Control‐oriented modeling and robust nonlinear triple‐step controller design for an air‐feed system for polymer electrolyte membrane fuel cells

The efficient operation of polymer electrolyte membrane fuel cells (PEMFCs) significantly relies on the reliable control of air‐feed system. The core control objective in air‐feed system is to track a pre‐defined reference of the oxygen excess ratio to avoid oxygen starvation and stack damage. In this paper, we focus on the modeling of the air‐feed system in a PEMFC and the robust nonlinear controller design for the oxygen excess ratio tracking control. To facilitate the subsequent nonlinear controller design, a specific affine‐like, second‐order, control‐oriented model of oxygen excess ratio dynamic behavior is developed, and the modeling uncertainty is estimated and compensated by using an extended state observer (ESO). The control‐oriented model is verified via a high‐fidelity plant model. A nonlinear controller for oxygen excess ratio tracking control is proposed based on the triple‐step technique which is robust against the system disturbances. The tuning rule of the controller parameters is discussed in the scheme of the linear system. Finally, simulations are conducted to demonstrate the effectiveness and advantages of the proposed controller under variant operating conditions compared with baseline controllers.     

Design of a Sliding Mode Controller with Fuzzy Rules for a 4-DoF Service Robot

In this study, a novel control strategy that combines a fuzzy system and the sliding mode controller is proposed for improving stability and achieving high-accuracy control in service robots. Based on the kinematic and dynamic models of a 4-degrees of freedom manipulator, and the observed tracking error using a low-cost inertial sensor, the proposed fuzzy sliding mode controller (FSMC(IMU)) is designed to generate appropriate torques at robot joints. The FSMC(IMU) controller parameters are adjusted through a fuzzy rule that determines the state of the system. The error in trajectory tracking is reduced through this. The gain value K can be finely adjusted by fuzzy control by observing the degree of vibration after entering the sliding mode surface. The larger the observed vibration value, the faster the fuzzy controller follows the given input trajectory by selecting a smaller gain value K and reducing jitter due to the sliding mode control’s discontinuous switch characteristics. When the degree of error is small, it achieves faster and more accurate control performance than when the observer is not used. The stability of the FSMC(IMU) system is verified via disturbance experiments. The experimental data are compared with the conventional sliding mode controller and proportional-derivative control. The experimental results demonstrate that the proposed FSMC(IMU) controller is stable, fast, and highly accurate in controlling service robots.

     

Reciprocal convex approach to output‐feedback control of uncertain LPV systems with fast‐varying input delay

Robust control of parameter‐dependent input delay linear parameter‐varying (LPV) systems via gain‐scheduled dynamic output‐feedback control is considered in this paper. The controller is designed to provide disturbance rejection in the context of the induced ‐norm or the norm of the closed‐loop system in the presence of uncertainty and disturbances. A reciprocally convex approach is employed to bound the Lyapunov‐Krasovskii functional derivative and extract sufficient conditions for the controller characterization in terms of linear matrix inequalities (LMIs). The approach does not require the rate of the delay to be bounded, hence encompasses a broader family of input‐delay LPV systems with fast‐varying delays. The method is then applied to the air‐fuel ratio (AFR) control in spark ignition (SI) engines where the delay and the plant parameters are functions of the engine speed and mass air flow. The objectives are to track the commanded AFR signal and to optimize the performance of the three‐way catalytic converter (TWC) through the precise AFR control and oxygen level regulation, resulting in improved fuel efficiency and reduced emissions. The designed AFR controller seeks to provide canister purge disturbance rejection over the full operating envelope of the SI engine in the presence of uncertainties. Closed‐loop simulation results are presented to validate the controller performance and robustness while meeting AFR tracking and disturbance rejection requirements.     

Integral sliding mode control for Euler‐Lagrange systems with input saturation

This paper investigates the robust control for the Euler‐Lagrange (EL) system with input saturation by using the integral sliding mode control and adaptive control. An integral sliding mode surface that is suitable for solving the problem of the input constraint is given based on the saturation function. By using the integral sliding mode surface, two robust antisaturation controllers are designed for the EL system with external disturbances. The first controller can deal with the external disturbances with known bounds, whereas the second one can compensate the external disturbances with unknown bounds by using the adaptive control. Finally, the effectiveness of the proposed controllers is demonstrated by strict theoretical analysis and numerical simulations.     

