Optimized sliding mode current controller for power converters with non-minimum phase nature

This paper proposes a unified method to design an optimized type of the hysteresis modulation-based sliding mode current controller for non-minimum phase power converters in continuous conduction mode. The traditional sliding mode controlled converters have a slow transient voltage response at heavy loads, a large overshoot at light loads and during abrupt output resistance variations. To solve these problems, an optimized feedback control scheme is used according to the output resistance to adjust the coefficients of the controller. The basic idea of this controller is to suggest a new way for reduction of the sensitivity function amplitude of the closed loop system. The presented approach is developed for three basic DC/DC converters; i.e. boost, buck-boost and quadratic boost converters. Generally, the certain advantages of the suggested control approach are: (i) a fast transient response can be achieved in heavy load conditions, (ii) the voltage overshoot can be effectively reduced during load variations; (iii) the transient voltage overshoot can be eliminated in light load conditions; (iv) the closed loop control sensitivity can be reduced and therefore, the performance specification of a control system can be improved compared with the conventional sliding mode current control. To show the reliability of the suggested control scheme, simulations and experimental results for the derived systems are developed. Several conditions are performed to confirm the effectiveness of the proposed controller.     

Fault tolerant control for partial loss of control authority in aircraft using piecewise affine slab models

In this paper, a new fault tolerant control methodology is proposed for partial loss of control authority in aircraft using piecewise affine (PWA) slab models while minimizing an upper bound on a quadratic cost function. The proposed controller stabilizes and satisfies performance bounds for both the nominal and faulty systems. The controller design criteria are cast as a set of Linear Matrix Inequalities (LMIs) that can be solved efficiently. The new technique is illustrated in a numerical example for the Beechcraft 99 aircraft model.     

H∞ guaranteed cost control for uncertain Markovian jump systems with mode-dependent distributed delays and input delays

This paper investigates the H_∞ guaranteed cost control problem for mode-dependent time-delay jump systems with norm-bounded uncertain parameters. Both distributed delays and input delays appear in the system model. Based on a matrix inequality, a sufficient condition for the existence of robust H_∞ guaranteed cost controller is derived, which stabilizes the considered system and guarantees that both the H_∞ performance level and a cost function have upper bounds for all admissible uncertainties. By the cone complementary linearization approach, the desired state-feedback controller can be constructed. A numerical example is provided to show the effectiveness of the proposed theoretical results.     

Predictor-based optimal robust guaranteed cost control for uncertain nonlinear systems with completely tracking errors constraint

In this paper, a novel composite controller is proposed to achieve the prescribed performance of completely tracking errors for a class of uncertain nonlinear systems. The proposed controller contains a feedforward controller and a feedback controller. The feedforward controller is constructed by incorporating the prescribed performance function (PPF) and a state predictor into the neural dynamic surface approach to guarantee the transient and steady-state responses of completely tracking errors within prescribed boundaries. Different from the traditional adaptive laws which are commonly updated by the system tracking error, the state predictor uses the prediction error to update the neural network (NN) weights such that a smooth and fast approximation for the unknown nonlinearity can be obtained without incurring high-frequency oscillations. Since the uncertainties existing in the system may influence the prescribed performance of tracking error and the estimation accuracy of NN, an optimal robust guaranteed cost control (ORGCC) is designed as the feedback controller to make the closed-loop system robustly stable and further guarantee that the system cost function is not more than a specified upper bound. The stabilities of the whole closed-loop control system is certified by the Lyapunov theory. Simulation and experimental results based on a servomechanism are conducted to demonstrate the effectiveness of the proposed method.     

Resilient observer-based sliding mode control of connected vehicles with denial-of-service attacks

This paper investigates an observer-based sliding mode control (SMC)) for connected vehicles under denial-of-service attacks. The attacks refer to interrupting communication channels between vehicles. Firstly, a reduced order observer is used to estimate the relative acceleration between neighbor vehicles, and a switching communication topology is introduced to model the attack. Then, an observer based sliding mode controller is proposed to achieve desired stability performance. Moreover, a quadratic cost performance is also defined and the cost upper bound is proved. Some sufficient conditions are provided such that the connected vehicles can achieve robust tracking performance, and input-to-state string stability is guaranteed under zero initial errors. Finally, numerical simulations are given to illustrate the validity of the designed controller.     

