Search

This paper focuses on autonomous underwater vehicle (AUV) stabilization in the nonlinear descriptor model, as well as some AUV limitations such as model uncertainty, singularity, saturation constraint, and time delay. The capability of the descriptor model to show the real model is more reasonable than the standard state-space model. Based on the constructed Lyapunov function method and applying the bilinear matrix inequalities technique, all of the constraints are handled by introducing the new theorem. This theorem aims to design a state feedback with the intent that the closed-loop system be admissible. Here, the results are less conservative than other approaches. This issue has not yet been fully addressed in the literature, especially on AUVs. Theorem achievement is implemented on new AUV descriptor model that is obtained and introduced here. This method covers both neutral and descriptor systems. Also, it can be generalized and applied to conventional AUVs or similar dynamics. Examples and simulation results illustrate the effectiveness of the proposed approach.

This article investigates an enhanced optimal robust time-delay stabilizer for an autonomous underwater vehicle in the descriptor model. Time-delay, model uncertainty, and actuator saturation constraint are some practical challenges in autonomous underwater vehicle controller design. In this regard, an appropriate autonomous underwater vehicle descriptor model is obtained, and sufficient stabilization conditions are determined in the terms of linear matrix inequality. The obtained criterion guarantees the system to be regular, impulse-free, and stable. Meanwhile, the delay-dependent and rate-dependent conditions are taken into account. Furthermore, uncertainty and time-delay are time-variant. This method includes a tuning factor for practical design aspects and tradeoff among desired requirements. Also, as an essential general requirement in non-linear systems, the maximal estimate of the attraction domain is proposed as an optimization problem. Numerical examples and simulations illustrate that the proposed methods are effective and useful in less conservative results. The technique can be generalized and applied to the most conventional autonomous underwater vehicles.

In this article, an observer-based adaptive hybrid attitude controller is presented that overcomes the topological obstructions associated with the global attitude stabilization. This hybrid controller consists of two major parts: an adaptive trimodal hybrid controller to eliminate $unwinding$ phenomenon, and a centrally synergistic potential function. In the adaptive trimodal hybrid controller, the first logic variable selects, which quaternion representation of the desired attitude should be tracked. Furthermore, an adaptive technique is introduced to collaborate with the second logic variable to adapt the hysteresis width. The third logic variable controls the mismatch between the auxiliary dynamical system and the actual attitude. Moreover, an auxiliary dynamical system and a nonlinear angular velocity observer are presented whose outputs are utilized in the proposed feedback control law to attain the necessary damping. Furthermore, a new centrally synergistic potential function is presented to cooperate with the trimodal hybrid controller to overcome the topological obstruction associated with the vector bundle structure. The robust global asymptotic stability of the consequent closed-loop system is guaranteed through a Lyapunov analysis. A comparative analysis in simulations illustrates the effectiveness and superiority of the proposed control scheme.

This paper peruses the Doppler-bearing passive target tracking (DBT), a task that is subject to the nonlinear measurement equations. These measurement equations form the target tracking a nontrivia...

The main purpose of this paper is to introduce a hybrid controller for global attitude tracking of a quadrotor. This controller globally exponentially stabilizes the desired attitude, a task that is impossible to accomplish with memoryless discontinuous or continuous state feedback owing to topological obstruction. Thereafter, this paper presents a new centrally synergistic potential function to construct hybrid feedback that defeats the topological obstruction. This function induces a gradient vector field to globally asymptotically stabilize the reference attitude and produces the synergy gap to generate a switching control law. The proposed control structure is consisting of two major parts. In the first part, a synergetic controller is designed to cooperate with the hybrid controller, whereas it exponentially stabilizes the origin of the error dynamics. In the second part, a hybrid controller is introduced to globally stabilize the attitude of the quadrotor, where an average dwell constraint is considered with the switching control law to guarantee the exponential stability of the switched system. Finally, the effectiveness and superiority of the proposed control technique are validated by a comparative analysis in simulations.

In this paper, a new fault-tolerant control strategy is suggested to control the induction motors (IMs). The mathematical model of IMs is supposed to be unknown and also the main disturbances such as perturbation in the rotor resistance, and suddenly changes in the load torque are considered. A general type-2 fuzzy system using a new non-singleton fuzzification is proposed to cope with the uncertainties. The robustness and the stability of the proposed control scheme is studied on basis of the Lyapunov theorem. The simulation results show that the suggested control method has good performance in the versus of unknown dynamics of IM, time-varying disturbances, abrupt faults and measurement errors. The proposed scheme is compared with other popular control systems and other kind of fuzzy systems and singleton fizzification.

