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In recent years, a new paradigm in control engineering, called networked control system (NCS), has emerged due to the success of internet and associated communication infrastructure. The NCS offers various advantages compared to traditional control systems which include increase of agility, wiring reduction, and easy maintenance and diagnosis. With an objective to investigate the effectiveness of various controllers in networked environment, the present study designs a -based single-bit PID controller for the rotor side converter (RSC) of a doubly-fed induction generator (DFIG) based wind energy conversion system (WECS). This consists of 20-DFIGs of 5MW capacity each. A comparative performance investigation has been carried out with three other controllers; a conventional PID, Q-Learning and Dynamic Fuzzy Q-Learning (DFQL) controller. The study considers various imperfections of a Zigbee protocol based practical communication network such as random delay and packet dropout. The results of both the simulation and experiment demonstrate that the -based single-bit PID controller shows better performance compared to other controllers.

In this paper, an uncertainty and disturbance estimator (UDE)‐based control is employed to ensure the finite‐time tracking and disturbance rejection performance for a class of Takagi–Sugeno fuzzy switched systems including additive time‐varying delays, unknown time‐varying uncertainties and disturbances. To be precise, the robust tracking performance is achieved by estimating unknown uncertainties and disturbances with the aid of low‐pass filter by means of appropriate bandwidth choice of the desired filter. Moreover, a new delay‐dependent finite‐time stability criterion is derived by employing fuzzy‐dependent Lyapunov–Krasovskii functional, extended Wirtinger's integral inequality and average dwell‐time approach to enforce the addressed system to track the given reference system within a finite period of time. Finally, the developed theoretical results are ensured by presenting the numerical examples with simulation results.

Power electronic converters find application in diverse fields due to their high power conversion efficiency. Converters are often characterized by time response specifications, robustness and stability. Conventionally, converters employ the classic PID controller. The state space average linear time invariant model of a boost converter is known to be a non-minimum phase system. This paper demonstrates that the boost converter with a PID controller using the Queen Bee assisted Genetic Algorithm (QBGA) optimization is not robust to plant parameter variations. A fractional order PID controller based on QBGA optimization proposed here is shown to have improved robustness. The controller proposed here is applicable across converters, viz., buck, boost and buck-boost, equally.

This work presents an investigation on Improved Extended Kalman Filter (IEKF) performance for induction motor drive without a speed sensor. The performance of a direct sensorless vector-controlled system through simulation and experimental work is tested. The proposed observer focuses on estimating rotor flux and mechanical speed of rotor from the stationary axis components. Extended Kalman Filters’ estimation performance depends on the system matrix’s proper value ( $Q$ ) and measurement error matrix ( $R$ ). These matrices are assumed to be persistent and are calculated by the trial-and-error method. But, the operating environment affects these matrix values. They must be updated based on the prevailing operating conditions to get high speed and accurate estimates. The values of Q and R in the Improved EKF (IEKF) algorithm are obtained using the genetic algorithm. Besides, IEKF is incorporated to reduce in computational burden for real-time applications.

The vigorous growth of electric vehicles in the field of automobile paves the way for the development of dc-dc converter. A novel high gain super Luo dc-dc converter is proposed in this article. A modification is suggested in the topology when the converters are cascaded for high gain. This suggested modification can be applied to any topology for reliable capacitor. The presented converter adds boosting (voltage multiplier) cell before the load to expand the voltage conversion ratio. This converter renders remarkable features like extended voltage gain, low voltage stress on power switches, minimal capacitor stress and less component count. The operating principle and steady-state analysis of the proposed topology is presented. The main feature of the proposed topology is reduced capacitor stress which is evaluated by reliability study with military handbook MIL-HDBK-217F. The significance of minimal capacitor stress with the failure of the capacitor is elaborated. Simulation on the derived topology is carried out with Matlab/Simulink and it validates the theoretical results. Furthermore, the proposed topology is extended with dual output which makes the restructured converter suitable for Electric vehicle application and the simulation of the dual output topology is performed and studied. The experimental results obtained from the 50 W prototype validate the complete steady-state analysis performed on the proposed topology.