A modified PID controller (PIIσβD)

The purpose of this study is to modify the traditional PID controller in order to improve its performance (stability and tracking) by changing the length of integration interval. The performance of the traditional PID controller was improved by changing the length of integration interval to make the most of the returns of the PID and PI_σD controllers. The asymptotic stability domain, in terms of the feedback gains, is derived for systems of second order using the modified controller which will be identified as PII_σ^βD. Comparing this controller with the traditional PID controller and PI_σD controller proposed in [1], it proves that it is more accurate and more stable. For illustration and comparison, two examples have been simulated to evaluate the performance of the modified controller. All simulation results indicate that the modified controller is better than the traditional PID controller and the PI_σD controller from the accuracy and stability point of view.     

Tabu search algorithm based PID controller tuning for desired system specifications

This paper presents a tuning approach based on a tabu search algorithm (TSA) to obtain the optimal proportional-integral-derivative (PID) controller parameters in order to achieve a desired transient response. TSA is used to determine the main parameters of the PID controller. The performance of the PID controlled system is examined by considering the characteristics of the step response of the plant. Simulation results demonstrate that the tabu algorithm based approach is one of the useful methods for PID controller tuning, and using by the presented method, performance of the controlled system can be significantly improved according to the given control specifications.     

Pole-placement in discrete systems by using single and multirate sampling

This paper deals with closed-loop pole-placement in discrete, linear systems under single and multirate sampling. The technique is extendable to hybrid systems, i.e. those involving both continuous and discrete substates. The sampling rates for the state, input and output components are used as a controller design technique to achieve closed-loop pole-placement since the controller, which is also discrete or hybrid in the general case, can be periodically reparametrized, the main useful effect of which being the availability of multiple design gains whose number and value are under the designer's choice. The key design factor in the multirate sampling design is that once the closed-loop running sampling period (i.e. that defining the closed-loop dynamics and thus the controller reparametrization periodicity) has been chosen, one can use freedom in the choice of smaller sampling periods for the various plant input and output components as well as for those of the controller state. All these sampling periods are chosen as submultiples of the closed-loop running sampling period.     

Resilient control based on disturbance observer for nonlinear singular stochastic hybrid system with partly unknown Markovian jump parameters

In this paper, the composite anti-disturbance resilient control is considered for nonlinear singular stochastic hybrid system with partly unknown Markovian jump parameters under multiple disturbances. Three kinds of disturbances are included in the studied system. One is generated by an external system and it enters the hybrid system from the channel of the control input. The other one is stochastic white noise. And the third one is the external unknown time-varying disturbance and it is supposed to be H₂ norm bounded. By combining the disturbance-observer-based-control scheme, H_∞ control technique and resilient control method, a composite anti-disturbance resilient controller is constructed to attenuate and eliminate the affection of these disturbances, and ensures the whole closed-loop system regular, impulse free and stochastically stable with the corresponding control performance. Then, some sufficient conditions and the gains of the controller and observer are obtained by using Lyapunov function method and the linear matrix inequalities (LMIs) technique. Finally, two numerical examples are given to show the effectiveness of presented method.     

Optimal controller for uncertain stochastic polynomial systems

This paper presents the optimal quadratic-Gaussian controller for uncertain stochastic polynomial systems with linear control input and a quadratic criterion over linear observations. The optimal closed-form controller equations are obtained using the separation principle, whose applicability to the considered problem is substantiated. As intermediate results, the paper gives closed-form solutions of the optimal regulator and controller problems for stochastic polynomial systems with linear control input and a quadratic criterion. Performance of the obtained optimal controller is verified in the illustrative example against the conventional quadratic-Gaussian controller that is optimal for stochastic polynomial systems with known parameters. Simulation graphs demonstrating overall performance and computational accuracy of the designed optimal controller are included.     

