Remote Tactile Transmission with Time Delay for Robotic Master–Slave Systems

This study develops a method to compensate for the communication time delay for tactile transmission systems. For transmitting tactile information from remote sites, the communication time delay degrades the validity of feedback. However, so far time delay compensation methods for tactile transmissions have yet to be proposed. For visual or force feedback systems, local models of remote environments were adopted for compensating the communication delay. The local models cancel the perceived time delay in sensory feedback signals by synchronizing them with the users' operating movements. The objectives of this study are to extend the idea of the local model to tactile feedback systems and develop a system that delivers tactile roughness of textures from remote environments to the users of the system. The local model for tactile roughness is designed to reproduce the characteristic cutaneous deformations, including vibratory frequencies and amplitudes, similar to those that occur when a human finger scans rough textures. Physical properties in the local model are updated in real-time by a tactile sensor installed on the slave-side robot. Experiments to deliver the perceived roughness of textures were performed using the developed system. The results showed that the developed system can deliver the perceived roughness of textures. When the communication time delay was simulated, it was confirmed that the developed system eliminated the time delay perceived by the operators. This study concludes that the developed local model is effective for remote tactile transmissions.     

Stable Fault-tolerance Control for a Class of Networked Control Systems

In this paper, we use the matrix measure technique to study stable fault-tolerance control of networked control systems. State feedback networked control systems with the network-induced delay, parameter uncertainties, sensor failures and actuator failures are considered. State feedback gain K is designed for any invariant delay T, and some theorems and sufficient conditions for stable fault-tolerance control are given. Example is presented to illustrate the effectiveness of these theorems.     

Call for Papers New Trends in Theory and Applications of Complex Control Systems Special Issue in Journal of Control Theory and Applications

In recent years modeling and control of complex systems, in particular complex nonlinear systems, have been one of the most active fields in the community of system and control, Various methods such as adaptive control, switching control, distributed and network-based control design methods have been proposed to cope with the complexity of systems under appropriate mathematical assumptions. However, considerable efforts are still needed in order to bridge the gap between the theory and application. In particular, there have not been many key industrial applications reported so far. One of the main reasons for this gap is that many complexities and nonlinearities encountered in practice do not satisfy the mathematical assumptions of the available results.     

Call for Papers New Trends in Theory and Applications of Complex Control Systems Special Issue in Journal of Control Theory and Applications

In recent years, modeling and control of complex systems, in particular complex nonlinear systems, have been one of the most active fields in the community of system and control. Various methods such as adaptive control, switching control, distributed and network-based control design methods have been proposed to cope with the complexity of systems under appropriate mathematical assumptions. However, considerable efforts are still needed in order to bridge the gap     

Study on the Application of Iterative Learning Control to Terminal Control of Linear Time-varying Systems

An iterative learning control algorithm based on shifted Legendre orthogonal polynomials is proposed to address the terminal control problem of linear time-varying systems. First, the method parameterizes a linear time-varying system by using shifted Legendre polynomials approximation. Then, an approximated model for the linear time-varying system is deduced by employing the orthogonality relations and boundary values of shifted Legendre polynomials. Based on the model, the shifted Legendre polynomials coefficients of control function are iteratively adjusted by an optimal iterative learning law derived. The algorithm presented can avoid solving the state transfer matrix of linear time-varying systems. Simulation results illustrate the effectiveness of the proposed method.     

Robust Control of Uncertain Markov Jump Singularly Perturbed Systems

In this paper,we study the robust control for uncertain Markov jump linear singularly perturbed systems(MJLSPS),whose transition probability matrix is unknown.An improved heuris- tic algorithm is proposed to solve the nonlinear matrix inequalities.The results of this paper can apply not only to standard,but also to nonstandard MJLSPS.Moreover,the proposed approach is independent of the perturbation parameter and therefore avoids the ill-conditioned numerical prob- lems.     

Formal Reduction of Interfaces to Large-scale Process Control Systems

A formal methodology is proposed to reduce the amount of information displayed to remote human operators at interfaces to large-scale process control plants of a certain type.The reduction proceeds in two stages.In the first stage,minimal reduced subsets of components,which give full information about the state of the whole system,are generated by determining functional dependencies between components.This is achieved by using a temporal logic proof obligation to check whether the state of all components can be inferred from the state of components in a subset in specified situations that the human operator needs to detect,with respect to a finite state machine model of the system and other human operator behavior.Generation of reduced subsets is automated with the help of a temporal logic model checker.The second stage determines the interconnections between components to be displayed in the reduced system so that the natural overall graphical structure of the system is maintained.A formal definition of an aesthetic for the required subgraph of a graph representation of the full system,containing the reduced subset of components,is given for this purpose. The methodology is demonstrated by a case study.     