In this paper, a novel fractional-order adaptive controller is presented for a class of nonlinear systems with unknown dynamics. The dynamics of the system is considered to be fully unknown. The mu...

Chaotic secure communication via synchronization of chaotic systems has attracted increasing attention in recent years. This note aims to introduce the function projective synchronization (FPS) of ...

Kalman filter and its different variants are commonly used as optimal methods for fault detection in various types of system components. In this paper, a newly introduced type of aforementioned filters, called modal Kalman filter, is extended and utilized in order to estimate the states of nonlinear systems, for sensor fault detection purposes, in a class of nonlinear certain systems. This method, in contrast to the extended Kalman filter, which employs only the linear term of Taylor expansion, retains higher-order terms; as a result, the estimation error will reduce accordingly. Practicality and effectivity of this method, and its superiority over Kalman filter, in terms of accuracy and promptness of sensor fault detection, are also verified with simulation results.

This study presents a novel fractional-order nonlinear sliding mode controller (FONSMC) based on an extended nonlinear disturbance observer (ENDOB) for a class of fractional order systems with matched and mismatched disturbances. Firstly, an ENDOB is introduced to estimate both the matched and mismatched disturbances. Then, the fractional-order nonlinear sliding surface is designed to satisfy the sliding condition in finite time. Accordingly, the corresponding FONSMC is proposed using the Lyapunov stability theorem. The proposed method shows an impressive disturbances rejection and also guarantees finite-time stability of closed-loop systems. Finally, the effectiveness of the proposed FONSMC-ENDOB structure is illustrated via numerical simulation. The simulation results exhibit the superiority of the proposed controlling method.

In this study a novel type-2 fuzzy control approach on basis of the adaptive immersion and invariance (I&I) control method is proposed to control of brushless DC motors (BLDCMs). The parameters of the mathematical model of the BLDCM are considered to be unknown and furthermore the dynamics of BLDCM are disturbed by changes of some variables such load torque and phases resistance. The stability is analyzed based on the adaptive I&I theorem and some tuning laws are derived for uncertain parameters. Furthermore, the approximation error is tackled by the proposed fuzzy compensator. The parameters of the fuzzy compensator are tuned through the Lyapunov stability method. The reference signal tracking performance of the suggested control technique is examined in three cases. In the first case the load torque and phases resistance are constant, in the second case the phases resistance is considered to be time-varying and the load torque is abruptly changed and finally in the third case, a comparison with some other well-known control techniques is taken to account. It is shown that the proposed controller results in desired performance.

This paper deals with the fuzzy control design for nonlinear impulsive switched systems modeled by a novel nonlinear Takagi-Sugeno (T-S) fuzzy structure. To model, this structure only uses some of the nonlinearities as premise variables. So, the derived model has fewer rules compared with the traditional T-S fuzzy models that utilize standard local sector nonlinearity; and accordingly, the number of stability/stabilization conditions is sharply reduced. In our structure, considering only a part of nonlinearities as premise variables causes that some of the local models in the consequent part of the fuzzy rules be nonlinear but with less complexity than the original nonlinear system. As a result, the feasibility of our model’s stability criteria is more than those that one can directly establish for the original nonlinear system. Besides, unlike the existing methods in the literature of impulsive switched systems that aim to permanently reduce the value of Lyapunov function candidates, this paper takes into account this process until trajectories reach a sufficient small region containing the origin. Then, within this region, the size of Lyapunov functions is just controlled at impulse instants. This strategy is useful when there are non-vanishing impulses and/or uncertainties, and it is more relaxed when the goal is ultimate bound stability. Finally, to achieve the stabilizing control signal that ensures practical control issues along with smallest ultimate bound and widest region of attraction, this paper also proposes an optimization problem with linear and bilinear constraints. The simulation results represent the performance of the proposed method.

SUMMARYThis paper proposes an adaptive robust impedance control for a single-link flexible arm when it encounters an environment at an unknown intermediate point. First, the intermediate collision point is estimated using a collision detection algorithm. The controller, then, switches from free to constrained motion mode. In the unconstrained motion mode, the exerted force to environment is nearly zero. Thus, the reference trajectory is a prescribed desired trajectory in position control. In the constrained motion mode, the reference trajectory is determined by the desired target dynamic impedance. The simulation results demonstrate the efficiency of proposed control scheme.