Performance-oriented parallel distributed compensation

The main idea of the original parallel distributed compensation (PDC) method is to partition the dynamics of a nonlinear system into a number of linear subsystems, design a number of state feedback gains for each linear subsystem, and finally generate the overall state feedback gain by fuzzy blending of such gains. A new modification to the original PDC method is proposed here, so that, besides the stability issue, the closed-loop performance of the system can be considered at the design stage. For this purpose, the state feedback gains are not considered constant through the linearized subsystems, rather, based on some prescribed performance criteria, several feedback gains are associated to every subsystem, and the final gain for every subsystem is obtained by fuzzy blending of such gains. The advantage is that, for example, a faster response can be obtained, for a given bound on the control input. Asymptotic stability of the closed loop system is also guaranteed by using the Lyapunov method. To illustrate the effectiveness of the new method, control of a flexible joint robot (FJR) is investigated and superiority of the designed controller over other existing methods is demonstrated.     

Reliable H∞ control on saturated linear Markov jump system with uncertain transition rates and asynchronous jumped actuator failure

This paper is concerned with reliable H_∞?control for saturated linear Markov jump systems with uncertain transition rates and asynchronous jumped actuator failure. The actuator failures are assumed to occur randomly under the Markov process with a different jumping mode from the system jumping mode. In considering the mixed-mode-dependent state feedback controller, both H_∞ stochastic stability analysis for closed-loop system with completely accessible transition rates and uncertain transition rates are investigated. Moreover, based on the obtained stability conditions, the H_∞?control problems are investigated, and the controller gains can be obtained by solving a convex optimization problem with minimizing H_∞ performance as objective and linear matrix inequalities (LMIs) as constraints. The problem of designing state feedback controllers such that the estimate of the domain of attraction is enlarged is also formulated and solved as an optimization problem with LMI constraints. Simulation results are presented to illustrate the effectiveness of the proposed results.     

Experimental validation of a continuous-time MCSI algorithm with bounded adaptive gains

Model reference adaptive control algorithms with minimal controller synthesis have proven to be an effective solution to tame the behaviour of linear systems subject to unknown or time-varying parameters, unmodelled dynamics and disturbances. However, a major drawback of the technique is that the adaptive control gains might exhibit an unbounded behaviour when facing bounded disturbances. Recently, a minimal controller synthesis algorithm with an integral part and either parameter projection or σ-modification strategies was proposed to guarantee boundedness of the adaptive gains. In this article, these controllers are experimentally validated for the first time by using an electro-mechanical system subject to significant rapidly varying disturbances and parametric uncertainty. Experimental results confirm the effectiveness of the modified minimal controller synthesis methods to keep the adaptive control gains bounded while providing, at the same time, tracking performances similar to that of the original algorithm.     

Event-triggered control for active vehicle suspension systems with network-induced delays

This paper presents a novel event-triggered H_∞ static output-feedback control for active vehicle suspension systems with network-induced delays. The proposed control schema introduces an event-triggering mechanism in the suspension system such that the communication resources can be significantly saved. By applying some improved slack inequalities and an augmented Lyapunov–Krasovskii functional (LKF), a new design condition expressed in the form of linear matrix inequalities (LMIs) is developed to derive the desired event-triggered controller. The obtained algorithm is then employed to solve the static output-feedback control gain. Compared with the traditional sampled-data H_∞ control scheme, the proposed controller is able to provide an enhanced disturbance attenuation level while saving the control cost. Finally, comparative simulation results are provided to show the performance of the proposed event-triggered controller.     

Delayed proportional-integral control for offshore steel jacket platforms

This paper is concerned with the problem of delayed proportional-integral control of an offshore platform subject to self-excited nonlinear hydrodynamic force. By using current and distributed delayed states, a delayed proportional-integral controller is designed to stabilize the offshore platform. Under such a controller, the closed-loop system of the offshore platform is modeled as a nonlinear system with discrete and distributed delays, which allows us to employ the Lyapnov–Krasovskii functional method to analyze its asymptotic stability. Since an affine Wirtinger-based inequality is exploited to estimate the derivative of the Lyapunov–Krasovskii functional, a new stability criterion for the closed-loop system is derived, based on which, suitable control gains can be designed provided that a set of linear matrix inequalities are feasible. It is found through simulation results that the proposed control scheme can improve the control performance remarkably. Moreover, (i) compared with the existing delay-free controllers, the proposed controller can reduce the required control force and the oscillation amplitudes of the platform significantly; and (ii) compared with several delayed controllers, the proposed controller requires less control cost.     

