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W. Ross Ashby’s elementary non-trivial machine, known in the cybernetic literature as the “Ashby Box,” has been described as the prototypical example of a black box system. As far as it can be ascertained from Ashby’s journal, the intended purpose of this device may have been to exemplify the environment where an “artificial brain” may operate. This paper describes the construction of an elementary observer/controller for the class of systems exemplified by the Ashby Box – variable structure black box systems with parallel input.

Starting from a formalization of the second-order assumptions implicit in the design of the Ashby Box, the observer/controller system is synthesized from the ground up, in a strictly system-theoretic setting, without recourse to disciplinary metaphors or current theories of learning and cognition, based mainly on guidance from Heinz von Foerster’s theory of self-organizing systems and W. Ross Ashby’s own insights into adaptive systems.

Achieving and maintaining control of the Ashby Box requires a non-trivial observer system able to use the results of its interactions with the non-trivial machine to autonomously construct, deconstruct and reconstruct its own function. The algorithm and the dynamical model of the Ashby Box observer developed in this paper define the basic specifications of a general purpose, unsupervised learning architecture able to accomplish this task.

The problem exemplified by the Ashby Box is fundamental and goes to the roots of cybernetic theory; second-order cybernetics offers an adequate foundation for the mathematical modeling of this problem.

Increasing commercial applications for small unmanned aircraft create growing challenges in providing safe flight conditions. The conventional measures to detect icing are either expensive, energy consuming or heavy. The purpose of this paper is to develop a fault identification and isolation scheme using unknown input observers to detect and isolate actuator and structural faults in simultaneous occurrence.

The fault detection scheme is based on a deviation in system parameters due to icing and lock-in-place (LIP), two faults from different categories with similar indications that require different reconfiguration actions. The obtained residual signals are selected to be triggered by desired faults, while insensitive to others.

The proposed observer is sensitive to both actuator and structural faults, and distinguishes simultaneous occurrences by insensitivity to LIP in selected residue signals. Simulation results confirm the success of the proposed system in the presence of uncertainty and disturbance.

The fault detection and isolation scheme proposed here is based on the linear model of a winged aircraft, the Aerosonde. Moreover, the faults are applied to rudder and aileron in simulations, but the design procedure for other models is provided. The designed scheme could be further implemented on a non-linear aircraft model.

Applying the proposed icing detection scheme increases detection system reliability, since fault isolation enables timely reconfiguration schemes.

The observers proposed in previous papers detected icing fault but were not insensitive to actuator faults.

The purpose of this paper is to investigate the design method of partial observer canonical form (POCF), which is one of the important research tools for industrial plants.

Motivated by the two-steps method proposed in Xu et al. (2020), this paper extends this method to the case of Multi-Input Multi-Output (MIMO) nonlinear system. It decomposes the original system into two subsystems by observable decomposition theorem first and then transforms the observable subsystem into OCF. Furthermore, the necessary and sufficient conditions for the existing of POCF are proved.

The proposed method has a wide range of applications including completely observable nonlinear system, noncompletely observable nonlinear system, autonomous nonlinear system and forced nonlinear system. Besides, comparing to the existing results (Saadi et al., 2016), the method requires less verified conditions.

The new method concerning design POCF has better plants compatibility and less validation conditions.

To meet the need of reducing the cost of industrial systems, sensorless control applications on electrical machines are increasing day by day. This paper aims to improve the performance of the sensorless induction motor control system. To do this, the speed observer is designed based on the combination of the sliding mode and the fractional order integral.

Super-twisting sliding mode (STSM) and Grünwald–Letnikov approach are used on the proposed observer. The stability of the proposed observer is verified by using Lyapunov method. Then, the observer coefficients are optimized for minimizing the steady-state error and chattering amplitude. The optimum coefficients (c₁, c₂, k_i and λ) are obtained by using response surface method. To verify the effectiveness of proposed observer, a large number of experiments are performed for different operation conditions, such as different speeds (500, 1,000 and 1,500 rpm) and loads (100 and 50 per cent loads). Parameter uncertainties (rotor inertia J and friction factor F) are tested to prove the robustness of the proposed method. All these operation conditions are applied for both proportional integral (PI) and fractional order STSM (FOSTSM) observers and their performances are compared.

The observer model is tested with optimum coefficients to validate the proposed observer effectiveness. At the beginning, the motor is started without load. When it reaches reference speed, the motor is loaded. Estimated speed and actual speed trends are compared. The results are presented in tables and figures. As a result, the FOSTSM observer has less steady-state error than the PI observer for all operation conditions. However, chattering amplitudes are lower in some operation conditions. In addition, the proposed observer shows more robustness against the parameter changes than the PI observer.