This paper studies the global stabilization of a rigid body attitude, a task that is subject to topological obstacles. Theseobstructions preclude the existence of a globally stable equilibrium point. Consequently, the rigid body attitude cannotbe globally stabilized by continuous feedback control laws. In order to resolve this challenge, this paper presents anobserver-based hybrid feedback control law. Thereafter, in order to derive the proposed feedback law, a new kind ofsynergistic potential functions is presented which induces a gradient vector eld to globally stabilize a given set. Moreover, the gradient of the proposed synergistic potential functions is utilized to derive a hybrid angular velocityobserver. The outputs of the proposed observer are employed to produce the necessary damping from the noisy measurements of the attitude. Furthermore, this paper considers two types of constraints: angular velocity constraints, and input torque constraints. Afterward, these constraints are formulated in terms of the Linear Matrix Inequalities (LMI) optimization problem to perform constraints satisfaction at all times. Moreover, this paper introduces a novel hybrid quantizer to deal with the problem of the low-price wireless network. This paper analyzes the global asymptotic stability of the reference set via the Lyapunov's method. Finally, a comparative study in simulations is provided to assess the performance of the proposed control technique.

This paper peruses the attitude control problem of a rigid body, a task that is subjected to topological obstructions. These topological obstructions express that there is no globally asymptotically stable equilibrium point for a system evolving on a compact manifold. Therefore, there exist no continuous or discontinuous feedback control laws to globally stabilize the desired rigid body attitude. Thereafter, this paper presents quaternion-based hybrid feedback to defeat these topological obstacles. The proposed control law is derived from a new kind of centrally synergistic potential functions which is introduced in this paper. This function induces a gradient vector field that globally asymptotically stabilizes the desired attitude. Finally, a simulation study depicts the superior performance of the proposed quaternion-based hybrid feedback control technique.

This paper presents a novel adaptive control for a class of nonlinear switched systems by introducing a sufficient condition for stabilization. Based on the possible instability of all sub-systems, a variable structure (VS) switching rule with an adaptive approach and sliding sector was offered. Moreover, the stability condition of the system can be determined by solving linear matrix inequalities (LMIs) to ensure asymptotic stability. The application of H∞ analysis of nonlinear switched systems was also investigated through the design of the mentioned adaptive control system and defining a VS switching rule. Finally, simulation results were presented to validate the novelty of the proposed method.

This paper peruses the voltage control of a boost DC-DC converter. The hybrid model of the converter is utilized to introduce a new switching control law, which regulates the output voltage of the converter. In this switching control law an average dwell time constraint is considered. This suggestion guarantees the exponential stability of a desired output voltage value. Furthermore, in the proposed switching control law, there exist no Zeno solutions, since the existence of the average dwell time constraint. Moreover, in power converters, two significant concerns are switching loss and electromagnetic interference resulting from numerous rates of variations of voltage and current. Therefore, the salient features of the proposed controller are the mitigation of the switching rate as well as the regulation of the output voltage. Finally, simulation experiments are followed through on a boost converter to validate the effectiveness and superiority of the proposed control strategy.

In this paper, based on Modal series, a new filter is proposed for a nonlinear system state estimation. Modal series is a new method to obtain a closed-form approximate solution of a nonlinear differential equation. Up to now, this series is only obtained in the neighborhood of an equilibrium point. In the proposed method, this series is attained in the neighborhood of the current estimated state vector that is named as Stochastic Extended Modal Series (SEMS). Based on SEMS and proper approximations, the proposed nonlinear filter is converted to a series of linear filters, and the extracted filter is named as Extended Modal Kalman Filter (EMKF). The performance of EMKF is analytically compared with that of Extended Kalman Filter (EKF), and its applicability presented with some simulations. Finally, it is proved that the EKF is a special case of EMKF.

SUMMARYThis paper presents a fractional-order sliding mode control scheme equipped with a disturbance observer for robust impedance control of a single-link flexible robot arm when it comes into contact with an unknown environment. In this research, the impedance control problem is studied for both unconstrained and constrained maneuvers. The proposed control strategy is robust with respect to the changes of the environment parameters (such as stiffness and damping coefficient), the unknown Coulomb friction disturbances, payload, and viscous friction variations. The proposed control scheme is also valid for both unconstrained and constrained motions. Our novel approach automatically switches from the free to the constrained motion mode using a simple algorithm of contact detection. In this regard, an impedance control scheme is proposed with the inner loop position control. This means that in the free motion, the applied force to the environment is zero and the reference trajectory for the inner loop position control is the desired trajectory. However, in the constrained motion the reference trajectory for the inner loop is determined by the desired impedance dynamics. Stability of the closed loop control system is proved by Lyapunov theory. Several numerical simulations are carried out to indicate the capability and the effectiveness of the proposed control scheme.

