Transactions of the Institute of Measurement and Control

Gupta, Dhananjay; Kumar, Awadhesh; Giri, Vinod Kumar

doi: 10.1177/01423312231203483pmid: N/A

An adaptive control law encompasses a regulating control rule compensating for system dynamics variations by adjusting the controller characteristics to maintain the overall system performance. Recently, some techniques have been developed based on fundamental aspects of the adaptability of living organisms. The adaptive control method is a technique that measures the dynamic characteristics of the plant automatically and continuously to make a comparison with its required output. It utilizes the difference between these two to commute adaptable system parameters to maintain optimal performance regardless of the system variations. The behavior of the adaptation rule is significantly affected by the adaptation gain value. Here, it has also been investigated that the adaptation gain range is wide for the systems with the lower order. The appropriate range of adaptation gain decreases as the order of the system increases. In the present work, the model reference adaptive control (MRAC) for first- and second-order systems has been designed and investigated using a wide range of values for the adaptation gain and variations in the reference model parameters. The MIT (Massachusetts Institute of Technology) and Lyapunov rules are applied for the analyses of systems. On the MATLAB/Simulink platform, all the adaptation process comparisons, variations, and investigations have been carried out by altering the adaptation gain and the reference model parameters. The obtained results present encouraging outcomes.

Mohammadzadeh, Amir; Tavassoli, Babak

doi: 10.1177/01423312231202667pmid: N/A

Identification of networked systems over communication links with packet losses is considered. It is assumed that there is no connection from the actuators to the system identifier such that no information is available on loss of data packets carrying the actuation signals. While the packet loss occurrences in the sensor links are naturally detectable by the system identifier as the receiving node, the packet loss occurrences in the actuation paths are not directly detectable. The existing system identification methods fail to be applicable without the information on packet loss occurrences. Presenting a solution for this issue is the objective of the present work. Two recursive algorithms are proposed to solve the problem in real time. For this purpose, ARMAX input–output representations of the system with Markovian jumping modes are developed. Then, filters are designed for estimation of the packet loss occurrences. The estimated mode is used in the recursive algorithms for identification of the whole system based on the maximum likelihood approach. A main algorithm and its simplified version are proposed that are capable of finding the various kinds of system parameters including the physical plant parameters and the communication mode transition probabilities. Effectiveness of the algorithms is verified through simulation examples where the system performance is evaluated and compared.

Amiri, Fatemeh; Khorashadizadeh, Saeed

doi: 10.1177/01423312231203270pmid: N/A

In this paper, an adaptive controller for a class of uncertain nonlinear systems is presented using a combination of Legendre polynomials and brain emotional learning-based intelligent controller (BELBIC). Recently, some versions of BELBIC have been presented with the aim of satisfying the universal approximation property using Gaussian basis function. However, the size of regressor vector is too large that imposes a heavy computational load to the processor. The novelty of this paper is presenting a new version of BELBIC with less computational burden using Legendre polynomials. Moreover, there are very few tuning parameters in Legendre polynomials. Another contribution of this paper is editing the stability analysis presented in recent related works. Due to the intrinsic non-differentiability of the adaptation rules of BELBIC, the second time derivative of Lyapunov function is undefined and thus, the Barbalat’s lemma cannot be applied to verify the asymptotic convergence of the error function. Therefore, bounded-input-bounded-output (BIBO) stability can only be claimed for this controller. Simulation results on different case studies show that Legendre polynomials can improve the universal approximation property of BELBIC with less tuning parameters. Moreover, in the absence of the robust control term in the control law, the performance Legendre polynomials will not deteriorate, while the performance degrade in Gaussian basis function is quite considerable.

Kızmaz, Hakan

doi: 10.1177/01423312231201234pmid: N/A

A current challenge with adaptive controllers is to define efficient tuning methods of the controller parameters. Unlike linear systems, nonlinear systems may need parameters that are continuously tuned at different operating points to provide stability and desired behaviours. This study aims to develop a solution for tuning proportional–integral–derivative (PID) controller parameters as opposed to changing the operating points of a nonlinear system. Most tuning methods calculate parameters according to the system’s step or frequency response. However, adaptive controllers have self-tuneable parameters or control rules. The proposed algorithm in this paper contains a controller, an estimator, and a reference model, and uses the system model. Unlike the model reference adaptive control method, the proposed controller has tuneable controller parameters estimated by the extended Kalman–Bucy filter. The filter estimates the controller parameters to make the system perform like the auxiliary ideal reference model to ensure minimum-time consumption. Hence, this study aims to develop an algorithm that will automatically calculate controller parameters for each operating point of the controlled chaotic or nonlinear system to minimize settling time at each operating point. The proposed algorithm is implemented in a unified chaotic system in which the estimator and controller of the system run together. Simulation results confirm the performance of the proposed algorithm. In addition, the simulation results provide strong evidence that the proposed algorithm can be an effective tool for controlling nonlinear or chaotic systems.

