Dynamic Feedback Control Research Articles

Disturbance-Observer-Based Feedback Linearization Control for Stabilization and Accurate Voltage Tracking of a DC–DC Boost Converter

The nonminimum-phase property of the dc–dc boost converter can create difficulties in designing a stable, robust, and fast control for the output voltage. In this article, these difficulties are reduced by modifying the state model of the boost converter in such a way that it behaves like a minimum-phase system. More specifically, the control input entering the state equation for the output voltage is treated as an unknown disturbance to make the relative degree of the system equal the system’s order. As a result, the modified model does not exhibit zero dynamics, so that it can be treated as a minimum-phase system for the control design. The modified model is, then, used to derive a dynamic compensator for the output voltage regulation. More explicitly, the dynamic compensator is designed based on combining linearizing feedback control with a disturbance observer. The latter is employed to compensate for model uncertainties and unknown load with a view to ensure asymptotic regulation under the composite controller. The asymptotic regulation is achieved due to the integral action property characterizing the disturbance observer. More interestingly, after simple algebraic manipulation, it turns out that the composite controller reduces to a dynamic state feedback control plus an antiwindup scheme to mitigate the effect of control saturation during transients. The performance of the proposed controller is verified by experimental tests. The experimental results demonstrate the ability of the proposed controller to achieve good transient and steady-state performances.

Distributed robust group output synchronization control for heterogeneous uncertain linear multi-agent systems

This paper investigates the distributed robust group output synchronization problem of heterogeneous uncertain linear leader-follower multi-agent systems (MASs), whose followers have nonidentical and parameter uncertain dynamics. To achieve cooperative tracking with multiple targets, a new group synchronization framework based upon the output regulation technique is established. In the underlying directed communication topology, all nonidentical followers are divided into several subgroups. Meanwhile, each subgroup has its output tracking objective generated by an autonomous exosystem which is seen as the leader of each subgroup. Since not all followers can access their exosystems directly, the distributed exosystem observer based on the algebraic Riccati inequality (ARI) is designed to obtain the information of exosystems. Moreover, to compensate for parameter uncertainties for different group topologies, the p-copy internal model is synthesized into distributed control laws, i.e., dynamic state feedback control protocol under an acyclic directed graph and dynamic output feedback control protocol under a general directed graph. It is shown that group synchronization can be respectively achieved with these controllers under acyclic and general partitions regardless of parameter uncertainties. Finally, some examples are provided to verify the validity of the analytic results.

Hybridization of battery and ultracapacitor for electric vehicle application with dynamic energy management and non-linear state feedback controller

• Proposed a dynamic energy management system for hybrid sources in an electric vehicle. • Buck-boost H-bridge converters are introduced for bidirectional power flow control. • System non-linearities are addressed using a nonlinear state feedback controller. • The proposed system accurately delivers instantaneous vehicle speed and torque. This paper describes a methodology to control a multi-source battery-capacitor hybrid EV incorporating a dynamic power splitting strategy. Considering the requirement for precise speed control characteristics of the EV and the non-linear behavior of traction motor with system disturbances, a non-linear state feedback controller (NLSFC) with a disturbance observer is suggested as the speed control technique for the EV traction motor. To interface a parallel configured multi-source system, a non-inverted buck-boost H-bridge is proposed as the source side converter for effective recovery of the braking energy. Detailed control design for traction motor and converter is also presented for efficient control of EV. Besides, an adaptive energy management strategy considering power profile and dynamic source characteristics is incorporated into the overall control system. The simulation results from various case studies indicate that the proposed system can follow the required vehicle speed and torque despite the sudden change in EV load torque. Furthermore, the comparative analysis between NLSFC and PI controller shows improvement with steady-state error reduction from 0.43 to 0.0014 and peak overshoot drop from 12.07% to 3.51% during acceleration of the system when proposed NLSFC is adopted. The proposed solutions will be implemented in a prototype EV system in the future.

Observer-based feedback stabilization of a reaction-diffusion equation with variable coefficients and boundary input delay

Abstract In this paper, we consider the stabilization issues of a reaction-diffusion equation with variable coefficients and boundary input delay. At first, we design an observer based on the system output to estimate the state of the system. Due to the present of time delay in control, we design a dynamic feedback controller based on the state information of observer, that is called the integral-type controller. By selecting appropriate kernel functions, we prove that the closed-loop system is exponentially stable. Herein, our approach mainly is based on the idea of ‘feedback equivalence’. By some equivalence transformations, we establish connection between the closed-loop system and a stable system.

