using electronic throttle control with varying road grade

The design objective of this paper is to apply various control techniques to control the speed of a hybrid electric vehicle (HEV) using an electronic throttle control system (ETCS). The DC servo motor is used for controlling the angular position of the throttle valve. A proportional-integral-derivative (PID), a self-tuning fuzzy PID (STF-PID) controller and a model reference adaptive system (MRAS) with a sliding mode (SM) adaptation mechanism are used for controlling the speed of the nonlinear vehicle. The integral error performance indices (IEPI) such as the integral of the absolute error (IAE), the integral of the square of error (ISE) and the time domain performance specifications such as overshoot (OS), settling time (ST) and rise time (RT) are taken into consideration for the performance analysis of HEV. The robust H_∞ controller using mixed sensitivity approach is designed and implemented for the linearized HEV. The robust stability of uncertain HEV with H_∞ controller using Kharitonov’s theorem is analyzed, and the stability margin of the linearized vehicle system is determined. These control techniques are developed to achieve the robust performance of the throttle controlled HEV with the target to achieve a wide range of speed, fuel economy, reduced pollution and improved efficiency.     

Synchronization and chaos control by quorum sensing mechanism

Diverse rhythms are generated by thousands of oscillators that somehow manage to operate synchronously. By using mathematical and computational modeling, we consider the synchronization and chaos control among chaotic oscillators coupled indirectly but through a quorum sensing mechanism. Some sufficient criteria for synchronization under quorum sensing are given based on traditional Lyapunov function method. The Melnikov function method is used to theoretically explain how to suppress chaotic Lorenz systems to different types of periodic oscillators in quorum sensing mechanics. Numerical studies for classical Lorenz and Rössler systems illustrate the theoretical results.     

Optical Stokes flow estimation: an imaging-based control approach

We present an approach to particle image velocimetry based on optical flow estimation subject to physical constraints. Admissible flow fields are restricted to vector fields satifying the Stokes equation. The latter equation includes control variables that allow to control the optical flow so as to fit to the apparent velocities of particles in a given image pair. We show that when the real unknown flow observed through image measurements conforms to the physical assumption underlying the Stokes equation, the control variables allow for a physical interpretation in terms of pressure distribution and forces acting on the fluid. Although this physical interpretation is lost if the assumptions do not hold, our approach still allows for reliably estimating more general and highly non-rigid flows from image pairs and is able to outperform cross-correlation based techniques.