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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.

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]

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]

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 P1 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 teaming control (ILC) module. The LLC 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. [ABSTRACT FROM AUTHOR]

This article considers the output tracking control problem of nonidentical linear multiagent systems (MASs) using a model-free reinforcement learning (RL) algorithm, where partial followers have no prior knowledge of the leader's information. To lower the communication and computing burden among agents, an event-driven adaptive distributed observer is proposed to predict the leader's system matrix and state, which consists of the estimated value of relative states governed by an edge-based predictor. Meanwhile, the integral input-based triggering condition is exploited to decide whether to transmit its private control input to its neighbors. Then, an RL-based state feedback controller for each agent is developed to solve the output tracking control problem, which is further converted into the optimal control problem by introducing a discounted performance function. Inhomogeneous algebraic Riccati equations (AREs) are derived to obtain the optimal solution of AREs. An off-policy RL algorithm is used to learn the solution of inhomogeneous AREs online without requiring any knowledge of the system dynamics. Rigorous analysis shows that under the proposed event-driven adaptive observer mechanism and RL algorithm, all followers are able to synchronize the leader's output asymptotically. Finally, a numerical simulation is demonstrated to verify the proposed approach in theory.