Insight into the hierarchical control governing leg stiffness during the stance phase of running

Leg stiffness plays a key role in the storage and release of elastic energy during stance. However, the extent to which a runner is able to reuse stored energy remains a limiting factor in determining their running effectiveness. In this study, ten habitual rearfoot strikers and ten habitual forefoot strikers were asked to run on a treadmill in three footwear conditions: traditional, neutral, and minimal running shoes. We examined the effect of habitual foot strike pattern and footwear on leg stiffness control within three task-relevant phases of stance (i.e. touch-down, loading, unloading). Control was quantified using stride-to-stride leg stiffness time-series and the coefficient of variability and detrended fluctuation analysis (DFA). The results are interpreted within a theoretical framework that blends dynamic systems theory and optimal feedback control. Results indicate that leg stiffness control is tightly regulated by an active control process during the loading period of stance. In contrast, the touch-down and unloading phases are driven mostly by passive allometric control mechanisms. The effect of footwear on leg stiffness control was inconclusive due to inconsistent trends across three shoe types. However, stiffness control was affected by landing technique. Habitual rearfoot strike runners have reduced DFA values during the touch-down and unloading phases. These sub-phases are associated with an allometric control process and suggests that rearfoot strike runners express a reduction in system complexity for leg stiffness control and hence, a less adaptable system.

Decentralized adaptive output feedback dynamic surface control for stochastic nonstrict‐feedback interconnected nonlinear systems with actuator failures and input quantization via command filter

AbstractIn this article, a new decentralized adaptive neural output feedback control scheme based on first‐order command filter is proposed for stochastic nonstrict‐feedback interconnected systems with prescribed performance, input quantization, actuator failures and unmodeled dynamics. The unknown smooth functions are eliminated by using the radial basis function neural networks. The immeasurable states in the system are estimated using the decentralized K‐filters, unmodeled dynamics is processed using dynamic signal, and the hyperbolic tangent function is applied to the construction of the prescribed performance function. The hysteretic quantizer and actuator failure are denoted in the form of linearization, and a smoothing function is introduced to compensate for the effects of quantization and bounded stuck faults. Based on the dynamic surface control (DSC) method and using the properties of Gaussian function to deal with stochastic nonstrict‐feedback interconnected systems, the first‐order command filter is used to replace the first‐order filter in the traditional DSC to eliminate the influence of filtering error on the systems, and an error compensation signal is introduced at the recursive each step of the design to construct a new error dynamic surface, which simplifies the derivation process and the design of the controller. Finally, the Lyapunov method is used to prove that all the signals in the whole controlled system are semiglobally uniformly ultimately bounded in probability and the tracking error is within the time‐varying constraint. The effectiveness of the proposed decentralized adaptive control method is verified by a numerical simulation and an example simulation.

Dynamic Event-triggered Quantitative Feedback Control for Switched Affine Systems

Dynamic Event-triggered Quantitative Feedback Control for Switched Affine Systems

The Design of an Anti-Synchronization Control Algorithm for a 4D Laser System

When studying the control problems of nonlinear systems, there are always uncertainties and disturbances. The existence of this phenomenon will increase the error in production engineering and reduce work efficiency. In order to reduce the nonlinear asymmetric control, the control method of a laser hyperchaotic system is designed in this paper. The system is a complex number system, with remarkable nonlinear characteristics. The system is divided into two parts by calculating the state transformation matrix, which shows that the system can realize simultaneous synchronization and anti-synchronization. Firstly, in the ideal case, the stabilization, synchronization, and anti-synchronization of the system are studied by using the dynamic gain feedback method, and a dynamic feedback controller is designed. Secondly, in the case of uncertainty and disturbance, a dynamic feedback control strategy based on uncertainty and disturbance estimator (UDE) is proposed. With the aim to solve the control problem of the system, the corresponding controller is designed to modify the system. Finally, through simulation and comparison, it is verified that the effect of this method is remarkable.

