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Service providers often recommend unnecessary and expensive services to unsuspecting consumers, such as recommending a new part when a simple fix to the old will do, a phenomenon known as overprovisioning. The purpose of this paper is to examine to what extent consumers tend to defer their decisions should they suspect that sellers are overproviding services to them and they cannot prevent the sellers from doing so (they lack personal control); and how proper market signals can mitigate such suspicions, restore personal control and reduce deferrals.

The paper conducts three laboratory experiments. The experiments expose the participants to hypothetical repair scenarios and measure to what extent they suspect that sellers might be overproviding services to them and they feel that they lack the personal control to prevent the sellers from doing so. Thereafter, the experiments expose them to two different market signals, one conveying that the seller is providing quality services (a repair warranty; quality signal) and the other conveying that the seller is taking away any incentives their agents (technicians) may have to overprovide services (the technicians are paid a flat salary; quantity signal). The paper examines how these quality/quantity signals are able to reduce overprovisioning suspicions, restore personal control and reduce decision deferrals.

The paper has two main findings. First, the paper shows a mediation process at work i.e. suspecting potential overprovisioning by sellers leads consumers to defer their decisions indirectly because they feel that they lack personal control to prevent the sellers from doing so. Second, the paper shows that the quantity signal (flat salary disclosure), but not the quality signal (warranty), is able to mitigate suspicions of overprovisioning, restore personal control and reduce decision deferrals.

The paper suggests that although buyers may rely on quality signals to assure them of superior service, these signals do not guarantee that the quantity of service they are receiving is appropriate. Therefore, sellers will have to send a credible quality signal and a credible quantity signal to the consumers if they wish to tackle suspicions about service overprovision and service quality.

The paper is original in two ways. First, the paper theorizes and tests a mediation process model whereby quality/quantity signals differentially mitigate overprovisioning suspicions, restore personal control and reduce decision deferrals. Second, the paper speaks to the necessity of expanding the traditional signaling literature, designed primarily to detect poor quality hidden in the products/services of lower-quality sellers, to include detecting/solving overprovisioning often hidden in the services provided by higher-quality sellers.

The purpose of this review paper is to address the substantial challenges of the outdated exoskeletons used for rehabilitation and further study the current advancements in this field. The shortcomings and technological developments in sensing the input signals to enable the desired motions, actuation, control and training methods are explained for further improvements in exoskeleton research.

Search platforms such as Web of Science, IEEE, Scopus and PubMed were used to collect the literature. The total number of recent articles referred to in this review paper with relevant keywords is filtered to 143.

Exoskeletons are getting smarter often with the integration of various modern tools to enhance the effectiveness of rehabilitation. The recent applications of bio signal sensing for rehabilitation to perform user-desired actions promote the development of independent exoskeleton systems. The modern concepts of artificial intelligence and machine learning enable the implementation of brain–computer interfacing (BCI) and hybrid BCIs in exoskeletons. Likewise, novel actuation techniques are necessary to overcome the significant challenges seen in conventional exoskeletons, such as the high-power requirements, poor back drivability, bulkiness and low energy efficiency. Implementation of suitable controller algorithms facilitates the instantaneous correction of actuation signals for all joints to obtain the desired motion. Furthermore, applying the traditional rehabilitation training methods is monotonous and exhausting for the user and the trainer. The incorporation of games, virtual reality (VR) and augmented reality (AR) technologies in exoskeletons has made rehabilitation training far more effective in recent times. The combination of electroencephalogram and electromyography-based hybrid BCI is desirable for signal sensing and controlling the exoskeletons based on user intentions. The challenges faced with actuation can be resolved by developing advanced power sources with minimal size and weight, easy portability, lower cost and good energy storage capacity. Implementation of novel smart materials enables a colossal scope for actuation in future exoskeleton developments. Improved versions of sliding mode control reported in the literature are suitable for robust control of nonlinear exoskeleton models. Optimizing the controller parameters with the help of evolutionary algorithms is also an effective method for exoskeleton control. The experiments using VR/AR and games for rehabilitation training yielded promising results as the performance of patients improved substantially.