The proposed FOSTSM observer can be applied easily for industrial variable speed drive systems which are using induction motor to improve the performance and stability.

The robustness of the STSM and the memory-intensive structure of the fractional order integral are combined to form a robust and flexible observer. This paper grants the lower steady-state error and chattering amplitude for sensorless speed control of the induction motor in different speed and load operation conditions. In addition, the proposed observer shows high robustness against the parameter uncertainties.

Aircraft pitch control is fundamental for the performance of micro aerial vehicles (MAVs). The purpose of this paper is to establish a simple experimental procedure to calibrate pitch instrumentation and classical control algorithms. This includes developing an efficient pitch angle observer with optimal estimation and evaluating controllers under uncertainty and external disturbances.

A wind tunnel test bench is designed to simulate fixed-wing aircraft dynamics. Key elements of the instrumentation commonly found in MAVs are characterized in a gyroscopic test bench. A data fusion algorithm is calibrated to match the gyroscopic test bench measurements and is then integrated into the autopilot platform. The elevator-angle to pitch-angle dynamic model is obtained experimentally. Two different control algorithms, based on model-free and model-based approaches, are designed. These controllers are analyzed in terms of parametric uncertainties due to wind speed variations and external perturbation because of sudden weight distribution changes. A series of experimental tests is performed in wind-tunnel facilities to highlight the main features of each control approach.

With regard to the instrumentation algorithms, a simple experimental methodology for the design of optimal pitch angle observer is presented and validated experimentally. In the context of the platform design and identification, the similitude among the theoretical and experimental responses shows that the platform is suitable for typical pitch control assessment. The wind tunnel experiments show that a fixed linear controller, designed using classical frequency domain concepts, is able to provide adequate responses in scenarios that approximate the operation of MAVs.

The aircraft orientation observer can be used for both pitch and roll angles. However, for simultaneousyaw angle estimation the proposed design method requires further research. The model analysis considers a wind speed range of 6-18 m/s, with a nominal operation of 12 m/s. The maximum experimentally tested reference for the pitch angle controller was 20°. Further operating conditions may require more complex control approaches (e.g. scheduling, non-linear, etc.). However, this operating range is enough for typical MAV missions.

The study shows the design of an effective pitch angle observer, based on a simple experimental approach, which achieved locally optimum estimates at the test conditions. Additionally, the instrumentation and design of a test bench for typical pitch control assessment in wind tunnel facilities is presented. Finally, the study presents the development of a simple controller that provides adequate responses in scenarios that approximate the operation of MAVs, including perturbations that resemble package delivery and parametric uncertainty due to wind speed variations.

Monitoring of a process leading to the detection of faults and determination of the root causes are essential for the production of consistent good quality end products with improved yield. The history of process monitoring fault detection (PMFD) strategies can be traced back to 1930s. Thereafter various tools, techniques and approaches were developed along with their application in diversified fields. The purpose of this paper is to make a review to categorize, describe and compare the various PMFD strategies.

Taxonomy was developed to categorize PMFD strategies. The basis for the categorization was the type of techniques being employed for devising the PMFD strategies. Further, PMFD strategies were discussed in detail along with emphasis on the areas of applications. Comparative evaluations of the PMFD strategies based on some commonly identified issues were also carried out. A general framework common to all the PMFD has been presented. And lastly a discussion into future scope of research was carried out.

The techniques employed for PMFD are primarily of three types, namely data driven techniques such as statistical model based and artificial intelligent based techniques, priori knowledge based techniques, and hybrid models, with a huge dominance of the first type. The factors that should be considered in developing a PMFD strategy are ease in development, diagnostic ability, fault detection speed, robustness to noise, generalization capability, and handling of nonlinearity. The review reveals that there is no single strategy that can address all aspects related to process monitoring and fault detection efficiently and there is a need to mesh the different techniques from various PMFD strategies to devise a more efficient PMFD strategy.

The review documents the existing strategies for PMFD with an emphasis on finding out the nature of the strategies, data requirements, model building steps, applicability and scope for amalgamation. The review helps future researchers and practitioners to choose appropriate techniques for PMFD studies for a given situation. Further, future researchers will get a comprehensive but precise report on PMFD strategies available in the literature to date.

The review starts with identifying key indicators of PMFD for review and taxonomy was proposed. An analysis was conducted to identify the pattern of published articles on PMFD followed by evolution of PMFD strategies. Finally, a general framework is given for PMFD strategies for future researchers and practitioners.

The paper seeks to provide an adaptive fuzzy logic controller for permanent magnet synchronous motor (PMSM) under direct torque control (DTC) algorithm to minimize the torque ripple.