In this brief, non-fragile fault alarm-based hybrid control design for the attitude quadrotor model with actuator saturation is developed. Specifically, the fault alarm-based signal is proposed based on the alarm threshold value to timely alert the controller to switch from the robust controller to fault-tolerant controller. More precisely, with the aid of extended Wirtinger’s integral inequality and new double integral inequality, a new set of stability conditions with delay-dependent terms in the form of linear matrix inequalities is derived to achieve the desired attitude performance of the quadrotor. At last, the efficiency of the developed theoretical result is validated by presenting the simulation result for the quadrotor model and also clearly shows the timely alert performance of the designed alarm signal to restrain the system stability.

In this paper, the stabilization problem for a class of periodic piecewise linear systems with uncertainties, time-varying delay, actuator faults and disturbances is discussed. Precisely, the resilient reliable control scheme is designed to stabilize the addressed system with satisfactory disturbance attenuation index. Moreover, the concerned system is a kind of periodic system which consists of many subsystems with constant state dynamics. Based on fixed dwell time approach, the addressed system is divided into many piecewise subsystems and activated periodically. Depending on the division of subintervals, the sufficient conditions are derived by constructing a proper Lyapunov–Krasovskii functional with piecewise time-varying positive definite matrices. Further, the periodic time-varying control gain matrices for individual subsystems are obtained via solving the developed constraints. Specifically, the potential and impact of the developed control scheme is examined by presenting two numerical examples including the periodic piecewise vibration systems.

In this work, the authors precisely concentrate on the subject of enhanced vehicle handling performance of the bicycle model with two-degrees-of-freedom via improved-equivalent-input-disturbance and repetitive control technique. To be specific, improved-equivalent-input-disturbance estimator is inserted into the controller design for attenuating the effect of the crosswind in the considered vehicle system with state-delay. A modified two-dimensional repetitive control design is implemented for improving the accurate tracking performance of the considered model. In particular, by combining an improved-equivalent-input-disturbance approach together with two-dimensional modified repetitive control design, steering angles of front and rear wheels of the considered vehicle have been controlled in order to achieve the accurate tracking performance of the vehicle states. The criteria for the robust asymptotic stability on the basis of Lyapunov stability theory is developed by means of the sufficient conditions which are obtained in the form of linear-matrix-inequalities. Simultaneously, through these inequality conditions, the parameters of proposed improved-equivalent-input-disturbance based repetitive control strategy are designed for improving the accurate tracking performance against the crosswind effect. Finally, simulation results are presented to show that the proposed control design is more effective when aperiodic disturbances occur.

In this work, a new control methodology is proposed for Type -IV wind energy conversion system (WECS) using a self-recurrent wavelet neural network (SRWNN) control with a Vienna rectifier as the machine side converter (MSC). A SRWNN combines excellent dynamic properties of recurrent neural networks and the fast convergence speed of wavelet neural network. Hidden neurons of SRWNN contains local self-feedback loops, which provide the memory feature and the necessary information of past values of the signals, allowing it to track maximum power from WECS under varying wind speeds. The Vienna rectifier allows unity power factor operation to increase electrical efficiency. Frame angle-controlled wavelet modulation is proposed for the grid side converter (GSC). Wavelet modulated inverter produces output voltage fundamental components with higher magnitudes than those obtained from the pulse width modulated inverters. The non-linear load compensation and power quality enhancement are achieved by executing frame angle control for WM inverter. The overall system is modeled, and performance is verified in MATLAB Simulink. The hardware prototype is developed, and the switching pulses for the rectifier and inverter are generated using dSPACE1104 controller. The results prove that the system provides low harmonic content and high magnitude of the fundamental current component at the machine and grid sides and ensures maximum power operation at various wind speeds.

This paper presents a binary hybrid multilevel inverter (BHMLI) based grid-connected solar energy conversion system (SECS), controlled by damped second-order generalized integral (DSOGI). The BHMLI architect has a cascaded half-bridge array, which modifies the DC-link of the H-bridge of the voltage source inverter, and results in approximate reference waveform. It reduces the dV/dt of the H-bridge switches and improves output waveform quality. The DSOGI control damps the oscillations and overshoots and provides longer service period of low power switches at transient conditions. It is implemented in the multilevel inverter application for the first time in literature. The SECS is designed to inject active power to the grid, and also mitigates the harmonic and reactive power demands of the load. The cascading of n' half-bridges and one H-bridge generate (2(nC1) - 1) output voltage levels. The maximum power extraction from solar photovoltaic (PV) array is achieved through incremental conductance (IC) algorithm based maximum point tracking (MPPT) operation of the DC-DC converter. An isolated single-input multiple-output single-ended primary inductance converter (SIMO-SEPIC) realizes it. SECS with 15-level BHMLI is analyzed with extensive simulation as well as with a hardware prototype. Moreover, the shunt active filter functionality of the system at various load conditions are verified and maintained the grid power quality within the IEEE-519 standard throughout the operation. The laboratory developed setup is tested for 5 kW, 400 V, three-phase system, and the experimental analysis at steady-state and dynamic variations of load-side and insolation variations validate the theoretical claims.

