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Summary: A model predictive cascade controller is proposed in this article to resolve the actuator saturation problem of underwater human‐occupied vehicle (HOV) trajectory tracking. For the kinematic model, a grasshopper optimization‐based model predictive control (MPC) is developed to obtain control velocities with small fluctuations in allowable regions. Based on the desired velocities obtained from the improved kinematic control, the HOV dynamic model is used to generate the corresponding torques and forces using sliding mode control. With the control velocities and forces given by the cascade control strategy, the elimination of actuator saturation during the HOV trajectory tracking can be realized. The proposed controller is verified by simulations using a numerical example based on a four degrees of freedom (4‐DOFs) HOV. [ABSTRACT FROM AUTHOR]

A system of fast moving quadcopters has a high risk of collisions with neighboring quadcopters or obstacles. The objective of this work is to develop a control strategy for collision and obstacle avoidance of multiple quadcopters. In this paper, the problem of distributed dynamic matrix control (DMC) for collision avoidance among a team of multiple quadcopters attempting to reach consensus in the horizontal plane and yaw direction (x,y$$ x,y $$, and ψ$$ \psi $$) is investigated. Violations of a predetermined safety radius generates output constraints on the DMC optimization function, which has not been dealt with in the literature. Different from past works, the proposed strategy can perform collision avoidance in the x$$ x $$, y$$ y $$, and z$$ z $$‐directions. In addition, logarithmic barrier functions are implemented as input rate constraints on the control actions. Extensive simulation studies for a team of quadcopters illustrate promising results of the proposed control strategy and case variations. In addition, DMC parameter effects on the system performance are studied, and a successful study for obstacle avoidance is presented. [ABSTRACT FROM AUTHOR]

This paper proposes a novel distributed formation controller for general linear multi-agent systems with application to multiple quadcopters. First, a new locally computable state-estimate-based event-triggering communication condition is proposed for each agent. Then, the formation tracking problem is formulated as a stability analysis, controller gain and event-generator gain design problem of the closed-loop formation error dynamics. Sufficient conditions that guarantee the co-existence of a valid formation controller and an event-triggered communication mechanism are derived using a Lyapunov-based method and linear matrix inequality techniques. In addition, equivalent low (agent-sized) dimensional sufficient conditions are obtained to reduce the computational complexity. For the simulation conditions used in this research, the proposed estimate-based event-triggered communication mechanism generates less data communication instants when compared with traditional state-error-based mechanisms while still achieving similar control performance. [ABSTRACT FROM AUTHOR]

In this article, we address the distributed event-triggered leader–follower formation tracking control problem of general linear multiagent systems with a dynamic leader in sampled-data settings. A novel locally computable state-estimate-based event generator is established for each follower agent to regulate the interagent communication at each sampling instant. Then, we propose a distributed formation tracking protocol based on the triggered sampled information such that the formation tracking control problem can be formulated as a stability-analysis problem of the closed-loop formation error dynamics. The event generator and formation tracking controller gains can then be co-designed using the feasible linear matrix inequality conditions that are derived from Lyapunov-based stability-analysis methods that guarantee the ultimate boundedness of the closed-loop formation error dynamics. Finally, numerical simulations along with experiment implementations were conducted for a group of linearized unicycle-type mobile robots to demonstrate the effectiveness and advantages of the proposed method. [ABSTRACT FROM AUTHOR]

A distributed control policy is designed for a group of Euler–Lagrange (EL) agents in a leader–follower-based communication network with time-varying delays. The nonsingular terminal sliding mode control (NTSMC) policy is integrated with mixed-type feedback and time-varying, adaptive control parameters. The control gain and proportions of feedback with and without estimated self-delays are tuned online with fuzzy logic control (FLC). The total and maximum tracking errors of a group of EL agents are assessed to demonstrate an improvement in synchronization performance with the proposed NTSMC+FLC approach compared to the NTSMC approach with constant parameters. Simulation and experimental results of a group of Phantom Omni manipulators are presented to validate the proposed control policy. [ABSTRACT FROM AUTHOR]