Model Predictive Control of Nonlinear Systems： Stability Region and Feasible Initial Control

This paper proposes a new method for model predictive control (MPC) of nonlinear systems to calculate stability region and feasible initial control profile/sequence, which are important to the implementations of MPC. Different from many existing methods, this paper distinguishes stability region from conservative terminal region. With global linearization, linear differential inclusion (LDI) and linear matrix inequality (LMI) techniques, a nonlinear system is transformed into a convex set of linear systems, and then the vertices of the set are used off-line to design the controller, to estimate stability region, and also to determine a feasible initial control profile/sequence. The advantages of the proposed method are demonstrated by simulation study.     

Predictive Compensation for Stochastic Time Delay in Network Control Systems

This paper proposes a predictive compensation strategy to reduce the detrimental effect of stochastic time delays induced by communication networks on control performance. Values of a manipulated variable at the present sampling instant and future time instants can be determined by performing a receding horizon optimal procedure only once. When the present value of the manipulated variable does not arrive at a smart actuator, its predictive one is imposed to the corresponding process Switching of a manipulated variable between its true present value and the predictive one usually results in unsmooth operation of a control system. This paper shows: 1) for a steady process, as long as its input is sufficiently smooth, the smoothness of its output can be guaranteed; 2) a manipulated variable can be switched smoothly by filtering the manipulated variable just using a simple low-pass filter. Thus the control performance can be improved. Finally, the effectiveness of the proposed method is demonstrated by simulation study.     

Control of Non-Deterministic Systems With μ-Calculus Specifications Using Quotienting

The supervisory control problem for discrete event system(DES) under control involves identifying the supervisor, if one exists, which, when synchronously composed with the DES,results in a system that conforms to the control specification. In this context, we consider a non-deterministic DES under complete observation and control specification expressed in action-based propositional μ-calculus. The key to our solution is the process of quotienting the control specification against the plan resulting in a new μ-calculus formula such that a model for the formula is the supervisor. Thus the task of control synthesis is reduced a problem of μ-calculus satisfiability. In contrast to the existing μ-calculus quotienting-based techniques that are developed in deterministic setting, our quotienting rules can handle nondeterminism in the plant models. Another distinguishing feature of our technique is that while existing techniques use a separate μ-calculus formula to describe the controllability constraint(that uncontrollable events of plants are never disabled by a supervisor), we absorb this constraint as part of quotienting which allows us to directly capture more general state-dependent controllability constraints. Finally, we develop a tableau-based technique for verifying satisfiability of quotiented formula and model generation. The runtime for the technique is exponential in terms of the size of the plan and the control specification. A better complexity result that is polynomial to plant size and exponential to specification size is obtained when the controllability property is state-independent. A prototype implementation in a tabled logic programming language as well as some experimental results are presented.     

H∞ Synchronization of Chaotic Systems via Delayed Feedback Control

The H∞ synchronization problem for a class of delayed chaotic systems with external disturbance is investigated. A novel delayed feedback controller is established under which the chaotic master and slave systems are synchronized with a guaranteed H∞ performance. Based on the Lyapunov stability theory, a delay-dependent condition is derived and formulated in the form of linear matrix inequality (LMI). A numerical simulation is also presented to validate the effectiveness of the developed theoretical results.     

H_∞ Synchronization of Chaotic Systems via Delayed Feedback Control

The H∞ synchronization problem for a class of delayed chaotic systems with external disturbance is investigated. A novel delayed feedback controller is established under which the chaotic master and slave systems are synchronized with a guaranteed H∞ performance. Based on the Lyapunov stability theory, a delay-dependent condition is derived and formulated in the form of linear matrix inequality (LMI). A numerical simulation is also presented to validate the effectiveness of the developed theoretical results...     

Special Issue on ＂＂Recent Advances in Power System Control＂＂ International Journal of Control, Automation, and Systems

Today the high quality power supply is of essential in the economic development in a country. With the development of modem power systems and increasing demand for power supply, the electric power industry is ricing a great challenge in meeting the increased load demand with highest reliability and security with minimum trammission expenditure.     