This paper proposes a Resistance perturbation based maximum power point tracking (MPPT) with an adaptive control limit algorithm to extract the maximum power from solar photovoltaic (PV) array. This algorithm consists of two main functions, namely 1) resistance perturbation & observation (RP&O) and 2) adaptive resistance control (ARC) limit. The RP&O operates the PV array at maximum power point (MPP), and the ARC limit continuously monitors the resistance of the PV Rpv to determine the operating limit of MPP. The ultimate aim of proposing this algorithm is to reduce the oscillations and improve MPP's tracking performance for sudden variation in temperature and irradiance conditions. Furthermore, it does not require an expensive pyranometer or temperature sensor to track the MPP of the PV array. This paper also compares the proposed and conventional MPPT algorithm's performance. Its validation results in both MATLAB/Simulink and experimental studies are presented under constant and sudden changes in irradiance conditions.

This article proposes a $\Delta $ -Modulator ( $\Delta $ -M) based quantised output feedback controller for linear networked systems. The proposed $\Delta $ -M is essentially a 2-level quantiser, in contrast to some of the existing quantisers such as $2^{p}$ level ( $p \geq 1$ ) uniform-interval-nearest-neighbour quantiser, and offers various advantages which include lower design complexity, less noisy and lower cost. The three key components of the control system: the controller , the filter and the quantiser are designed to achieve the desired performance. The stability conditions of the $\Delta $ -M are derived and conditions for the existence of zig-zag behaviour in steady-state are determined. The performance of the proposed controller is illustrated through simulations considering practical communication network based on ZigBee protocol. The results of the simulation demonstrate that the proposed controller could effectively achieve desired performance under various imperfections of the practical communication network.

This paper deals with the robust fault estimation based synchronization problem for a class of fractional-order multi-weighted complex dynamic networks subject to external disturbances. Specifically, the synchronization problem is converted to an equivalent uniformly ultimately boundedness problem of the corresponding error system by use of spectral decomposition of the Laplacian and proper scalings of the faults. First, by introducing an intermediate estimator technique and using monochromatic Lyapunov function method, the sufficient condition for uniformly ultimately boundedness of the resulting error system via fault estimation based non-fragile controller is presented. Next, by using the linear matrix inequality (LMI) technique and optimization approach, the existence condition in the form of LMIs for designing the fault estimation based robust non-fragile controller is derived. Finally, two numerical examples including financial model are provided to demonstrate the validity and feasibility of the developed theoretical results.

This paper presents the use of a delta-sigma quantizer for generalized one-bit control processing. An equivalent control strategy based on sliding-mode control is employed to derive the necessary condition for the convergence of the proposed one-bit control system in both the continuous-time and discrete-time domains. Under the convergence condition, the binary signals generated by delta-sigma quantizers in the one-bit control system effectively replace their counterpart signals in conventional control systems. This enables a significant reduction in the number of multipliers and overall hardware cost for computing the control laws in one-bit control systems. Our result is applied to design a multiplier-less one-bit generalized proportional and integral controller for the position control of an experimental prototype of a DC motor. An implementation of the one-bit control system is carried out using an FPGA platform to demonstrate the behavior of one-bit generalized proportional and integral controller and compare the results with the standard in terms of implementation efficiency. The results of the simulation and experiment show that the one-bit generalized proportional and integral controller effectively controls the system and achieves the desired specifications. At the same time, the proposed one-bit control system consumes significantly fewer hardware resources than the standard control system.