Background and Objectives: Grain quality is a complex trait in rice, compared with other staple crops as it is predominantly consumed as a whole grain. Although considered secondary to yield, to align with consumer preferences, breeders are increasingly interested in quality. At the early stages of a breeding program, grain quality‐related traits are often ignored as they are arduous and time‐consuming. Near‐infrared spectroscopy (NIRS) could be a suitable high‐throughput alternative to conventional wet chemistry and image processing‐related methods to be adopted for early screening. This study aims to quantify traits essential for rice breeders such as amylose, chalkiness, length, width, and the length/width ratio in rice samples with NIRS. We used conventional algorithms such as principal component analysis (PCA), partial least square regression (PLSR), multilayer perceptron (MLP), support vector classification (SVC), and linear discriminant analysis (LDA) to compare with the proposed convolutional neural network (CNN) for regression and classification. Findings: Our results showed that the proposed CNN outperformed the conventional models in estimating all traits. Unlike conventional models, CNN models could be developed with raw spectra with minimal to no preprocessing, and along with the transfer‐learning capabilities, the time required for model development could be significantly reduced. Conclusion: We recommend NIRS for quantitative estimation of amylose and chalkiness in rice and rather use classification/categorized estimation for other physical dimension‐related traits such as length and length/width ratio. Significance and Novelty: We found NIRS to be an appropriate alternative to wet chemistry and image‐based methods for screening lines at the early stages of the breeding program. Estimation of physical parameters such as length and length/width ratio with NIRS is novel and appears reasonable for high‐throughput applications. [ABSTRACT FROM AUTHOR]

This article studies the problem of dissipativity-based asynchronous state estimation for a class of discrete-time Markov jump neural networks subject to randomly occurring nonlinearities, sensor saturations, and stochastic parameter uncertainties. First, two stochastic nonlinearities occurring in the system are described by statistical means and obey two Bernoulli processes independently. Then, the hidden Markov model is used to characterize the real communication environment closely between the designed estimator and the system model due to the networked-induced phenomenons that also lead to randomly occurring parametric uncertainties of the estimator considered modeled by two Bernoulli processes. A new criterion is established to guarantee that the resulting error system is stochastically stable with predefined dissipativity performance. Finally, we provide a simulation example to validate the theoretical analysis. [ABSTRACT FROM AUTHOR]

In this paper, a new predictive approach is proposed for the impedance control of bilateral drive-by-wire teleoperation systems. The proposed control structure includes two mirror predictors/ observers in both the master and slave sides. These predictors/ observers are used to simultaneously estimate the master and slave internal dynamics, and thereby to avoid the use of the delayed transmitted information. As a consequence, the influence of the delay on the whole system can be minimized and the performance can be improved. Under a set of suited hypotheses, the proposed control structure is shown to be uniformly ultimate stable, even in the presence of time-varying delays. Simulation results are presented to show the effectiveness of the proposed approach. The behavior of the control structure is also experimentally demonstrated while performing remote steering of a small autonomous vehicle. Index Terms--Bilateral teleoperation systems, delayed systems, network-controlled systems, predictive approach, tlme-varying delays.

In this paper, a modular control approach is applied to a permanent-magnet synchronous motor (PMSM) speed control. Based on the functioning of the individual module, the modular approach enables the powerfully intelligent and robust control modules to easily replace any existing module which does not perform well, meanwhile retaining other existing modules which are still effective. Property analysis is first conducted for the existing function modules in a conventional PMSM control system: proportional--integral (PI) speed control module, reference current-generating module, and PI current control module. Next, it is shown that the conventional PMSM controller is not able to reject the torque pulsation which is the main hurdle when PMSM is used as a high-performance servo. By virtue of the internal model, to nullify the torque pulsation it is imperative to incorporate an internal model in the feed-through path. This is achieved by replacing the reference current-generating module with an iterative learning control (ILC) module. The ILC module records the cyclic torque and reference current signals over one entire cycle, and then uses those signals to update the reference current for the next cycle. As a consequence, the torque pulsation can be reduced significantly. In order to estimate the torque ripples which may exceed certain bandwidth of a torque transducer, a novel torque estimation module using a gain-shaped sliding-mode observer is further developed to facilitate the implementation of torque learning control. The proposed control system is evaluated through real-time implementation and experimental results validate the effectiveness. Index Terms--Iterative learning, modular approach, permanent-magnet synchronous motor (PMSM) speed control, pulsation torque minimization, sliding mode, torque observer.