Hybrid Adaptive Type‐2 Fuzzy Tracking Control of Chaotic Oscillation Damping of Power Systems

In this paper a novel hybrid direct/indirect adaptive fuzzy neural network (FNN) moving sliding mode tracking controller for chaotic oscillation damping of power systems is developed. The proposed approach is established by providing a tradeoff between the indirect and direct FNN controllers. It is equipped with a novel moving sliding surface (MSS) to enhance the robustness of the controller against the present system uncertainties and unknown disturbances. The major contribution of the paper arises from the new simple tuning idea of the sliding surface slope and intercept of the MSS. This study is novel because the approach adopted tunes the sliding surface slope and intercept of MSS using two simple rules simultaneously. One advantage of the proposed approach is that the restriction of knowing the bounds of uncertainties is also removed due to the adaptive mechanism. Moreover, the stability of the control system is also presented. The proposed controller structure is successfully employed to damp the complicated chaotic oscillations of an interconnected power system, when such oscillations can be made by load perturbation of a power system working on its stability edges. Comparative simulation results are presented, which confirm that the proposed hybrid adaptive type‐2 fuzzy tracking controller shows superior tracking performance.     

Nonlinear fractional‐order power system stabilizer for multi‐machine power systems based on sliding mode technique

This paper presents two novel nonlinear fractional‐order sliding mode controllers for power angle response improvement of multi‐machine power systems. First, a nonlinear block control is used to handle nonlinearities of the interconnected power system. In the second step, a decentralized fractional‐order sliding mode controller with a nonlinear sliding manifold is designed. Practical stability is achieved under the assumption that the upper bound of the fractional derivative of perturbations and interactions are known. However, when an unknown transient perturbation occurs in the system, it makes the evaluation of perturbation and interconnection upper bound troublesome. In the next step, an adaptive‐fuzzy approximator is applied to fix the mentioned problem. The fuzzy approximator uses adjacent generators relative speed as own inputs, which is known as semi‐decentralized control strategy. For both cases, the stability of the closed‐loop system is analyzed by the fractional‐order stability theorems. Simulation results for a three‐machine power system with two types of faults are illustrated to show the performance of the proposed robust controllers versus the conventional sliding mode. Additionally, the fractional parameter effects on the system transient response and the excitation voltage amplitude and chattering are demonstrated in the absence of the fuzzy approximator. Finally, the suggested controller is combined with a simple voltage regulator in order to keep the system synchronism and restrain the terminal voltage variations at the same time. Copyright © 2014 John Wiley & Sons, Ltd.     

A parameter-varying filtered PID strategy for air–fuel ratio control of spark ignition engines

In this paper, a new synthesis method is presented to control air–fuel ratio (AFR) in spark ignition engines to maximize the fuel economy while minimizing exhaust emissions. The major challenge in the control of AFR is the time-varying delay in the control loop which restricts the application of conventional control techniques. In this paper, the time-varying delay in the system dynamics is first approximated by Padé approximation to render the system dynamics into non-minimum phase characteristics with time-varying parameters. Application of parameter-varying dynamic compensators is invoked to retrieve unstable internal dynamics. The associated error dynamics is then utilized to construct a filtered PID controller combined with a parameter-varying dynamic compensator to track the desired AFR command using the feedback from the universal exhaust gas oxygen sensor. The proposed method achieves desired dynamic properties independent of the matched disturbances. It also accommodates the unmatched perturbations due to the dynamic compensator features. The results of applying the proposed method to experimental numerical data demonstrate the closed-loop system stability and performance against time-varying delay, canister purge disturbances and measurement noise for both port fuel injection engines and lean-burn engines.     