The main attention of this paper is to tackle the issue of robust tracking and disturbance estimation for the four wheel steering vehicle by implementing a feedback control design based on the improved-equivalent-input-disturbance technique and the Smith predictor approach. The intention of incorporating the Smith predictor into the controller design is to compensate the effect of input time-delay. In addition, the improved-equivalent-input-disturbance technique is applied for dealing with the nonlinear uncertainty and external disturbances. Based on the proposed controller, both front and rear steering angles of the considered model are controlled to trace the desired position of the vehicle. More precisely, the developed criterion that ensures the desired tracking performance of the vehicle is obtained in the form of linear-matrix-inequalities based on the construction of an appropriate Lyapunov-Krasovskii functional candidate. Numerical simulation results for vehicle dynamics are presented to examine the performance of the proposed control strategy.

The present study proposes a new dynamic two-level quantizer, called as hybrid delta modulator ( $\Delta _{H} $-M), which combines the features of both delta-modulator and delta-sigma modulator. In the transient state, the $\Delta _{H} $-M exhibits the dynamical behaviour of delta modulator (Δ-M) while in steady state, its behaviour is similar to delta-sigma modulator ( $\Delta \Sigma $-M). This study investigates about various dynamics of the proposed $\Delta _{H} $-M in both continuous and discrete-time domains. The stability conditions of $\Delta _{H} $-M are derived using the theory of sliding and quasi-sliding mode. The theoretical results are validated through extensive simulations. Abbreviations: Δ-M: delta modulator; $\Delta _{H} $-M: hybrid delta modulator; $\Delta \Sigma $-M: delta sigma modulator; ADC: analogue to digital converter; CT: continuous-time; DAC: digital to analogue converter; DT: discrete-time; NCS: networked control system; QSM: quasi-sliding model; QSMD: quasi-sliding mode domain; SS: steady state; TP: transient process

Microgrids are often considered as the solution for affordable and clean energy in the distribution sector. This article presents the small-signal stability analysis of a distributed generation unit in an autonomous microgrid operation. The purpose of the proposed strategy is to optimally improve the capacity of the power system to restore the reasonable operating condition following a small physical disturbance. The proposed strategy is the joined execution of both the modified antlion optimization algorithm (MALO) and artificial neural network (ANN), and hence it is abbreviated to MALANN. In this article, the proposed controller comprises two control loops, namely the inner current control loop and the outer power control loop. The MALO technique is incorporated to generate the dataset of possible proportional integral (PI) gain parameters. By using the accomplished dataset of MALO, the ANN is trained, and convincing estimate execution is brought out through the entire machine working condition. The proposed strategy is implemented in MATLAB/Simulink, and the results are examined with two test cases and compared with various solution techniques such as base method and ant-lion optimization. The results prove that the stability analysis is reasonably accurate, and the controller offers a reliable system's operation.

During the past two decades, a new paradigm in control engineering, called networked control system (NCS), has emerged. This has been shown to be a successful alternative to traditional control systems. The present study designs a reinforcement learning controller based on the concept of Dynamic Fuzzy Q-Learning (DFQL). This controls the rotor side converter (RSC) of a doubly-fed induction generator (DFIG) of a wind energy conversion system (WECS) through a communication network. A comparative performance investigation has been carried out with two other controllers; namely a conventional PID and Q-Learning controller. The performance of these controllers is studied considering various imperfections of the communication network such as random delay and packet dropout. Simulations are carried out considering a WECS consisting of 20-DFIGs of 5MW capacity each. The results of the study demonstrate that the DFQL controller shows better performance compared to Q-Learning and conventional PID controllers.

Water hammering is a significant problem in pumping systems. It damages the pipelines of the pump drastically and needs to identify with an intelligent method. Various conventional methods such as the method of characteristics and wave attenuation methods are available to identify water hammering problems, and the predictive control method is one of the finest and time-saving methods that can identify the anomalies in the system at an early stage such that the device can be saved from total damage and reduce energy loss. In this research, a machine learning (ML) algorithm has used for a predictive control method for the identification of water hammering problems in a pumping system with the help of simulations and experimental-based works. A linear regression algorithm has been used in this work to predict water hammering problems. The efficiency of the algorithm is almost 90% compared to other ML algorithms. Through a Vib Sensor app-based device at different pressures and flow rates, the velocity of the pumping system, a fluctuation between healthy and faulty conditions, and acceleration value at different times have been collected for experimental analysis. A fault created to analyze a water hammering problem in a pumping system by the sudden closing and opening of the valve. When the valve suddenly closed, the kinetic energy in the system changed to elastic resilience, which created a series of positive and negative wave vibrations in the pipe. The present work concentrates on the water hammering problem of centrifugal pumping AC drive systems. The problem is mainly a pressure surge that occurs in the fluid, due to sudden or forced stops of valves or changes in the direction and momentum of the fluid. Various experimental results based on ML tool and fast Fourier transformation (FFT) analysis are obtained with a Vib Sensor testbed set-up to prove that linear regression analysis is the less time-consuming algorithm for fault detection, irrespective of data size.