It is well known by equivalent control theory, that in the sliding mode a low-pass filter, working as an average operator, can capture the desired control fairly well from the switching control signals. However, directly adding the filtered signals in parallel with the switching control does not warrant any improvement in the control system performance. In this work, we make clear the underlying reason why the sliding mode control (SMC) system does not function properly with such a simple closed-loop filtering structure. The correct way of incorporating the closed-loop filtering into SMC requires a second low-pass filter, which works concurrently with the first low pass filter to scale down the gain of the switching control. The SMC system with the new closed-loop filtering is able to realize the acquisition of equivalent control or estimate the disturbance, effectively reduce the switching gain to the minimum level, and as a result to eliminate chattering. Complementary to existing SMC, the proposed control system can easily incorporate feed-forward control into the closed-loop for bounded system perturbations. In addition, the frequency-domain knowledge can be easily used to construct the two filters. Index Terms--Closed-loop filtering, nonlinear systems, sliding mode control, Van der Pol circuits.

This article presents a novel model-based control design scheme for a commercially-available micro quadcopter. A simple yet effective attitude dynamics model was identified using the closed-loop instrumental variable method with an iterative minimization search algorithm, since the actual model of the onboard attitude controller was unknown. Model-based integral-linear quadratic regulator, backstepping, and nested saturation controllers were proposed and compared for hovering control of the micro quadcopter based on the identified attitude dynamics model and its theoretical translational model. The proposed hovering controllers were first evaluated in simulations and then validated experimentally. For the conditions used in this research, it was observed that the nested saturation controller generally had the best performance among the three proposed controllers when hovering in the presence of external wind disturbances, while the backstepping controller exhibited the worst performance. [ABSTRACT FROM AUTHOR]

Common assumptions in most of the previous nonlinear networked leader–follower systems are that the leader is provided as a constant signal and that the controllers are designed for either the joint-space regulation or the translational Cartesian-space motion control. This article addresses the control issue of the delay-induced horizontal shift effect when the leader is moving with a changing speed. A novel mixed-type feedback is introduced to reduce the horizontal shift effect so as to minimize tracking errors experienced by the follower agents. In this article, we also study the complete pose control using a nonsingular terminal sliding mode (NTSM) method. A stability analysis is provided to prove the finite-time boundedness of the tracking error signals. Quantitative evaluations of the multiple effects on the error bound are conducted to facilitate the subsequent control design to improve the performance. Numerical simulation results of a team of two degree-of-freedoms (DOFs) manipulators demonstrate the improved tracking performance of the end effectors with small bounded errors which are affected by network delays, maximum assigned accelerations, and the selection of control gains. The experimental results are provided to demonstrate the performance of the developed controller. [ABSTRACT FROM AUTHOR]

In this article, we focus on the experimental validation of the developed adaptive nonsingular terminal sliding mode (ANTSM) controller for a networked manipulator system. The proposed control approach is designed to deal with a combination of adverse and inexactly known conditions in practice, including parametric uncertainties, frictions, exogenous disturbances, and random time-varying network delays. Another issue addressed in this article is the tradeoff between achieving a smooth convergence and a high tracking accuracy in the physical implementation of the ANTSM controller. Hence, a novel time-varying gain in a form of logistic function is introduced to provide converging smoothness and meanwhile improve the tracking accuracy. Experimental results and empirical analysis are provided to demonstrate the effectiveness and performance improvement of the proposed controller with a time-varying gain. [ABSTRACT FROM AUTHOR]

Summary: This article presents a two‐layered framework to investigate the output synchronization problem in nonhomogeneous agent systems in the presence of periodic energy‐limited denial‐of‐service (DoS) attacks with an event‐triggered control strategy. Under the developed framework, the proposed controller for different agents is composed of a dynamic compensator and a regulator, where the dynamic compensator on the first layer can copy the dynamics of the leader node. DoS attacks with a periodic (partially known) attack strategy are based on a time sequence and interrupt the data exchange over a shard network consisting of the leader node and dynamic compensators in the first layer. An event‐triggered control protocol is proposed to reduce the update frequency of the controller, and it also ensures that the output of every dynamic compensator can track the output of the leader node without occurring "Zeno phenomenon." Based on the output regulator theory, the regulator for every agent can guarantee that all nonhomogeneous agents can converge to the trajectory of every dynamic compensator in the bottom layer. Finally, a simulation example is demonstrated to verify the new design method developed. [ABSTRACT FROM AUTHOR]