This study is about the identification problem of continuous-time switched linear systems from low-rate sampled data. The main problem in the identification of such systems, when the sampling rate is low, is that the sampling instances do not coincide with the switching times. Therefore, some of the measured samples are generated from more than one subsystem. This problem was first observed during the sampling of a step-up DC–DC converter at the rate of 100 kHz. The current study aims to explain the theoretical aspects of the identification problem of continuous-time switched linear systems, and to offer a new method for estimating of subsystem parameters plus the switching times. The proposed method accurately determines the switching times which might be between two consecutive sampling instances. The results obtained from the proposed method are used to determine the switching times and parameters of an experimental DC–DC boost converter.

The distributed finite-time control problem through adaptive neural identifier for a group of nonlinear agents with strict-feedback structure is assessed here. The main considered and assessed technical problems in this proposed control strategy are that followers’ states are not fully available for control design, and at the same time, each follower is represented by uncertain nonlinear switched dynamics. Due to the structure of the proposed followers here, a switched linear state observer is constructed to estimate the unavailable states. To finite convergence time guarantee, the backstepping design and finite-time approach are adopted in the distributed control design in a simultaneous manner. The control architecture is chosen to guarantee graph stability through multiple Lyapunov functions. It is revealed that the followers’ outputs are forced to follow the leader output in the finite time, and all signals in the overall closed-loop network system are assured to be bounded. Two simulation examples are presented to further demonstrate the validity of this proposed method.

This paper aims to investigate an efficient numerical scheme for the optimal control of fractional-order dynamic systems. By using the Grünwald–Letnikov approximation for the fractional derivatives and introducing a new transformation in the calculus of variations, the fractional optimal control problem under consideration is converted into a linear programming problem. Then, the internal model principle is employed in order to extend the new scheme for the fractional dynamic systems affected by the external persistent disturbances. Numerical examples and comparative results verify the validity and applicability of the new technique.

In this paper, a passive control scheme based on the fractional-order calculus is proposed. We study the modified complex projective synchronisation between two identical fractional-order complex chaotic systems, and its application in the secure communication. The fractional-order complex chaotic Lorenz system is employed to encrypt the emitted signal. In the transmitter module, the information signal is modulated into one parameter of the Lorenz system. It is assumed that the same parameter is unknown in the receiver module. In order to synchronise two systems with different initial conditions, the controllers and an appropriate parameter update rule are designed. Theoretical analysis and numerical simulations show that this method is feasible and robust to some extent in the presence of channel noise.

This paper investigates fractional Kalman filters when time-delay is entered in the observation signal in the discrete-time stochastic fractional order state-space representation. After investigating the common fractional Kalman filter, we try to derive a fractional Kalman filter for time-delay fractional systems. A detailed derivation is given. Fractional Kalman filters will be used to estimate recursively the states of fractional order state-space systems based on minimizing the cost function when there is a constant time delay (d) in the observation signal. The problem will be solved by converting the filtering problem to a usual d-step prediction problem for delay-free fractional systems.

Among other methods, state estimation using filters is currently used to increase the accuracy of systems. These filters are categorized into the following three branches: linear, nonlinear with Gaussian noise, and nonlinear with non-Gaussian. In this paper, the performance of particle filters is investigated via nonlinear, non-Gaussian methods. The main aim of this paper was to improve the performance of particle filters by eliminating particle impoverishment. A resampling step was proposed to overcome this limitation. However, resampling usually leads to a dearth of samples. Therefore, to virtually increase the number of samples, the available samples were broken into smaller parts based on their respective weights via a clustering approach. The experimental results indicate that the proposed procedure improves the accuracy of state estimations without increasing computational burden.

Wireless sensor networks (WSNs) are highly suitable for target tracking. In such networks, node scheduling is critical in terms of energy consumption and tracking accuracy. A WSN consisting of nodes with multiple bearings-only sensing units is considered in this study and an adaptive approach for the scheduling of such a network is presented. The proposed method continually determines the minimum number of measurements each node should perform in order to keep the tracking error below a certain limit. An extended Kalman filter (EKF) is utilized for target tracking. Tracking accuracy is formulated based on the nonlinear A-optimality measure. The node scheduling problem is reformulated as a linear binary mixed integer programming problem and solved in an online manner. Simulation results show that the proposed method results in less rms position error than the nearest node selection method, especially at the beginning of tracking when there is more uncertainty about the target state. With the same amount of energy consumption, the number of divergent tracks in this method is much fewer in comparison with those of the nearest node selection method.