In this paper, we consider the stability and various dynamical behaviors of both discrete-time delta modulator ( &Delta, M) and adaptive &Delta, M. The stability constraints and conditions of &Delta, M and adaptive &Delta, M are derived following the theory of quasi-sliding mode. Furthermore, the periodic behaviors are explored for both the systems with steady-state inputs and certain parameter values. The results derived in this paper are validated using simulated examples which confirms the derived stability conditions and the existence of periodicity.

In remote locations such as villages, islands and hilly areas, there is a possibility of frequent power failures, voltage drops or power fluctuations due to grid-side faults. Grid-connected renewable energy systems or micro-grid systems are preferable for such remote locations to meet the local critical load requirements during grid-side failures. In renewable energy systems, solar photovoltaic (PV) power systems are accessible and hybrid PV-battery systems or energy storage systems (ESS) are more capable of providing uninterruptible power to the local critical loads during grid-side faults. This energy storage system also improves the system dynamics during power fluctuations. In present work, a PV-battery hybrid system with DC-side coupling is considered, and a power balancing control (PBC) is proposed to transfer the power to grid/load and the battery. In this system, a solar power conditioning system (PCS) acts as an interface across PV source, battery and the load/central grid. With the proposed PBC technique, the system can operate in following operational modes: (a) PCS can be able to work in grid-connected mode during regular operation; (b) PCS can be able to charge the batteries and (c) PCS can be able to operate in standalone mode during grid side faults and deliver power to the local loads. The proposed controls are explained, and the system response during transient and steady-state conditions is described. With the help of controller-in-loop simulation results, the proposed power balancing controls are validated, for both off-grid and on-grid conditions.

This paper proposes an $H_{\infty }$ robust state-feedback controller design for uncertain Takagi–Sugeno fuzzy systems using a nonmonotonic Lyapunov function. In the nonmonotonic approach, the monotonicity requirement of the Lyapunov function is relaxed by allowing it to increase locally. Based on the nonmonotonic Lyapunov function approach, sufficient conditions for the existence of a robust state-feedback $H_{\infty }$ controller that guarantees stability and a prescribed $H_{\infty }$ performance are given in terms of linear matrix inequalities. The proposed design technique is shown to be less conservative than the existing $k$ -samples variations of the Lyapunov function. The effectiveness of the proposed approach is further illustrated via numerical examples.

This paper deals with the problem of designing a controller for a class of discrete-time nonlinear systems which is represented by discrete-time polynomial fuzzy model. Most of the existing control...

Fault tolerant control of affine class of multi-input multi-output (MIMO) nonlinear systems has not received considerable attention of researchers compared to other class of nonlinear syste...

This brief proposes a novel adaptive two-level quantizer, which generates 1-b per sample and can be used for a class of industrial networked control systems (NCSs). The adaptive quantizer is introduced to automatically estimate the input of the quantizer using equivalent control-based sliding mode control. The stability condition of the proposed quantizer is derived analytically with the help of a sliding-mode analysis. The effectiveness of the proposed quantized NCS is illustrated experimentally by designing a quantized feedback controller to control the position of a dc motor, where signals with 1-b per sample are utilized to interconnect the controller with the plant. Simulation results from a laboratory prototype illustrate that the proposed quantizer with the feedback controller controls the system effectively, introduces less quantization noise, and minimizes the data rate.

Bidirectional Inductive power transfer (IPT) systems behave as high order resonant networks and hence are highly sensitive to changes in system parameters. Traditional PID controllers often fail to maintain satisfactory power regulation in the presence of parametric uncertainties. To overcome these problems, this paper proposes a robust controller which is designed using linear matrix inequality (LMI) techniques. The output sensitivity to parametric uncertainty is explored and a linear fractional transformation of the nominal model and its uncertainty is discussed to generate a standard configuration for μ-synthesis and LMI analysis. An H∞ controller is designed based on the structured singular value and LMI feasibility analysis with regard to uncertainties in the primary tuning capacitance, the primary and pickup inductors and the mutual inductance. Robust stability and robust performance of the system is studied through μ-synthesis and LMI feasibility analysis. Simulations and experiments are conducted to verify the power regulation performance of the proposed controller.