In this article, the dissipativity-based filtering of the Markovian jump neural networks subject to incomplete measurements and deception attacks is investigated by adopting an event-triggered communication strategy, where the attackers are supposed to occur in a random fashion but obey the Bernoulli distribution. Consider that the information of the system mode is transmitted to the filter over the communication network that is vulnerable to external attacks, which may lead to the undesired performance of the resulting system by injecting malicious information from the attackers. As a result, the filter has difficulty completing information from the original system. Besides, an event-triggered communication mechanism is introduced to reduce the communication frequency between data transmission due to the limited network resources, and different triggering conditions corresponding to different jump modes are developed. Then, based on the above considerations, the sufficient condition is derived to ensure the stochastic stability and dissipativity of the resulting augmented system although the deception attacks and incomplete information exist. A numerical simulated example is provided to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper studies the event-triggered containment control (CC) problem of multiagent systems with a directed graph, where the followers’ communication graph is an undirected graph. A novel event-triggered CC protocol is presented to schedule communications between agents, which depends on both local states and control inputs. Different from traditional approaches using broadcasts, a unique property of the proposed protocol is that it enables agent-to-agent data transmission. To do so, each communication link is associated with a specific local event. The estimated relative interagent states are transmitted over a specific link only when the related input-based event is detected. We develop sufficient conditions to solve CC problem under this protocol and extend it to the adaptive event-triggered protocol that does not require the global knowledge on the smallest positive eigenvalue of the Laplacian. For both protocols, we derive positive low bounds on the interevent time intervals generated by individual events, which eliminate the “Zeno phenomenon.” Feasibility of the proposed algorithm is verified by an example. [ABSTRACT FROM AUTHOR]

Summary: This article addresses a novel multilateral teleoperation control scheme for single‐master multiple slave systems, which can be extended to n masters and n slaves without the loss of generality, where the master is a m degrees of freedom (DOF) manipulator arm and the slaves are m DOF mobile manipulators. The human operator operates the master robot to remotely control the slaves handling a target object. The master position signal is transmitted to the slave side to generate a desired object trajectory as well as the reference mobile base velocity. An adaptive robust controller is designed for the slaves to follow the desired trajectory from the master, which not only provides the excellent trajectory tracking but also optimize the internal force distribution of the object. A null space controller is designed for the mobile platforms of the mobile manipulators to achieve the velocity consensus while achieving the main task of object transportation. The novel control design uses the transmission of the environmental force feedback over the communication channel by the estimated parameters of the environment, which helps retain the stability of the overall system. The environmental force is predicted on the master side based on the estimated environmental parameters. The proposed control design can simultaneously achieve the objectives of stability, synchronization, and optimal internal force distribution. The simulation results of a single‐master and three slaves teleoperation system validate the efficacy of the proposed control algorithm. [ABSTRACT FROM AUTHOR]

In this article, an adaptive nonsingular terminal sliding-mode (ANTSM) method is proposed for the motion tracking control of a bilateral teleoperation system. Efforts in this article seek to improve the position tracking performance of nonlinear systems subject to time-varying network delays, parametric uncertainties, and unknown external disturbances and frictions. Another issue addressed in this article is the common delay-induced phase shift of tracking profiles in many control methods, which is greatly reduced by introducing a novel mixed type of feedback signals in the ANTSM control design. Furthermore, the proposed adaptive control design with two online-estimated compensatory bounds removes the requirement of exact knowledge of network delays and disturbance bounds as a prior. In the master side, a force predictor is used to estimate the current environmental force for the reference signal generator. Therefore, the direct transmission of force signals is avoided. By comparing with the existing model-based and model-free methods, numerical simulation results with six-degree-of-freedom manipulators illustrate the merits of the developed robust and adaptive controllers. Experimental results with two Phantom Omni devices are also provided to demonstrate the effectiveness and the significant performance improvements of the proposed controllers. [ABSTRACT FROM AUTHOR]

