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Sequential techniques can enhance the efficiency of the approximate Bayesian computation algorithm, as in Sisson et al.'s (2007) partial rejection control version. While this method is based upon the theoretical works of Del Moral et al. (2006), the application to approximate Bayesian computation results in a bias in the approximation to the posterior. An alternative version based on genuine importance sampling arguments bypasses this difficulty, in connection with the population Monte Carlo method of Cappé et al. (2004), and it includes an automatic scaling of the forward kernel. When applied to a population genetics example, it compares favourably with two other versions of the approximate algorithm.

The active disturbance rejection control (AD RC), first proposed by Jingqing Han in late 1980s, is a powerful control technology being able to deal with external disturbances and internal uncertainties in large scale for control systems in engineering applications. This survey paper will articulate, from a theoretical perspective, the origin, ideology and progress of ADRC for not only uncertain finite-dimensional systems but also uncertain infinite-dimensional ones. Some recent theoretical developments, general framework and unsolved problems of ADRC for finite-dimensional systems with mismatched disturbances and uncertainties by output feedback, uncertain finite-dimensional stochastic systems, uncertain infinite-dimensional systems described by both the wave equation and the fractional-order partial differential equation are successively addressed, from which we see the challenges and opportunities for this remarkable emerging control technology to various types of control systems.

Partial discharge (PD) measurements provide valuable information for assessing the condition of high voltage (HV) insulation systems, contributing to their quality assurance. Different PD measuring techniques have been developed in the last years specially designed to perform on-line measurements. Non-conventional PD methods operating in high frequency bands are usually used when this type of tests are carried out. In PD measurements the signal acquisition, the subsequent signal processing and the capability to obtain an accurate diagnosis are conditioned by the selection of a suitable detection technique and by the implementation of effective signal processing tools. This paper proposes an optimized electromagnetic detection method based on the combined use of wideband PD sensors for measurements performed in the HF and UHF frequency ranges, together with the implementation of powerful processing tools. The effectiveness of the measuring techniques proposed is demonstrated through an example, where several PD sources are measured simultaneously in a HV installation consisting of a cable system connected by a plug-in terminal to a gas insulated substation (GIS) compartment.

Motivated by the thought of using couplings to reject disturbances, the authors propose a novel partial inverted decoupling control for improving the disturbance rejection of multivariable processes with time delays. With the relative disturbance gain (RDG) for n × n processes, whether the couplings among loops are favorable is evaluated. The inverted decoupling usually used in full decoupling control is then extended to partial decoupling control to retain the favorable couplings and remove the unfavorable ones. The elements of the partial inverted decoupler are derived and the implementation structure is provided. Based on the partially decoupled processes, the decentralized controllers for both the decoupled and non-decoupled loops are designed. An analytical design method for the decentralized controllers is proposed to improve disturbance rejection. Controller parameters are determined in terms of both performance and robustness. Two simulation examples show that the presented partial inverted control strategy can provide superior disturbance rejection to several other classical multivariable control strategies.

Autonomous Underwater Vehicle are widely used in industries, such as marine resource exploitation and fish farming, but they are often subject to a large amount of interference which cause poor control stability, while performing their tasks. A decoupling control algorithm is proposed and A single control volume–single attitude angle model is constructed for the problem of severe coupling in the control system of attitude of six degrees of freedom Autonomous Underwater Vehicle. Aiming at the problem of complex Active Disturbance Rejection Control (ADRC) adjustment relying on manual experience, the PSO-ADRC algorithm is proposed to realize the automatic adjustment of its parameters, which improves the anti-interference ability and control accuracy of Autonomous Underwater Vehicle in dynamic environment. The anti-interference ability and control accuracy of the method were verified through experiments.

The conventional nonlinear control methods for induction motors have the problem of difficult observation of rotor current, and load disturbances make the dynamic performance of the system speed control unsatisfactory. A novel disturbance rejection control scheme with variable damping model based on port controlled Hamiltonian with dissipation is proposed. The induction drive is regarded as energy conversion device including mechanical and electrical ports. The Euler Lagrange equation of the closed-loop system is obtained by the output feedback to establish the energy shaping control method. The variable damping injection is introduced to improve the dynamic performance of the conventional control methods. The L 2 disturbance rejection controller is designed to enhance the load disturbance resistance performance of induction motors. The experimental results show that the proposed method can optimize the dynamic and steady-state performance of the induction drive control system and effectively meet the control requirements of the speed and torque under load disturbances.