The classical method of perturb and observe (P&O) is mostly utilized because of it is simple technique, ease of implementation and low cost. Although, it has high oscillations around maximum power point (MPP) at steady state due to perturbation and challenge between step size and the convergence time. To avoid the drawbacks of classical P&O methods, this paper presents adaptive P&O using optimized proportional integral (PI) controller by particle swarm optimization (PSO) algorithm. To evaluate the proposed method, a PV system model is designed with different scenarios under various weather conditions. For each scenario, simulations are carried out and the results are compared with the other classical P&O MPPT methods. The results revealed that the proposed PSO-PI-P&O MPPT method improved the tracking performance, response to the fast changing weather conditions and also has less oscillation around MPP as compared to the classical P&O methods.

The present study designs a novel ΔΣ-based PID controller for controlling the rotor side converter (RSC) of a doubly-fed induction generator (DFIG) based wind energy conversion system (WECS). The proposed controller essentially uses ΔΣ modulators to represent the analogue signals in single-bit which is ideally suited for FPGA or application specific integrated circuit implementation and offers numerous advantages due to its inherent parallel nature. The performance of the controller is compared with various controllers including a conventional PID, Q and Dynamic Fuzzy-Q learning (DFQL) based intelligent controllers. The results of the simulation on WECS consists of 20 wind turbines and 20 DFIGs, illustrate that the ΔΣ based PID controller could perform better compared to conventional PID and Q-learning based controllers.

During the past decade, networked control systems (NCS) has emerged as a viable alternative to traditional control systems due to various advantages it offers which include a reduction in system wiring, increase of system agility etc. However, the performance of various existing controllers such as PID degrades in the networked environment due to the existence of random time-varying delay, packet-dropouts which may cause instability. The present study designs a neural network (NN) based controller for NCS and investigates its performance under random time-varying delay, packet-dropouts. The performance of this controller is compared with both the classical PID and ΔΣ-based PID controllers. The robustness of the NN based controllers in the networked environment is studied under different degree of parametric uncertainties considering an example of a DC servo mechanism. The results of the comparative investigation demonstrate that the performance of the NN based controller is superior compared to other controllers.

Among the total energy consumed by presently installed utilities, pumping systems contributes nearly 30% of them that are controlled through induction motor. The flow rate of centrifugal pump is directly proportional to the speed of induction motor. Induction motor based electric drives are a complex nonlinear system to control due to their varying nature of speed with respect to changes in load. Thus, controllers are required for the speed control and performance enhancement of the induction motors. In this paper, a comparison of various controllers is discussed for the flow rate control of the pumping system. Among all the conventional controllers the proportional integral derivative (PID) is the mostly preferred for induction motor speed control. However, high overshoot, fixed gain constants and sluggish response are the disadvantages of the PID controller. So, automatic gain tuned PI controllers (i.e., adaptive PI controllers) are introduced to overcome the drawbacks of the conventional PID controllers. Further advancements in the field of artificial intelligence lead to the development of fuzzy logic based controllers. These controllers are simple, compatible and can be modelled without detailed mathematical model of the system. Thus, they are gaining more popularity than other controllers. The rules and membership functions (MFs) are responsible for performance of fuzzy logic controllers are designed using trial and error method. The result comparison of all the controllers is presented and the performance of each controller is analyzed. From the observations, fuzzy logic controller provides better performance than the conventional controllers.

Filtering is an important research issue, particularly in signal processing applications, as it provides the means to estimate state information in the presence of disturbance and system uncertainties. This chapter develops robust H ∞ output feedback filtering for uncertain Takagi–Sugeno (T-S) fuzzy systems via linear matrix inequalities (LMIs). Our main focus is to adopt the idea of nonmonotonic approach to further reduce the conservatism and improve the performance of the H ∞ output feedback filtering. An illustrative example is given at the end of this chapter to show the feasibility and efficiency of the developed method.