This paper applies an input-based triggering approach to investigate the secure consensus problem in multiagent systems under denial-of-service (DoS) attacks. The DoS attacks are based on the time-sequence fashion and occur aperiodically in an unknown attack strategy, which can usually damage the control channels executed by an intelligent adversary. A novel event-triggered control scheme on the basis of the relative interagent state is developed under the DoS attacks, by designing a link-based estimator to estimate the relative interagent state between intermitted communication instead of the absolute state. Compared with most of the existing work on the design of the triggering condition related to the state measurement error, the proposed triggering condition is designed based on the control input signal from the view of privacy protection, which can avoid continuous sampling for every agent. Besides, the attack frequency and attack duration of DoS attacks are analyzed and the secure consensus is reachable provided that the attack frequency and attack duration satisfy some certain conditions under the proposed control algorithm. “Zeno phenomenon” does not exhibit by proving that there exist different positive lower bounds corresponding to different link-based triggering conditions. Finally, the effectiveness of the proposed algorithm is verified by a numerical example. [ABSTRACT FROM AUTHOR]

This paper considers the consensus problem of multiagent systems with the input-based triggering condition. A model-based approach is first given to estimate the relative interagent states between intermittent communications instead of absolute states. A novel consensus protocol consisting of the relative interagent states is proposed for the consensus problem. Besides, compared with some results on the triggering condition consisting of state measurement error, a new triggering condition is constructed based on the control input. Then, the consensus protocol is executed by every agent in a fully distributed way, which has the advantage that the controller design is related to the number of agents instead of using global information. Moreover, the bounds of parameters of the controller and the triggering condition can be obtained by the proposed algorithm simultaneously, which depends on the total number of agents in multiagent networks. The proposed control scheme can ensure that states of all agents can achieve consensus. It is shown that “Zeno behavior” does not appear under the proposed algorithm. Finally, an illustrative example is given to verify the proposed method. [ABSTRACT FROM AUTHOR]

This paper addresses the dissipative asynchronous filtering problem for a class of Takagi–Sugeno fuzzy Markov jump systems in the continuous-time domain. The hidden Markov model is applied to describe the asynchronous situation between the designed filter and the original system. Based on the stochastic Lyapunov function, a sufficient condition is developed to guarantee the stochastic stability of the filtering error systems with a given dissipative performance. Two different methods for the existence of desired filter are established. Due to the Finsler’s lemma, the second approach has fewer variables to decide and brings less conservatism than the first one. Finally, an example is provided to demonstrate the correctness and advantage of the proposed approaches. [ABSTRACT FROM AUTHOR]

In this paper, the problem of distributed event-triggered pinning control for practical consensus of multiagent systems (MASs) with quantized communication based on a directed graph is investigated. The pinning control for practical consensus of MASs with uniform quantizer is first discussed. Then, in order to decrease communication load of interagent, the event-triggered quantized communication protocol is designed. The nonsmooth analysis and Gronwall’s inequality approach is used to guarantee the existence of a solution to the resulting closed-loop system. It is shown that practical consensus is reachable through the event-triggered control and converges to a consensus set. Moreover, “Zeno phenomenon” can be excluded. Finally, an example is given to validate the feasibility and efficiency of the proposed new design method. [ABSTRACT FROM AUTHOR]

The realism or transparency of haptic interfaces is becoming more critical as they are applied to training in fields like minimally invasive surgery (MIS). Surgical training simulators must provide a transparent virtual environment (VE) at a high update rate. Complex, deformable, cuttable tissue models have nonlinear dynamics and are computationally expensive, making it difficult to provide sufficient update rates. The objective of this work is to improve the transparency for this type of VE by formulating the unknown nonlinear dynamics as a quasi-linear parameter varying (LPV) system and designing a predictor to provide an output at a much higher update rate. An adaptive controller based on gain-scheduled prediction is considered for a nonlinear haptic device and a nonlinear, delayed, and sampled VE. The predictor uses feedback from the more accurate but slow-updating VE to update a simplified dynamic model. The predictor is designed based on numerical solutions to a linear matrix inequality derived using Lyapunov-based methods. Experimental results demonstrate the effectiveness of the gain-scheduled predictor approach and compare it to previous work using a constant-gain predictor. The gain-scheduled predictor results in significant performance improvements compared to a haptic system without prediction, but less significant improvement compared to the constant-gain approach. [ABSTRACT FROM AUTHOR]