H∞ control of singular time-delay systems via discretized Lyapunov functional

This paper addresses the problem of robust H_∞ control for uncertain continuous time singular systems with state delays. A new singular-type complete quadratic Lyapunov-Krasovskii functional (LKF) is introduced, which combines with the discretization LKF method to synthesis problems. An improved bounded real lemma (BRL) is presented to ensure the system to be regular, impulse free and stable with H_∞ performance condition. Based on the BRL, a memoryless state feedback controller is designed via linear matrix inequalities (LMIs), which greatly reduces the disturbance attenuation level. Numerical examples are given to illustrate improvements over some existing results.     

Robust H∞ control of an observer-based repetitive-control system

This paper concerns the problem of designing a robust observer-based modified repetitive-control system with a prescribed H_∞ disturbance rejection level for a class of strictly proper linear plants with unknown aperiodic disturbances and time-varying structural uncertainties. A correction to the amount of the delay in the repetitive controller is introduced that leads to a significant improvement in tracking performance. An integrated performance index is defined to quantify the overall effect of rejecting the aperiodic disturbances and tracking the periodic reference input. A Lyapunov functional with two tuning parameters is used to derive a linear-matrix-inequality based robust stability condition for the system with a prescribed disturbance-rejection bound. Combining the performance indices, an optimization algorithm that searches for the best combination of state-observer gain and the feedback control gains is developed. A numerical example illustrates the design procedure and demonstrates the effectiveness of the method.     

Design of a H∞ model reference tracking control for interconnected nonlinear systems by decentralized dynamic output-feedback

This study investigates the problem of robust tracking control for interconnected nonlinear systems affected by uncertainties and external disturbances. The designed H_∞ dynamic output-feedback model reference tracking controller is parameterized in terms of linear matrix inequalities (LMIs), which is formulated within a convex optimization problem readily implementable. The resolution of such a problem, guarantying not only the quadratic stability but also a prescribed performance level of the resulting closed-loop system, enables to calculate concurrently the robust decentralized control and observation gain matrices. The established LMI conditions are computed in a single-step resolution to obtain all the controller/observer parameters and therefore to overcome the problem of iterative algorithm based on a multi-stage resolution leading in most cases to conservative and suboptimal solutions. Numerical simulations on diverse applications ranging from a numerical academic example to coupled inverted double pendulums and a 3-strongly interconnected machine power system are provided to corroborate the merit of the proposed control scheme.     

Finite-time guaranteed cost control for uncertain delayed switched nonlinear stochastic systems

This paper studies the finite-time guaranteed cost control problem for switched nonlinear stochastic systems with parameter uncertainties and time-varying delays. By choosing a model-dependent and delay-dependent Lyapunov-Krasovskii functional, applying the average dwell time approach and the Gronwall inequality, some novel sufficient conditions are derived to ensure that the switched nonlinear stochastic closed-loop system is finite-time stochastically stable and an upper bound is given on the performance index. The obtained nonlinear matrix is transformed into a linear matrix form, and then the feedback controller gains of the switched nonlinear stochastic systems with time-varying delay are obtained. Finally, two simulation examples are designed to verify the effectiveness of the suggested approach.     

TS fuzzy robust L1 control for nonlinear systems with persistent bounded disturbances

In this paper, a novel technique for Takagi–Sugeno (TS) model-based robust L₁ controller design of nonlinear systems is proposed. Two synthesis methods based on quadratic and non-quadratic Lyapunov functions are considered. To design the robust stabilizing controller, a new approach for deriving sufficient conditions associated with the L₁ performance criterion in terms of strict linear matrix inequality is proposed. This novel technique results in less pre-chosen scalar design variables and calculation burden. Furthermore, deriving the controller synthesis conditions via a non-quadratic Lyapunov function (NQLF) relaxes the obtained conditions. Therefore, the proposed approaches not only efficiently minimize the effect of persistent bounded disturbance, but also are applicable for wider classes of TS systems. Furthermore, some new lemmas are proposed to facilitate strict LMI formulation and to provide more degrees of freedom. Finally, several numerical and practical examples are presented to show the merits of this paper.