On input‐to‐state stability of rigid‐body attitude control with quaternion representation

The concept of input‐to‐state stability (ISS) is important in robust control, as the state of an ISS system subject to disturbances can be stably regulated to a small region around the origin. In this study, the ISS property of the rigid‐body attitude system with quaternion representation is thoroughly investigated. It has been known that the closed loop with continuous controllers is not ISS with respect to arbitrarily small external disturbances. To deal with this problem, hybrid proportional‐derivative controllers with hysteresis are proposed to render the attitude system ISS. The controller is far from new, but it is investigated in a new aspect. To illustrate the applications of the results about ISS, 2 new robust hybrid controllers are designed. In the case of large bounded time‐varying disturbances, the hybrid proportional‐derivative controller is designed to incorporate a saturated high‐gain feedback term, and arbitrarily small ultimate bounds of the state can be obtained; in the case of constant disturbances, a hybrid adaptive controller is proposed, which is robust against small estimate error of inertia matrix. Finally, simulations are conducted to illustrate the effectiveness of the proposed control strategies.     

Improving asynchronous motor speed and flux loop control by using hybrid fuzzy-SMC controllers

This paper presents a new method combining sliding mode control (SMC) and fuzzy logic control (FLC) to enhance the robustness and performance for a class of non-linear control systems. This fuzzy sliding mode control (FSMC) is developed for application in the area for controlling the speed and flux loops of asynchronous motors. The proposed control law can solve those problems associated with the conventional control by sliding mode control, such as high current, flux and torque chattering, variable switching frequency and variation of parameters, in which a robust fuzzy logic controller replaces the discontinuous part of the classical sliding mode control law. Simulation results of the proposed FSMC technique on the speed and flux rotor controllers present good dynamic and steady-state performances compared to the classical SMC in terms of reduction of the torque chattering, quick dynamic torque response and robustness to disturbance and variation of parameters.     

Variable‐Structure Control with Complementarity‐Inputs for a Lean‐Burn IC Engine of a Series Hybrid Vehicle

This paper presents a robust controller for an internal combustion (IC) engine, as the first stage of a project to develop a hybrid light urban vehicle, running on ethanol in lean burn. In particular, this work focuses on the design of a sliding mode control for an IC engine of a series hybrid power train. The controller must allow for optimal speed regulation and high fuel efficiency. To attain the latter, a complementary operation mode is proposed for the system inputs. Simulation results are presented and discussed showing the viability and advantages of the control strategy employed.     

天然气发动机智能模糊混合控制器的研究

提出了基于智能模糊的混合控制算法，对其结构原理和算法进行了详细介绍。仿真结果表明，该算法对非线性时变系统有较好的适应性和鲁棒性，并将该算法应用于增压天然气发动机闭环控制中，取得了满意的效果。     

Finite‐time attitude‐tracking control for rigid spacecraft with actuator failures and saturation constraints

In this article, the problem of finite‐time attitude‐tracking control for rigid spacecraft is addressed. Uncertainties caused by external disturbances, unknown inertial matrix, actuator failures, and saturation constraints are tackled simultaneously. First, a smooth function that is more qualified to approximate the standard saturation characteristics is presented to deal with the actuator saturation constraints. Second, a fast nonsingular terminal sliding mode (FNTSM) manifold is constructed as a foundation of controllers design. By incorporating the fuzzy logic system into FNTSM technique, a less demanding solution of coping with model uncertainties is provided because the requirement of a prior knowledge of unknown inertial parameters and external disturbances in many existing achievements is removed. To reduce the number of parameters to be estimated, the norm approximation approach is exploited. Subsequently, an antichattering attitude controller is presented such that all the tracking errors converge into arbitrary small domains around the origin in finite time. The result is further extended to obtain a fault‐tolerant controller against completely failed actuators. Finally, numerical simulation is conducted to verify the effectiveness of the proposed control scheme and comparison with relevant literature demonstrates its high performance. Furthermore, an experiment for the large satellite Hubble Space Telescope is carried out to validate the practical feasibility.     