Complete Synchronization and Partial Anti-Synchronization of Complex Lü Chaotic Systems by the UDE-Based Control Method

The presence of uncertainty and disturbance can lead to asymmetric control of nonlinear systems, and this asymmetric control can lead to a decrease in the productivity of the engineered system. In order to improve the control speed of the improved nonlinear system, complete synchronization and partial anti-synchronization of complex Lü chaotic systems with uncertainty and disturbance are investigated in the present paper. First, a new UDE-based dynamic feedback control method is proposed for the complete synchronization problem of the system. The method unites the dynamic gain feedback control method and the uncertainty and perturbation estimator (UDE) control method, where the dynamic gain feedback controller is used to achieve asymptotic stability of the nominal system and the UDE controller is used to handle a given controlled system with uncertainty and disturbance. Second, for the partial desynchronization problem of this system, a new UDE-based linear-like feedback control method is proposed, which consists of two controllers: a linear-like feedback controller used to achieve the asymptotic stabilization of the nominal system and the other UDE controller is designed to handle the given controlled system with uncertainty and disturbance. Finally, numerical simulations are performed to verify the correctness and stability of the theoretical results.

Optimal output consensus of second‐order uncertain nonlinear systems on weight‐unbalanced directed networks

AbstractThis article investigates the distributed optimal output consensus problem of second‐order uncertain nonlinear multiagent systems over weight‐unbalanced directed networks. Under the standard assumption that local cost functions are strongly convex with globally Lipschitz gradients, a novel distributed dynamic state feedback controller is developed such that the outputs of all the agents reach the optimal solution to minimize the global cost function which is the sum of all the local cost functions. The controller design is based on a two‐layer strategy, where a distributed optimal coordinator and a reference‐tracking controller are proposed to address the challenges arising from unbalanced directed networks and uncertain nonlinear functions respectively. A key feature of the proposed controller is that the nonlinear functions containing the uncertainties and disturbances are not required to be globally Lipschitz. Furthermore, by exploiting adaptive control technique, no prior knowledge of the uncertainties or disturbances is required either. Two simulation examples are finally provided to illustrate the effectiveness of the proposed control scheme.

Robust cooperative output regulation of linear uncertain multi-agent systems by distributed event-triggered dynamic feedback control

In this paper, distributed state and output feedback control law based on the dynamic event-triggered mechanism are proposed to solve the robust cooperative output regulation problem for a class of general linear uncertain multi-agent systems (MASs) subject to external disturbances. The discrete-time control law proposed for each agent is equivalent to a discrete one and thus directly implementable in the digital platform. Our design can handle parametric uncertainties, reject external disturbances and track a dynamic leader while excluding the Zeno phenomenon by providing the existence of a lower bound for inter-event times of each agent, the efficiency of which is illustrated by a numerical example.

Adaptive friction compensation for a class of mechanical systems based on LuGre model

AbstractThis paper deals with the problem of friction compensation for a class of uncertain mechanical systems based on LuGre model. The objective is to develop control laws such that the position variable of the system tracks a periodic desired signal or a constant desired signal. Since the friction behavior of the system with periodic desired signals is largely different from that of the system with constant desired signals, two different adaptive control methods are presented for the two cases, respectively. For the case of periodic desired signals, an adaptive repetitive learning control method is presented, and for the case of constant desired signals, an adaptive dynamic state feedback control method is presented. Both the control laws can guarantee that all the signals in the closed loop system are bounded and the tracking errors converge to zero. Several numerical simulations are carried out to show effectiveness of the proposed control algorithms.

Design and Analysis of a Voltage-Mode Non-Linear Control of a Non-Minimum-Phase Positive Output Elementary Luo Converter

The positive output elementary Luo (POEL) converter is a fourth-order DC–DC converter having highly non-linear dynamic characteristics. In this paper, a new dynamic output voltage feedback controller is proposed to achieve output voltage regulation of the POEL converter. In contrast to the state-of-the-art current-mode controllers for the high-order boost converters, the proposed control strategy uses only the output voltage state variable for feedback purposes. This eliminates the need for the inductor current sensor to reduce the cost and complexity of implementation. The controller design is accompanied by a strong theoretical foundation and detailed stability analyses to obtain some insight into the controlled system. The performance of the proposed controller is then compared with a multi-loop hysteresis-based sliding-mode controller (SMC) to achieve the output voltage-regulation of the same POEL converter. The schemes are compared concerning ease of implementation, in particular, the number of state variables and current sensors required for implementation and the closed-loop dynamic performance. Experimental results illustrating the features of both controllers in the presence of input reference and load changes are presented.