The design methodology is based on vector control analysis. MATLAB simulations supported with experimental study under C++ are used to execute the proposed work.

The results show that considerable torque ripple reduction as well as considerable current ripple reduction can be achieved by utilizing adaptive fuzzy switching algorithm to fire the inverter supplying the PMSM.

This research is limited to PMSM, however the research can be extended to include other AC motors as well. In addition, the following points can be studied, the effects of harmonics in control signals on the torque ripple. Digital and active filters as solution to these harmonics can be also addressed. The actual mathematical relation between the torque ripple and flux ripple can be studied to set the flux and torque bands width in reasonable value.

Based on existence DTC control system, it is only required to change the software‐switching algorithm, to provide smooth torque, given that the switching frequency of the inverter module is more than or equal to 15 kHz and the system is supplied with timers. In addition, a relatively higher DC voltage may be required to achieve higher speed compared with the traditional DTC.

In this paper, the stator flux position, and errors due to deviations from reference values of the torque and stator flux are used to select two active vectors while at the same time the absolute value of the torque error and the stator flux position are fuzzified to adapt the switching of the inverter in order to control the applied average voltage level in such a way as to minimize the torque ripple, so instead of fixed time table structure, a fuzzy logic is used to calculate the switching time for the selected vectors and no PI controller is used as the case in the traditional‐space vector modulation. This work is directed to motor drive system designers who seek highly smooth torque performance with fast response.

Sensorless online measurements, application of variable speed drives has been given a great attention, especially over the past few years. In most of the previous literates dealing with permanent magnet synchronous motor (PMSM) drives, the combination of inter-sampled behavior with high gain design approach has not been discussed yet. This paper aims to discuss this feature in-depth.

The study contains a different approach for an observer running with surface-mounted permanent magnet synchronous machine drives to implement sensorless control. Design of sampled data observer methodology for one kind of AC machine having non-linear model and backed by an elegant formal stability convergence analysis using the tools of Lyapunov stability techniques was highly recommended in scientific contributions, and it is yet needed to be solved.

In this study, a solution to observation problem is covered and developed by combining ideas from the high-gain design approach and inter-sample predictor based on stator voltage measurements. The output state currents are accessible only at the sampling instant to solve the problem of states observation at continuous-time mode. This allows to reducing the usage of online appliances, improving reliability of control design and saving costs.

The proposed observer is capable of guaranteeing an acceptable closed loop dynamic response over a wide range of operation region and industrial process for random initial conditions.

The output state predictor has been interred in constructing the innovation correct term to prove the robustness of the proposed observer against attenuated sampling interval. To validate the theoretical results introduced by the main fundamental theorem and prove the observer stability convergence, the proposed observer is demonstrated through a sample study application to variable speed permanent magnet synchronous machine drive.

The purpose of this paper is to present an actuator fault detection method for unmanned aerial vehicles (UAVs) based on interval observer and extended state observer.

The proposed algorithm has very little model dependency. Therefore, a six-degree-of-freedom linear equation of UAVs is first established, and then, combined with actuator failure and external disturbances in flight control, a steering gear model with actuator failure (such as stuck bias and invalidation) is designed. Meanwhile, an extended state observer is designed for fault detection. Moreover, a fault detection scheme based on interval observer is designed by combining fault and disturbances.

The method is testified on the extended state observer and the interval observer under the failure of the steering gear and bounded disturbances. The simulation results show that the two types of fault detection schemes designed can successfully detect various types of faults and have high sensitivity.

This research paper studies the failure detection scheme of the UAVs’ actuator. The fault detection scheme in this paper has better performance on actuator faults and bounded disturbances than using regular fault detection schemes.

This paper aims to design the fractional order sliding mode controller for highly maneuverable remote piloted unmanned aircraft with time-varying delays.

With the assumption that the time-varying delays are bounded and identical for different outputs, an observer-based control technique is implied which reformulates the state variables based on the system model and delayed outputs. The estimated state variables are fed as feedback into the controller. Based on the delayed output observer, a fractional order sliding mode controller is designed. Further, the stability of the closed-loop system is analyzed and asymptotical convergence is realized using Lyapunov–Razumikhin theorem.

The simulation is done in Matlab and Simulink. The parametric variations and trajectory tracking results are illustrated which looks propitious.

In practical operation, measurement signal is often delayed, which significantly degrade the control performance or even disturb the stability. It is emphasized to choose attitude as the evaluation indicator for unmanned aerial vehicle time delay.

A novel fractional order sliding mode control technique is designed to enhance the trajectory tracking, thus autonomous flight performance, of the aircraft system. Also, the main idea behind this novel procedure is formulated for minimizing the parametric variations in presence of time delays.