With the increasing industrial requirements such as bigger size object, stable operation, and complex task, multilateral teleoperation systems extended from traditional bilateral teleoperation are widely developed. In this paper, the integrated control design is developed for multilateral teleoperation systems, where n master manipulators are operated by human to remotely control n slave manipulators cooperatively handling a target object. For the first time, the control objectives of multilateral teleoperation including stability, synchronization, transparency, and internal force distribution are clarified systematically. A novel communication architecture is proposed to cope with communication delays, where the estimated environmental parameters are transmitted from the slave side to the master, to replace the traditional environmental force measurement in the communication channel. A kind of nonlinear adaptive robust control technique is used to deal with nonlinearities, unknown parameters, and modeling uncertainties existing in the master, slave, and environmental dynamics, so that the excellent tracking performance is achieved in both master and slave sides. The coordinated motion/force control is designed in the slave side by the optimal internal force distribution among n slave manipulators, and the impedance control is designed in the master side to realize the target transparency behavior. In summary, the proposed control algorithm can achieve the guaranteed robust stability, the excellent synchronization and transparency performance, and the optimal internal force distribution simultaneously for multilateral teleoperation systems under arbitrary time delays and various modeling uncertainties. The simulation is carried out on a 2-master/2-slave teleoperation system, and the results show the effectiveness of the proposed control design. [ABSTRACT FROM AUTHOR]

Bilateral teleoperation technology has caused wide attentions due to its applications in various remote operation systems. The communication delay becomes one of the main challenging issues in the teleoperation control design. Meanwhile, various nonlinearities, parameter variations, and modeling uncertainties existing in manipulator and environment dynamics need to be considered carefully in order to achieve good control performance. In this paper, a globally stable nonlinear adaptive robust control algorithm is developed for bilateral teleoperation systems to deal with these control issues. Namely, the unknown dynamical parameters of the environmental force are estimated online by the improved least square adaptation law. A novel communication structure is proposed where only the master position signal is transmitted to the slave side for the tracking design, and the online estimators of the environmental parameters are transmitted from the slave to the master to replace the traditional environmental force measurement. Because the estimated environmental parameters are not power signals, the passivity problem of the communication channel and the trade-off limitation between the transparency performance and robust stability in traditional teleoperation control are essentially avoided. The nonlinear adaptive robust control is subsequently developed to deal with nonlinearities, unknown parameters, and modeling uncertainties of the master, slave, and environmental dynamics, so that the guaranteed transient and steady-state transparency performance can be achieved. The experiments on two voice-coil motor-driven manipulators are carried out, and the comparative results verify that the proposed control algorithm achieves the excellent control performance and the guaranteed robust stability simultaneously under time delays. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Bilateral teleoperation technology has caused wide attentions because of its applications in various remote operation systems. However, there exist some challenging control issues such as communication delay, unmeasurable environmental force, and various manipulator modelling uncertainties. In this study, the disturbance observer is designed based on the slave manipulator dynamics to observe the unmeasurable environmental force. When the environmental force is modelled as a general linear regression form, its unknown parameters can be estimated online by the least square adaptation law. A novel communication structure is proposed where only the master trajectory is transmitted to the slave side, and the transmission signal from the slave to the master is replaced by those estimated environmental parameters. Since these parameters are not power signals, the passivity problem of the communication channel and the trade‐off limitation between the transparency performance and robust stability in traditional teleoperation control are essentially avoided. The sliding mode control and the force compensation of disturbance observer are integrated subsequently to deal with various manipulator modelling uncertainties, so that the excellent synchronisation performance can be realised. Thus, the proposed control algorithm can guarantee the robust stability and the good control performance simultaneously under arbitrary time delays. The simulation and experiment on two single degree‐of‐freedom manipulators are carried out and the results show the effectiveness of the proposed control algorithm. [ABSTRACT FROM AUTHOR]