Control of DC–DC power converters in the presence of coil magnetic saturation

Engineers generally design control for power converters based on standard models that assume the involved passive components to be linear. In reality, the magnetic characteristics of these components are nonlinear (especially in the presence of large magnetic flux density in the ferromagnetic core). This nonlinearity, which is of the saturation type, is particularly pronounced in higher power coils. Therefore, a controller obtained from the standard models may not achieve the performance it is designed for under operational conditions where the nonlinearity of the components is not negligible. In this paper, the authors investigate the effect of coil magnetic saturation for certain converters is investigated. It is shown that the control performances actually deteriorate if such a feature is not accounted for in the converter modeling. A solution that explicitly accounts for the nonlinearity of coil characteristics is developed for two converters.     

Special Issue on “Recent Advances in Power System Control” for International Journal of Control, Automation, and Systems

Today the high quality power supply is of essential in the economic development in a country. With the development of modem power systems and increasing demand for power supply, the electric power industry is facing a great challenge in meeting the increased load demand with highest reliability and security with minimum transmission expenditure.     

Robust Stabilization of Uncertain Networked Control Systems with Data Packet Dropouts

The data packet dropouts phenomenon is usually inevitable when information transmit- ted among communication networks.In this paper,the robust stabilization problem for uncertain networked control systems with data packet dropouts is studied.First,an uncertain discrete-time switching system model is presented to describe these networked control systems.The stability equiv- alence is then proved between this switching system and an uncertain impulsive difference system. Moreover,a sufficient condition is obtained for the asymptotical stability of the nonlinear impulsive difference system.From this condition the robust stabilization problem is dealt with for the uncertain impulsive system.Main results are given in linear matrix inequalities.Finally a numerical example is given to illustrate the theoretical results.     

Stability in Probability and Inverse Optimal Control of Evolution Systems Driven by Lévy Processes

This paper first develops a Lyapunov-type theorem to study global well-posedness(existence and uniqueness of the strong variational solution)and asymptotic stability in probability of nonlinear stochastic evolution systems(SESs)driven by a special class of Levy processes,which consist of Wiener and compensated Poisson processes.This theorem is then utilized to develop an approach to solve an inverse optimal stabilization problem for SESs driven by Levy processes.The inverse optimal control design achieves global well-posedness and global asymptotic stability of the closed-loop system,and minimizes a meaningful cost functional that penalizes both states and control.The approach does not require to solve a Hamilton-Jacobi-Bellman equation(HJBE).An optimal stabilization of the evolution of the frequency of a certain genetic character from the population is included to illustrate the theoretical developments.     

Optimization of Relay Control Systems with Plants Containing Multi-valued Non-linearities†

For the synthesis of optimal systems with multi-valued non-linearities in the plant modified phase space techniques can be applied. In this paper the modifications are discussed in detail and a rule is given for determining the number of phase coordinates. It is shown that the appropriate final state manifold is a line which passes through the origin, for typical cases of plants with backlash or hysteresis. For a wido class of such systems, with relay control, it is proved that if a zero switch path between two states exists, it is the time optimal path between those states. Finally the time optimal controllers for two simple plants containing multi-valued non-linearities are found.     

Workload Management in Teleoperation of Unmanned Ground Vehicles: Effects of a Delay Compensation Aid on Human Operators’ Workload and Teleoperation Performance

ABSTRACT

Workload management is of critical concern in the teleoperation of unmanned vehicles because teleoperation is often employed in high-risk industries wherein high workload can lead to sub-optimal task performance and can harm human operators’ long-term well-being. This study aimed to assess the detrimental effects of time delays in teleoperation on operators’ workload and performance, and how a delay compensation aid mitigated such effects. We conducted a human-in-the-loop experiment with 36 participants using a dual-task teleoperation platform, where participants drove a simulated High Mobility Multipurpose Wheeled Vehicle (HMMWV) and performed a one-back memory task under three conditions: the delay condition, the delay with compensation aid condition, and the ideal no delay condition. A model-free predictor was used as the compensation aid. Results indicate that with a time delay of 0.8-s participants’ workload increased and performance degraded significantly. Moreover, the model-free predictor mitigated the detrimental effects of time delay on workload and task performance. Our findings suggest that participants are more sensitive in their perceived workload compared to the objective and physiological measures of workload. In addition, without any delay compensation algorithms, continuous teleoperation may not be ideal for operations with long time delays.