In the present scenario, the utilization of petroleum fuel is expanding forcefully worldwide in the vitality store and plays a highly hazardous role in the ecological system. Biofuel stands out among the most tenable keys for this issue. The lemongrass oil is used as a biofuel because of low density and viscosity when compared with diesel. The lemongrass oil is extracted by steam distillation process. In the present investigation, partially stabilized zirconium, due to its higher thermal conductivity, is selected as coating material. The top surface of the piston and the inlet and exhaust valves are coated up to the preferred thickness of 500 μm by the plasma spray technique. The lemongrass emulsion fuel is prepared in the proportion of 94% of lemongrass oil, 5% of water, and 1% of surfactant span 80. The nanoparticles of cerium oxide were used with lemongrass oil (LGO) nano-emulsion in the measurement of 30 ppm. The four-stroke diesel engine execution, ignition, and the outflow extent were contrasted in the diesel and lemongrass oil (LGO) compared with the base diesel engine. The performance characteristic curves of lemongrass-cerium oxide nano-emulsion fuel show the increase in brake thermal efficiency of 17.21% when compared with the mineral diesel fuel. The emission characteristics of lemongrass-cerium oxide nano-emulsion fuel show a drop in hydrocarbon and carbon monoxide emission by 16.21% and 15.21%, respectively, when compared with base diesel fuel and also there is a decrease in oxides of nitrogen and smoke emission by 24.1% and 6.3%, respectively, when compared to mineral diesel fuel.

In this paper, we consider performance output tracking for a boundary controlled one-dimensional wave equation with possibly unknown internal nonlinear uncertainty and external disturbance. We first show that the open-loop system is well-posed and then propose a disturbance estimator. It is shown that the disturbance estimator can estimate successfully the total disturbance that consists of internal uncertainty and external disturbance. An servomechanism based on the estimated total disturbance is then designed. It is shown that the closed-loop system is well-posed. Three control objectives are achieved: (a) the output is tracking the reference signal; (b) all the internal signals are uniformly bounded; (c) the closed-loop system is internally asymptotically stable if both the reference signal and the disturbance vanish or belong to the space H2(0, ∞) and L2(0, ∞), respectively. The unmatched performance output tracking control is first time applied to a system described by the partial differential equation for complete general disturbance rejection and reference tracking purpose. Another key feature of this paper is that we do not use the high-gain to estimate total disturbance for unmatched system. The numerical experiments are carried out to illustrate effectiveness of the proposed control law.

This paper provides a detailed analysis of the output voltage/current tracking control of a PWM DCDC converter that has been modeled as a Markov jump system. In order to achieve that, a dynamic sensorless strategy is proposed to perform active disturbance rejection control. As a convex optimization problem, a novel reformulation of the problem is provided to compute optimal control. Accordingly, necessary less conservative conditions are established via Linear Matrix Inequalities. First, a sensorless active disturbance rejection design is proposed. Then, to carry out the control process, a robust dynamic observer–predictive controller approach is introduced. Meanwhile, the PWM DC-DC switching power converters are examined as discrete-time Markovian switching systems. Considering that the system is subject to modeling uncertainties, time delays, and load variations as external disturbances, and by taking partial input saturation into account, the Lyapunov–Krasovskii function is used to construct the required feasibility frame and less conservative stability conditions. As a result, the proposed design provides an efficient control strategy with disturbance rejection and time-delay compensation capabilities and maintains robust performance with respect to constraints. Finally, a PWM DC-DC power converter simulation study is performed in different scenarios, and the obtained results are illustrated in detail to demonstrate the effectiveness of the proposed approach.

This paper explores finite-time formation control of multi-agent systems (MASs) with high-order nonaffine nonlinear dynamics and saturated input. Based on active disturbance rejection control theory, extended state observer is employed to identify unknown nonaffine nonlinear functions in MASs. The proposed control law consisting of backstepping control, tracking differentiator, and finite-time performance function is adopted for MASs to achieve the desired formation while reaching performance requirements. An auxiliary dynamic compensator is introduced to correct the control deviation caused by input saturation. Lyapunov stability theory is utilized to analyze the stability of the closed-loop system, which guarantees that the formation tracking error can asymptotically converge to an arbitrarily small neighborhood around zero in finite time. Finally, the simulation results show that compared to the adaptive, cooperative learning, and virtual structure methods, the proposed control algorithm has stronger tracking ability and faster setting time (1.8 s) under the influence of nonaffine nonlinear uncertainties. The integral square error for the formation control strategy in this paper is 0.16, which is much smaller than the abovementioned methods and is therefore provided to manifest the validity and feasibility of the proposed control strategy.