Robotic exoskeleton-based rehabilitation will help to reduce the fatigue of physiotherapists. Repeated and intention-based exercise will improve the recovery of the affected part at a faster pace. Improved rehabilitation training methods like VR/AR-based technologies help in motivating the subject.

The paper describes the recent methods for signal sensing, actuation, control and rehabilitation training approaches used in developing exoskeletons. All these areas are key elements in an exoskeleton where the review papers are published very limitedly. Therefore, this paper will stand as a guide for the researchers working in this domain.

The purpose of this paper is to design and construct an amplitude shift keying (ASK) modulator, which, using the digital binary modulating signal, controls a floating memristor emulator (MR) internally without the need for additional control circuits to achieve the ASK modulated wave.

A binary digital unipolar signal to be modulated is converted by a pre-processor circuit into a suitable bipolar modulating direct current (DC) signal for the control of the MR state, using current conveyors the carrier signal’s amplitude is varied with the change in the memristance of the floating MR. A high pass filter is then used to remove the DC control signal (modulating signal) leaving only the modulated carrier signal.

The results from the experiment and simulation are in agreement showed that the MR can be switched between two states and that a change in the carrier signals amplitude can be achieved by using an MR. Thus, showing that the circuit behavior is in line with the proposed theory and validating the said theory.

In this paper, the binary signal to be modulated is modified into a suitable control signal for the MR, thus the MR relies on the internal operation of the modulator circuit for the control of its memristance. An ASK modulation can then be achieved using a floating memristor without the need for additional circuits or signals to control its memristance.

The purpose of this paper is to develop a dynamic control method to improve bus schedule adherence under connected bus system.

The authors developed a dynamic programming model that optimally schedules the bus operating speed at road sections and multiple signal timing plans at intersections to improve bus schedule adherence. First, the bus route was partitioned into three types of sections: stop, road and intersection. Then, transit agencies can control buses in real time based on all collected information; i.e. control bus operating speed on road sections and adjust the signal timing plans through signal controllers to improve the schedule adherence in connected bus environment. Finally, bus punctuality at the downstream stop and the saturation degree deviations of intersections were selected as the evaluation criteria in optimizing signal control plans and bus speeds jointly.

An illustrative case study by using a bus rapid transit line in Jinan city was performed to verify the proposed model. It revealed that based on the proposed strategy, the objective value could be reduced by 73.7%, which indicated that the punctuality was highly improved but not to incur excessive congestion for other vehicular traffic.

In this paper, the authors applied speed guidance and the adjustment of the signal control plans for multiple cycles in advance to improve the scheduled stability; furthermore, the proposed control strategy can reduce the effect on private traffics to the utmost extend.

Traffic signal control is one of the oldest application areas of fuzzy sets in transportation. In general, fuzzy control is found to be superior in complex problems with multi-objective decisions. In traffic signal control, several traffic flows compete for the same time and space, and different priorities are often set to different traffic flows or vehicle groups

The public transport priorities are a very important part of the effective traffic signal control. Normally, the public transport priorities are programmed by using special algorithms, which are tailor-made for each intersection. The experiences have proved that this kind of algorithms can be very effective if some compensation algorithms and the traffic-actuated control mode are used. We believe that using the fuzzified public transport priority algorithms, the measures of effectiveness of traffic signal control can be even better. In this paper, our fuzzy control algorithm of the public transport priorities will be presented.

This chapter provides basic knowledge on the principles used in modern signalling systems to ensure safe train separation and to establish safe routes through point zones. For train control, lineside signals are compared with cab signalling. For block protection, fixed block and moving block systems are covered. The described interlocking principles for routes leading through point zones include route locking and release, conflicting routes, flank protection, and overlaps. A section on automatic train protection explains the principles of how trains can be prevented from violating speed and authority limits. For this, an overview on the levels of the European Train Control System is provided. Some information is also given on train describers and automatic route setting systems to support traffic management in signalling centres.