A Takagi–Sugeno (T-S) fuzzy model of the nonlinear system is often constructed as a combination of linear models with nonlinear scalar membership functions. This motivates researchers to design filters and controllers for nonlinear systems represented by T-S fuzzy systems using the linear matrix inequalities (LMIs) framework. However, many issues related to using LMIs fuzzy control, like conservatism, are still not completely solved. This chapter uses a nonmonotonic Lyapunov function (NLF) to design robust H ∞ state feedback controller for uncertain T-S fuzzy systems. In the nonmonotonic approach, the monotonicity requirement of the Lyapunov function (LF) is relaxed by allowing it to increase locally but go to zero ultimately. Based on the NLF approach, sufficient conditions for the existence of a robust state feedback H ∞ controller that guarantees stability and a prescribed H ∞ performance are given in terms of LMI. The design technique is shown to be less conservative than the existing k -sample variations of LF.

Unlike the traditional analysis and synthesis approach of a switched system that requires a monotonic decrease of Lyapunov function (LF), this chapter investigates an N -step ahead LF approach. Such an approach allows a nonmonotonic behavior both at the switching instants and during the running time of each subsystem but guarantees an average decrease at every N sampling steps. The asymptotic stability criterion is improved as well as the capability of disturbance attenuation. By introducing a series of auxiliary variables the future knowledge of states and exogenous noises can be properly used to derive sufficient conditions for the existence of a robust H ∞ controller in the form of a set of numerical testable conditions. Note that N has a direct impact on the number of the inequality constraints. The essential difficulty is constructing an exponential damping law of the decreasing points of LF, i.e., finding the joint point between the switching interval and the predictive horizon. Moreover, the relationship between N -step time difference of LF and switching rate, i.e., the average dwell-time constraint, is thoroughly discussed. An ecology system is employed to demonstrate practical potentials of the presented design framework.

This chapter develops robust H ∞ output feedback control stabilization for uncertain Takagi–Sugeno (T-S) fuzzy systems via linear matrix inequalities (LMIs). To reduce the conservatism associated with a T-S fuzzy system, a new form of nonmonotonic Lyapunov functions (NLFs) is used. In the nonmonotonic approach, the monotonic decrease of the Lyapunov function (LF) is relaxed by enabling it to increase locally but vanish eventually. Based on the NLF approach, sufficient conditions for the existence of robust H ∞ output feedback control stabilization are derived. The design technique is shown to be less conservative than the existing nonmonotonic approach, namely, k -sample variations of LF. The effectiveness of the developed approach is further illustrated via numerical example.

In recent years, delta (Δ-M) and delta-sigma modulators (ΔΣ-M) are increasingly being used as efficient data converters due to numerous advantages they offer. This paper investigates various dynamical features of these modulators/systems (both in continuous and discrete time domain) and derives their stability conditions using the theory of sliding mode. The upper bound of the hitting time (step) has been estimated. The equivalent mode conditions, i.e. where the outputs of the modulators are equivalent to the inputs, are established. The results of the analysis are validated through simulations considering a numerical example.

This study proposes a robust dynamic output feedback controller design for a class of discrete-time non-linear systems described by Takagi–Sugeno (T–S) fuzzy models using a non-monotonic Lyapunov approach. In the non-monotonic Lyapunov approach, the monotonicity requirement of the standard Lyapunov approach is not required. Based on the non-monotonic Lyapunov approach, sufficient conditions for the existence of an output stabilising feedback controller for discrete T–S fuzzy systems with and without uncertainties are derived in terms of linear matrix inequalities. The proposed design significantly reduces the conservativeness of the existing output feedback controller designs. An numerical example is used to illustrate the effectiveness of the proposed design.

Bit stream (BS)-based feedback control systems often use a delta–sigma modulator ( $\Delta\Sigma$ -M) as a two-level dynamic quantizer to encode and decode feedback signals. The stability and performance of such systems are critically dependent on the selection of the quantizer step size. This paper derives the stability condition of a BS-based control system in terms of the quantizer step size using sliding mode analysis. It is proved that the quantized system is equivalent to the original system on the sliding manifold under ideal sliding. However, the presence of the quantizer in a $\Delta\Sigma$ -M introduces noise into the system that often degrades the performance of the overall system. This paper therefore determines the optimum quantizer gain, i.e., the upper and lower boundaries of the quantizer, which maintains the stability and reduces the quantization noise. BS-based proportional–integral–differential (BS-PID) controllers are designed using the proposed optimal dynamic quantizer and implemented using three different realizations. Simulation results show that the optimal quantizer significantly reduces the noise within the system bandwidth. The effectiveness of the BS-PID controller with the optimal quantizer is further demonstrated using the experimental prototype of a dc servomechanism by designing a BS-PID controller. The experimental results from a laboratory prototype illustrate that the BS-PID controller gives identical performance to a traditional PID controller and effectively controls the system while consuming less information rate (channel interfaces) and hardware resources.