Quasi sliding mode‐based single input fuzzy self‐tuning decoupled fuzzy PI control for robot manipulators with uncertainty

This paper presents a robust adaptive control strategy for robot manipulators, based on the coupling of the fuzzy logic control with the so‐called sliding mode control (SMC) approach. The motivation for using SMC in robotics mainly relies on its appreciable features. However, the drawbacks of the conventional SMC, such as chattering effect and required a priori knowledge of the bounds of uncertainties can be destructive. In this paper, these problems are suitably circumvented by adopting a reduced rule base single input fuzzy self tuning decoupled fuzzy proportional integral sliding mode control approach. In this new approach a decoupled fuzzy proportional integral control is used and a reduced rule base single input fuzzy self‐tuning controller as a supervisory fuzzy system is added to adaptively tune the output control gain of the decoupled fuzzy proportional integral control. Moreover, it is proved that the fuzzy control surface of the single‐input fuzzy rule base is very close to the input/output relation of a straight line. Therefore, a varying output gain decoupled fuzzy proportional integral sliding mode control approach using an approximate line equation is then proposed. The stability of the system is guaranteed in the sense of the Lyapunov theorem. Simulations using the dynamic model of a 3DOF planar manipulator with uncertainties show the effectiveness of the approach in high speed trajectory tracking problems. The simulation results that are compared with the results of conventional SMC indicate that the control performance of the robot system is satisfactory and the proposed approach can achieve favorable tracking performance, and it is robust with regard to uncertainties and disturbances. Copyright © 2011 John Wiley & Sons, Ltd.     

FUZZY SLIDING MODE CONTROLLER DESIGN: INDIRECT ADAPTIVE APPROACH

In this paper, using the concept of sliding mode control SMC, a fuzzy sliding mode controller FSMC, which is synthesized by linguistic control rules, is proposed. Two sets of fuzzy rule bases are utilized to represent the controlled system. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of SMC, are changed according to adaptive law. In particular, only one adaptive factor is characterized to adapt the membership functions instead of several ones in conventional adaptive approaches. Under this design scheme, we not only maintain the distribution of membership functions over state space but also reduce considerably computing time. The proposed indirect adaptive FSMC is synthesized through the following stages. First, we construct the fuzzy rule bases according to the common sense of SMC to describe the model of the controlled system, and define the fuzzy sets whose membership functions are equally distributed in state space. Then, the derived adaptive law is used to adjust the membership functions of the THEN-part to approximate an equivalent control without knowing the mathematical model of the controlled system. Third, a hitting control is developed to guarantee the stability of the control system. Finally, we smooth the hitting control via proposed heuristic control rules. We apply this FSMC to controlling a nonlinear inverted pendulum system to confirm the validity of the proposed approach.     

Passivity‐based sliding mode controller/observer for second‐order nonlinear systems

A passivity‐based sliding mode control for a class of second‐order nonlinear systems with matched disturbances is proposed in this paper. Firstly, a nonlinear sliding surface is designed using feedback passification, in which the passivity is employed to guarantee the closed‐loop system's stability. The passivity‐based controller comprising a discontinuous term guarantees globally asymptotical convergence to the sliding surface. A sliding mode‐based control law that satisfies the reaching and sliding condition is also developed. Moreover, the passivity‐based sliding mode observer is also developed to effectively estimate the system states. Compared with conventional sliding mode control, the proposed control scheme has a shorter reaching time; and hence, the system performance is less affected by disturbances, thus eliminating the need to increase the control input gain. Finally, simulation results demonstrate the validity of the proposed method.     

Adaptive fault‐tolerant spacecraft attitude control using a novel integral terminal sliding mode

The attitude tracking of a rigid spacecraft is approached in the presence of uncertain inertias, unknown disturbances, and sudden actuator faults. First, a novel integral terminal sliding mode (ITSM) is designed such that the sliding motion realizes the action of a quaternion‐based nonlinear proportional‐derivative controller. More precisely, on the ITSM, the attitude dynamics behave equivalently to an uncertainty‐free system, and finite‐time convergence of the tracking error is achieved almost globally. A basic ITSM controller is then designed to ensure the ITSM from onset when an upper bound on the system uncertainties is known. Further, to remove this requirement, adaptive techniques are employed to compensate for the uncertainties, and the resultant adaptive ITSM controller stabilizes the system states to a small neighborhood around the sliding surface in finite time. The proposed schemes avoid the singularity intrinsic to terminal sliding mode‐based controllers and the unwinding phenomenon associated with some quaternion‐based controllers. Numerical examples demonstrate the advantageous features of the proposed algorithm. Copyright © 2017 John Wiley & Sons, Ltd.     