Intelligent control for unidentified systems with unstable equilibriums is not always a proper control strategy, which results in inferior performance in many cases. Because of the existing trial and error manner of the procedure in former duration of learning, this exploration for finding the appropriate control signals can lead to instability. However, the recent proposed emotional controllers are capable of learning swiftly; the use of these controllers is not an efficient solution for the mentioned instability problems. Therefore, a solution is needed to evade the instability in preliminary phase of learning. The purpose of this paper is to propose a novel approach for controlling unstable systems or systems with unstable equilibrium by model free controllers.

An existing controller (model‐based controller) with limited performance is used as a mentor for the emotional learning controller in the first step. This learning phase prepares the controller to control the plant as well as mentor, while it prevents any instability. When the emotional controller can imitate the behavior of model based one properly, the employed controller is gently switched from model based one to an emotional controller using a fuzzy inference system (FIS). Also, the emotional stress is softly switched from the mentor‐imitator output difference to the combination of the objectives. In this paper, the emotional stresses are generated once by using a nonlinear combination of objectives and once by employing different stresses to a FIS which attentionally modulated the stresses, and makes a subset of these objectives salient regarding the contemporary situation.

The proposed model free controller is employed to control an inverted pendulum system and an oscillator with unstable equilibrium. It is noticeable that the proposed controller is a model free one, and does not use any knowledge about the plant. The experimental results on two benchmarks show the superiority of proposed imitative and emotional controller with fuzzy stress generation mechanism in comparison with model based originally supplied controllers and emotional controller with nonlinear stress generation unit – in control of pendulum system – in all operating conditions.

There are two test beds for evaluating the proposed model free controller performance which are discussed in this paper: a laboratorial inverted pendulum system, which is a well‐known system with unstable equilibrium, and Chua's circuit, which is an oscillator with two stable and one unstable equilibrium point. The results show that the proposed controller with the mentioned strategy can control the systems with satisfactory performance.

In this paper, a novel approach for controlling unstable systems or systems with unstable equilibrium by model free controllers is proposed. This approach is based on imitative learning in preliminary phase of learning and soft switching to an interactive emotional learning. Moreover, FISs are used to model the linguistic knowledge of the ascendancy and situated importance of the objectives. These FISs are used to attentionally modulate the stress signals for the emotional controller. The results of proposed strategy on two benchmarks reveal the efficacy of this strategy of model free control.

The model for digitally controlled three-phase pulse width modulation (PWM) boost rectifiers is a sampled data model, which is different from the continuous time domain models presented in previous studies. The controller, which is tuned according to the model in continuous time domain and discretized by approximation methods, may exhibit some unpredictable performances and even result in unstable systems under some extreme situations. Consequently, a small-signal discrete-time model of digitally controlled three-phase PWM boost rectifier is required. The purpose of this paper is to provide a simple but accurate small-signal discrete-time model of digital controlled three-phase PWM boost rectifier, which explains the effect of the sampling period, modulator and time delays on system dynamic and improves the control performance.

Based on the Laplace domain analysis and the waveforms of up-down-count modulator, the small signal model of digital pulse width modulation (DPWM) in the Laplace domain is presented. With a combination of state-space average and a discrete-time modeling technique, a simplified large signal discrete time model is developed. With rotation transformation and feed-forward decoupling, the large-signal model is decoupled into a single input single output system with rotation transformation. Then, an integrated small signal model in the Laplace domain is constructed that included the time delay and modulation effect. Implementing the modified z-transform, a small-signal discrete-time model is derived from the integrated small signal model.

In a digital control system, besides the circuit parameters, the location of pole of open-loop transfer function is also related to system sampling time, affecting the system stability, and the time delay determines the location of the zero of open-loop transfer function, affecting the system dynamic. In addition to the circuit parameters discussed in previous literature, the right half plane (RHP) zero is also determined by the sampling period and the time delay. Furthermore, the corner frequency of the RHP zero is mainly determined by the sampling period.

The model developed in this paper, accounting for the effect of the sampling period, modulator and time delays on the system dynamic, give a sufficient insight into the behavior of the digitally controlled three-phase PWM rectifier. It can also explain the effect of sampling period and control delay time on system dynamic, accurately predict the system stability boundary and determine the oscillation frequency of the current loop in critical stable. The experimental results verify that the model is a simple and accurate control-oriented small-signal discrete-time model for the digitally controlled three-phase PWM boost rectifier.