Lim, Sok Li; Yeong, Wai Chung; Chong, Zhi Lin; Gan, Chew Peng; Khoo, Michael Boon Chong

doi: 10.1177/01423312231213125pmid: N/A

A major challenge for control charts monitoring the coefficient of variation is to quickly detect shifts in this parameter, so that assignable cause(s) can be quickly removed and the process can operate in an in-control state with a stable coefficient of variation. This is especially so when there are constraints in the sample size. One proposed strategy is to vary the sample size according to the most recent information. However, a side-sensitive synthetic chart monitoring the coefficient of variation with variable sample size is not available. This paper contributes to the literature by developing a variable sample size side-sensitive synthetic chart for the coefficient of variation. The main contributions are in terms of illustrating the operations of the chart, deriving the formulae to evaluate its performance and developing the algorithms to optimize its performance. Comparisons with current charts show that the proposed chart outperforms all existing synthetic-type charts monitoring the coefficient of variation. The proposed chart also outperforms the variable sample size coefficient of variation chart for all shift sizes. In addition, it outperforms the variable sample size run sum and variable sample size Exponentially Weighted Moving Average charts monitoring the coefficient of variation for moderate and large shift sizes.

Esfouna, Oussama; Ouahi, Mohamed; Tissir, El Houssaine

doi: 10.1177/01423312231210054pmid: N/A

In this paper, a new fuzzy Functional observer is developed for nonlinear neutral systems. Also, the existence conditions for it are studied. The delay-dependent stability of this observer is guaranteed by the combination of the solution of the Sylvester equation and the Lyapunov–Krasovskii stability approach. The parameters of the studied observer are obtained by solving linear matrix inequalities (LMIs). The performance of the approach developed in this paper is demonstrated at the end of the paper by numerical examples.

Huang, Qingnan; Zhang, Enze; Dai, Xisheng; Qi, Jingru; Wu, Qiqi

doi: 10.1177/01423312231196640pmid: N/A

This paper analyzes the problem of simultaneous fault detection and control of the six-rotor unmanned aerial vehicle control system, considering external disturbance, measurement disturbance, and actuator fault. The integral event trigger mechanism is introduced in the control side and sensor side of the system. Based on Lyapunov stability and H∞ control theory, the sufficient conditions to make the fault system asymptotically stable and have certain performance indexes are given by means of linear matrix inequalities; at the same time, the design criteria of event trigger parameters are also given. The linear matrix inequality is decoupled, and the calculation method of gain matrix of simultaneous fault detection and control module is given. The effectiveness of the proposed method is verified by simulation experiments.

Wang, Jianmei; Luo, Xiaoyuan; Li, Mengjie; Guan, Xinping

doi: 10.1177/01423312231197848pmid: N/A

In this paper, a distributed nonsingular terminal sliding mode control (NTSMC) is proposed for vehicular platoons subjected to nonlinear uncertainty, external disturbance, and input saturation. Due to the presence of input saturation, the platoon control becomes more complicated. However, only considering the impact of uncertainty on the system, input saturation will usually lead to a decline in the driving performance, even lead to string instability. First, the input saturation is compensated by a single parameter, which is simple and direct. The radial basis function neural network (RBFNN) based on disturbance observer is employed to compensate the nonlinear uncertainty and external disturbance, respectively. The basis function of neural network is only related to the velocity and acceleration of the leader. Therefore, the nonlinearity of the vehicle systems does not need to meet the matching conditions. Then, a distributed NTSMC is designed to realize the internal stability, which weakens the chattering of traditional sliding mode control (SMC) to some extent. In addition, the nonsingular problem in terminal sliding mode control (TSMC) is solved. The string stability is realized by employing a coupled sliding mode control (CSMC). Finally, simulation results demonstrate the effectiveness and feasibility of the proposed strategy.

Ren, Yuanhong; Li, Zhiwei; Sun, Yuqing

doi: 10.1177/01423312231198412pmid: N/A

The problems of prescribed-time leader-following consensus and prescribed-time containment control for double-integrator multiagent systems (MASs) with only position measurements are investigated in this paper. An observer-based prescribed-time control protocol is proposed, in which the two groups of observers for estimating the consensus errors of each follower both converge to zero within a specified time. Furthermore, the proposed controller only relies on its own observers and does not need to obtain the data from observers embedded in its neighbor nodes. The sufficient conditions for the MASs to achieve the defined prescribed-time consensus and to fulfill the goal of prescribed-time containment control are, respectively, given. The effectiveness of the proposed control protocol is further verified by computer simulations.

Luo, Maosen; Huang, Shipei; Yan, Zhengbing; Zhang, Zhengjiang; Zeng, Guoqiang

doi: 10.1177/01423312231199142pmid: N/A

This paper is concerned with the event-triggered control of switched two-dimensional (2D) continuous-discrete systems in Roesser model. A more general event-triggered scheme is proposed to reduce unnecessary resource waste and data redundancy, where a weighing coefficient and multiple parameter matrices are used. Based on the proposed event-triggered mechanism, a state feedback controller and a state-dependent switching signal are proposed. By using the multiple Lyapunov function method, sufficient conditions for the exponential stability of the closed-loop system are derived in terms of linear matrix inequalities. Finally, two examples are provided to illustrate the effectiveness of the proposed method.