Design of interval type-2 fuzzy sliding-mode controller

In this paper, an interval type-2 fuzzy sliding-mode controller (IT2FSMC) is proposed for linear and nonlinear systems. The proposed IT2FSMC is a combination of the interval type-2 fuzzy logic control (IT2FLC) and the sliding-mode control (SMC) which inherits the benefits of these two methods. The objective of the controller is to allow the system to move to the sliding surface and remain in on it so as to ensure the asymptotic stability of the closed-loop system. The Lyapunov stability method is adopted to verify the stability of the interval type-2 fuzzy sliding-mode controller system. The design procedure of the IT2FSMC is explored in detail. A typical second order linear interval system with 50% parameter variations, an inverted pendulum with variation of pole characteristics, and a Duffing forced oscillation with uncertainty and disturbance are adopted to illustrate the validity of the proposed method. The simulation results show that the IT2FSMC achieves the best tracking performance in comparison with the type-1 Fuzzy logic controller (T1FLC), the IT2FLC, and the type-1 fuzzy sliding-mode controller (T1FSMC).     

Continuous Finite‐Time Sliding Mode Control for Uncertain Nonlinear Systems with Applications to DC‐DC Buck Converters

This paper investigates the continuous finite‐time control problem of high‐order uncertain nonlinear systems with mismatched disturbances through the terminal sliding mode control method. By constructing a novel dynamic terminal sliding manifold based on the disturbance estimations of high‐order sliding mode observers, a continuous finite‐time terminal sliding mode control method is developed to counteract mismatched disturbances. To avoid discontinuous control action, the switching terms of a dynamic terminal sliding manifold are designed to appear only in the derivative term of the control variable. To validate its effectiveness, the proposed control method is applied to a DC‐DC buck converter system. The experimental results show the proposed method exhibits better control performance than a chattering free controller, such as mismatched disturbances rejection and smaller steady‐state fluctuations.     

Robust Tracking Control For A Wheeled Mobile Manipulator With Dual Arms Using Hybrid Sliding‐Mode Neural Network

In this paper, a robust tracking controller is proposed for the trajectory tracking problem of a dual‐arm wheeled mobile manipulator subject to some modeling uncertainties and external disturbances. Based on backstepping techniques, the design procedure is divided into two levels. In the kinematic level, the auxiliary velocity commands for each subsystem are first presented. A sliding‐mode equivalent controller, composed of neural network control, robust scheme and proportional control, is constructed in the dynamic level to deal with the dynamic effect. To deal with inadequate modeling and parameter uncertainties, the neural network controller is used to mimic the sliding‐mode equivalent control law; the robust controller is designed to compensate for the approximation error and to incorporate the system dynamics into the sliding manifold. The proportional controller is added to improve the system's transient performance, which may be degraded by the neural network's random initialization. All the parameter adjustment rules for the proposed controller are derived from the Lyapunov stability theory and e‐modification such that uniform ultimate boundedness (UUB) can be assured. A comparative simulation study with different controllers is included to illustrate the effectiveness of the proposed method.     

An intelligent fuzzy sliding mode control system with application on precision table positioning

In this paper, an intelligent fuzzy sliding mode control system, which cooperates with a new learning approach called modulus genetic algorithm, is proposed. Furthermore, it is applied to a high precision table positioning system for verifying its practicability. Fuzzy sliding mode controller (FSMC) is a special type of fuzzy controller with certain attractive advantages than the conventional fuzzy controller. The learning and stability issues of FSMC are discussed in the paper. Furthermore, to overcome the encoding/decoding procedure that leads to considerable numeric errors in conventional genetic algorithm, this paper proposes a new algorithm called modulus genetic algorithm (MGA). The MGA uses the modulus operation such that the encoding/decoding procedure is not necessary. It has the following advantages: (1) the evolution can be speeded up; (2) the numeric truncation error can be avoided; (3) the precision of solution can be increased. For verifying the practicability of the proposed approach, the MGA‐based FSMC is applied to design a position controller for a high precision table. The experimental results show the proposed approach can achieve submicro positioning precision. © 2001 John Wiley & Sons, Inc.