This paper presents a new compound synchronisation scheme among four hyperchaotic memristor system with incommensurate fractional-order derivatives. First a new controller was designed based on adaptive technique to minimise the errors and guarantee compound synchronisation of four fractional-order memristor chaotic systems. According to the suitability of compound synchronisation as a reliable solution for secure communication, we then examined the application of the proposed adaptive compound synchronisation scheme in the presence of noise for secure communication. In addition, the unpredictability and complexity of the drive systems enhance the security of secure communication. The corresponding theoretical analysis and results of simulation validated the effectiveness of the proposed synchronisation scheme using MATLAB.

This paper presents optimal control of uncertain switched systems in presence of the external disturbance and parametric uncertainty and generally every uncertainty due to modeling error. In this paper, the switching signal is selected a priori and control input is designed to minimize a given cost function. Discrete Linear Quadratic (DLQ) control has been efficiently applied to certain systems as an optimal control. There would seem to be some difficulties to apply discrete linear quadratic control to uncertain switched system. To overcome the problems, this paper presents an appropriate model. Then uncertainties of the uncertain switched system are compensated by robust time-delay controller. Then control input is designed by discrete linear quadratic control. The stability analysis and simulation verify effectiveness of the proposed control approach.

An algorithm is proposed for scheduling dependent tasks in time-varying heterogeneous multiprocessor systems, in which computational power and links between processors are allowed to change over time. Link contention is considered in the multiprocessor scheduling problem. A linear switching-state space-modeling paradigm is introduced to enable theoretical analysis from a system engineering perspective. Theoretical analysis of this model shows its robustness against changes in processing power and link failure. The proposed algorithm uses a fuzzy decision-making procedure to handle changes in the multiprocessor system. The efficiency of the proposed algorithm is illustrated by several random experiments and comparison against a recent benchmark approach. The results show up to 18% average improvement in makespan, especially for larger scale systems.

In this paper we present chaotic synchronization of a Lorenz system using Unscented Kalman Filter (UKF). The UKF has shown to produce better results, than Extended Kalman Filter (EKF), without performing potentially ill-conditioned numerical calculations and linearly approximating the evolution of the state vector covariance. The chaotic synchronization is implemented in the presence of state and measurement noises. Simulation results reveal the superior performance of UKF over EKF for this case.

In this paper, a new fuzzy fading memory (FFM) is developed in order to aid a modified input estimation (MIE) technique and enhance its performance in tracking high maneuvering targets. The MIE has been introduced recently and performs well in tracking low and medium maneuvering targets. However, due to some modeling errors, the accuracy of this tracker may be seriously degraded in presence of high maneuvers. To cope with this difficulty, an intelligent approach based on FFM is presented in this paper. Simulation results prove the efficiency of the proposed method in tracking high maneuvering targets.

Markov Decision Process (MDP) has enormous applications in science, engineering, economics and management. Most of decision processes have Markov property and can be modeled as MDP. Reinforcement Learning (RL) is an approach to deal with MDPs. RL methods are based on Dynamic Programming (DP) algorithms, such as Policy Evaluation, Policy Iteration and Value Iteration. In this paper, policy evaluation algorithm is represented in the form of a discrete-time dynamical system. Hence, using Discrete-Time Control methods, behavior of agent and properties of various policies, can be analyzed. The general case of grid-world problems is addressed, and some important results are obtained for this type of problems as a theorem. For example, equivalent system of an optimal policy for a grid-world problem is dead-beat.

A discrete-time adaptive fuzzy sliding mode controller is proposed for an antilock braking system (ABS) of a 13th order two-wheel nonlinear model of a car. The model includes interaction of front and rear wheel subsystems. The presented controller aims to least depend on a mathematical model, only assuming certain upper and lower bounds of uncertainties. The controller is designed based on a hybrid combination of variable structure control, direct adaptive fuzzy control and linear control. Two fuzzy approximators are used to estimate nonlinear functions of the plant. The controller is global uniform Lyapunov stable. Simulation results show favorable output tracking performance despite poor knowledge of wheel dynamics and system disturbances such as road roughness.

The original version of this article unfortunately contained a mistake. The affiliation of the first author was incorrect. The correct affiliation is: Department of Computer Engineering, Quchan Branch, Islamic Azad University, Quchan, Iran. Journal of Zhejiang University-SCIENCE C (Computers & Electronics) ISSN 1869-1951 (Print); ISSN 1869-196X (Online) www.zju.edu.cn/jzus; www.springerlink.com E-mail: jzus@zju.edu.cn