In recent years, wireless power transfer systems have successfully been used in various industrial applications due to their contactless power transfer feature. However, these systems behave as higher order resonant networks and hence are highly sensitive to changes in system parameters. Traditional PID controllers often fail to maintain satisfactory power regulation in the presence of parametric uncertainties which include load and circuit parameter variations, variations in magnetic coupling between the primary and secondary coils. To overcome these problems, this paper designs a robust H ∞ output feedback controller for a bi-directional inductive power transfer system. The control design is carried out following Ricatti approach. Simulations are conducted to verify the power regulation performance of the proposed controller and it is compared with a classical PID controller. The results show that the H ∞ output feedback controller could successfully regulate the power in both directions in the presence of large uncertainties in various circuit parameters.

This paper proposes a Sigma-Delta Modulator (ΣΔ-M) based Proportional and Integral (PI) controller for bidirectional inductive power transfer (IPT) systems. The controller uses ΣΔ-Ms to convert analog or multi-bit digital signals into single-bit signals and is ideally suited to be implemented in field programmable gate arrays (FPGAs). Various functional blocks are designed to implement PI actions in single-bit environment. The performance of the proposed controller was compared with a conventional PI controller through simulations in Hardware in Loop (HIL) environment and has been shown to be similar to that of the convectional PI controller. However, the single bit feature of the proposed PI controller consumes significantly less hardware reources such as number of logic elements and simplifies wire routing and computational complexity due to absence of multipliers.

This paper proposes a single-bit ADC system based Proportional and Integral (PI) controller to regulate the output voltage of Capacitive Power Transfer (CPT) systems. A simple single-bit ADC system i.e., Single-Bit Modulator (SBM) is considered as an alternative to the commonly used multi-bit ADC systems. Unique features of employing SBM are 1) its ability to convert analog signals into single-bit signals and 2) its easy integrability in digital chips with linear variable differential transformers (LVDTs) such as FPGAs. A SBM based PI (SBM-PI) controller is designed which guarantees consumption of less hardware resources, latency and effectively regulates the output voltage to provide the desired power transfer efficiency. The performance of the proposed SBM-PI controller is compared to that of a conventional multi-bit PI controller and has been shown that both controllers give identical performance. However, the SBM-PI consumes significantly less hardware resources. The effectiveness of the proposed controller with SBM-PI is further demonstrated using the experimental prototype of CPT using 16 MHz ATmega8 microcontroller. The experimental results from a laboratory prototype illustrate that SBM-PI controller successfully regulates the output voltage of CPT to control the power flow.

This paper proposes a novel approach for data-compression using Delta-sigma modulator (ΔΣ-M) and applies it to design bit-stream based controllers. An adaptive scheme is introduced to automatically determine the upper and lower boundaries of the quantizer of the ΔΣ-M. The stability condition of the feedback control system with embedded ΔΣ-M is derived analytically based on sliding mode analysis. The effectiveness of the proposed controller is illustrated experimentally by designing hybrid bit-stream based feedback controller to control the position of a D.C. motor. Experimental results from a laboratory prototype illustrate that the adaptive ΔΣ-M with the feedback controller effectively controls the systems while consuming less significant channels interfaces between the measurement device and the controller.

The present paper proposes a Delta Sigma (ΔΣ) modulator based control to control linear systems. This control method processes bit stream signals to control physical systems and offers various advantages compared to traditional methods of controller implementation, which uses multi-bit processing. To evaluate the performance of the bit-stream controller in real-life control applications, a digital controller based on a delta operator is used as a benchmark to which the controller utilizing bit-stream technique is compared. The effectiveness of the proposed bit-stream controller is experimentally validated considering an example of a DC motor. The results of the experiment show that the technique utilizing bit-stream signals are more attractive as an alternative to processing of multi-bit digital signal. Although both controllers display a comparable performance in simulation and experiment, the controller utilizing bit-stream uses approximately 400 logic elements (LE) on an Altera Cyclone FPGA comparing to the conventional controller which costs 600 (LE) and 17 9-bit multipliers.