Regional Eigenvalue Assignment in Cooperative Linear Output Regulation

The contribution of this paper is a regional eigenvalue assignment method for cooperative output regulation of heterogeneous linear multiagent systems with an internal model-based distributed dynamic state feedback control law. The proposed method offers an agent-wise local approach to synthesize distributed control gains while assigning, for example, the minimal decay rate and the minimal damping ratio of the overall closed-loop system as desired. Numerical examples demonstrate the efficacy of the proposed method by assigning the eigenvalues of a large-scale system to different regions, specifically, disks, shifted half-planes, and conic sectors.

Dissipative stabilization of linear input delay systems via dynamical state feedback controllers: an optimization based approach

In this note, we present an effective solution to the stabilization of linear input delay systems subject to dissipative constraints while all the effect of input delay is compensated by a controller with novel structure. The method is inspired by the recent development in the mathematical treatment of distributed delays and predictor controllers, which are critical for the derivation of the solution. An important conceptual innovation is the use of a parameterized dynamical state feedback controller (DSFC), where the dimension of the controller equals the dimension of the control input. A sufficient condition for the existence of a dissipative DSFC is obtained via the Krasovskii functional approach, where the condition includes a bilinear matrix inequality (BMI). To solve the BMI, we apply an inner convex approximation algorithm which can be initialized based on an explicit construction of a predictor controller gain. The proposed DSFC can be considered as an extension of the classical predictor controller, thereby capable of compensating all the effects of the pointwise input delay while satisfying dissipative constraints. A numerical example is given to illustrate the effectiveness of our proposed methodology.

Constrained Continuous-Time Dynamics for Linear Model Predictive Control

In this paper, we consider the use of a continuous-time dynamic feedback controller for linear model predictive control (MPC). The controller incorporates both integral-action and anti-windup conditioning and ensures optimality through online emulation of the solution trajectory of an underlying MPC problem. We establish closed-loop stability when the controller is interconnected with an open-loop stable linear-time invariant system using the passivity argument and the invariance principle. We include a computational example to illustrate the effectiveness and the constraint handling capability of the proposed controller.

Adaptive Asymptotic Control of Stochastic Systems With State Delay and Unknown Control Directions

For a class of stochastic nonlinear systems (SNSs) with state delay and unknown control directions (UCDs), the global asymptotic regulation problem is investigated in this brief. Based on the key Lyapunov-Krasovskii functional (KLF), a dynamic feedback control strategy is designed to solve the time delay and UCDs problems. The proposed dynamic compensator guarantees the global asymptotic convergence of the systems state in probability at the origin and the global boundedness of the closed-loop system (TCLS) in probability. Finally, an example is given to verify the effectiveness of the developed scheme.

Exponential stabilization of the problem of transmission of wave equation with linear dynamical feedback control

<p style='text-indent:20px;'>In this paper, we address exponential stabilization of transmission problem of the wave equation with linear dynamical feedback control. Using the classical energy method and multiplier technique, we prove that the energy of system exponentially decays.</p>

강화학습 기반 강인 제어를 위한 과거 입출력 정보 필요성 탐구

Reinforcement learning yields a feedback controller that achieves specific control goal (which is often translated as a reward function). However, it often suffers from the Sim2Real gap, and domain randomization is known to be a method to overcome this issue. In this paper, we demonstrate necessity of input/outpu history when domain randomization is employed by a formal example and a simulation result. This is equivalent to the necessity of dynamic feedback controller in terms of control theory.

Memory dynamic output feedback controller based on asynchronous event‐triggered robust H‐infinity control for nonlinear ICPSs under data injection attacks

AbstractAiming at reducing the influence caused by data injection attacks, an asynchronous event‐triggered robust H‐infinity control (AERHC) is proposed for the stability of nonlinear ICPSs suffering from data injection attacks. A robust H‐infinity memory dynamic feedback control technique is designed to guarantee asymptotic stability of the closed‐loop system under a Lyapunov functional and the robust stability criterion. Furthermore, a memory dynamic feedback controller which has five controller gains different from each other for mitigating the conservative of nonlinear ICPSs and for resisting data injection attacks in ICPSs. Meanwhile, an asynchronous event‐triggered strategy is adopted to reduce the data communication frequency among nonlinear ICPSs components, and it effectively handle the influence of coupling problem between the measurement channel and the control channel. Finally, simulation tests are conducted by using MATLAB to control the robustness of the motor angle position of electromechanical system by using AERHC, which verify that the correctness and effectiveness of the proposed method.