Controller Design Problem Research Articles

Adaptive fuzzy control of underwater vehicle manipulator system with dead-zone band input nonlinearities via fuzzy performance and disturbance observers

In this paper, an adaptive fuzzy control design problem is investigated for an underwater vehicle manipulator system (UVMS) based on a fuzzy performance observer (FPOB) and fuzzy disturbance observer (FDO). The UVMS is considered as a nonlinear system comprising model uncertainties, external disturbances and dead-zone band input nonlinearities. To mitigate the combined effects of the dead-zone and the hysteresis, a novel pre-deadzone compensator is proposed. Then, fuzzy logic systems (FLSs) with online adaptations are utilized to evaluate the unknown components of the inertia matrix, the Coriolis matrix and the damping matrix. In addition, a fuzzy performance observer is constructed whose errors are used to estimate the external disturbances. Further, an H∞ fuzzy control technique is developed to reduce the errors in estimating the external disturbance. Then, the stability and tracking performance of the closed-loop system are analyzed using the Lyapunov stability theory. It is shown that all signals of the closed-loop system are uniformly ultimately bounded. Finally, simulations are performed to demonstrate the effectiveness of the proposed control scheme in addressing the tracking control problem of the UVMS in presence of the dead-zone band and disturbances.

A capstone laboratory course on separations, reactions and control operations

This work describes current teaching methodologies applied in the Unit Operations Laboratories (UOL) at the National University of Colombia (UNAL) Bogota campus, with emphasis in the capstone course of Laboratory of Separations, Reactions and Control Operations (LSRCO). This class is carried out using a wide variety of pilot and bench scale equipment within a ∼ 1000 m2 laboratory facilities. The description of the course includes the context where it was developed, its goals and the intended student outcomes. Problem-based methodologies deployed during laboratory sessions are described, and required preparatory and final reporting materials together with examples of projects conceived and developed by students are described. The lasts are related to process control, separations, reaction engineering and entire process design problems. Additionally, course evaluation and grading scheme is presented including student surveys and final grades from recent semesters. Finally, tools, rubrics and results from the assessment of ABET’s student outcomes are summarized. Based upon the obtained results, it was observed that the working and evaluation methodologies have been well received by students, and besides improving technical competences, those have been effective to enhance their core skills and to promote the development of a research and entrepreneurial attitude.

Solution Set Augmentation for Knee Identification in Multiobjective Decision Analysis.

In multiobjective decision making, most knee identification algorithms implicitly assume that the given solutions are well distributed and can provide sufficient information for identifying knee solutions. However, this assumption may fail to hold when the number of objectives is large or when the shape of the Pareto front is complex. To address the above issues, we propose a knee-oriented solution augmentation (KSA) framework that converts the Pareto front into a multimodal auxiliary function whose basins correspond to the knee regions of the Pareto front. The auxiliary function is then approximated using a surrogate and its basins are identified by a peak detection method. Additional solutions are then generated in the detected basins in the objective space and mapped to the decision space with the help of an inverse model. These solutions are evaluated by the original objective functions and added to the given solution set. To assess the quality of the augmented solution set, a measurement is proposed for the verification of knee solutions when the true Pareto front is unknown. The effectiveness of KSA is verified on widely used benchmark problems and successfully applied to a hybrid electric vehicle controller design problem.

Learning-Based $H_\infty$ Path-Following Controller Design for Autonomous Ground Vehicles Subject to Stochastic Delays and Actuator Constraints

In order to decrease computation loads for path following control of autonomous ground vehicles (AGVs), in this article, we aim to design an output-feedback path following controller by using a learning-based least squares support vector machine (LS-SVM) model. The signal transmission delay, which would deteriorates the control performance, is considered as well. First, the LS-SVM model for vehicle path following system is trained. Then, the output-feedback controller subject to stochastic communication delay, which meets the stability condition, is designed for the LS-SVM model. The modeling error and bias terms of LS-SVM model are regarded as the disturbance term. In order to attenuate the effect of disturbance, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> controller is designed for the AGVs to track the target path. Grey wolf optimizer is employed to solve the controller design problem with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$H_\infty$</tex-math></inline-formula> performance and transform stability condition from bilinear matrix inequality to linear matrix inequality (LMI). Then, we employ efficient LMI toolbox to solve the LMI. To guarantee the effectiveness of proposed controller, characteristics of steering wheel in a hardware-in-loop platform are studied and rate of steering angle is regarded as the actuator constraints for designing controller. Experimental results based on the hardware-in-loop platform have verified the effectiveness of the proposed control strategy.

Robust stabilization for a class of complex production process systems based on multi-dimensional moving pattern

This paper studies robust stabilization problem and state feedback controller design problem for a class of complex production process systems by pattern class variable instead of state variable or output variable. Firstly, the maximum entropy clustering method is introduced and modeling method based on multi-dimensional moving pattern is given. Nonlinear state space models of systems with input-delay are established by using the trajectories of pattern class variable. Then sufficient conditions for robust stabilization of the system are obtained by Linear Matrix Inequality. In addition, a state feedback controller is designed based on this condition. Finally, the effectiveness of the methods is illustrated by taking the actual working conditions data as an example.

Direct Search Algorithm for Load Frequency Control of a Time-Delayed Electric Vehicle Aggregator

This article addresses the topic of frequency regulation of a single-area power system connected to an electric vehicle (EV) aggregator over a non-ideal communication network. It is considered that the command control action is received by the EV aggregator with constant delay and the power system includes uncertain parameters. Due to the presence of uncertainties and the delay term, the frequency regulation problem is non-convex and hard to solve. The present approaches in the literature convert the non-convex control design problem into a convex problem with a set of Linear Matrix Inequalities (LMIs), which is conservative and in many cases results infeasibility. In this paper, an innovative iterative algorithm, called direct search, is employed for the time-delayed system to design the unknown parameters of a pre-assumed controller. The controller choice is not limited and various controllers’ structures can be assumed. Without loss of generality, a proportional-integral (PI) controller is designed. The novel direct search algorithm can determine a feasible solution whenever at least one solution lays in the design space. Hence, by selecting a wide design space, we can anticipate that the PI controller guarantees closed-loop stability. Numerical simulations are carried out to demonstrate the performance of the developed controller compared to the state-of-the-art approach.

Adaptive Neural Control for Nonlinear MIMO Function Constraint Systems

Dear Editor, In this letter, a novel adaptive control design problem for uncertain nonlinear multi-input-multi-output (MIMO) systems with time-varying full state constraints is proposed, where the considered systems consist of various subsystems, and the states of each subsystem are interconnected tightly. It is universally acknowledged that in the existing researches with state constraints, system constraint bounds are always constants or time-varying functions. Different from previous methods, the constraint boundary of this letter is regarded as a special function of not only time but of state variables. In order to handle time-varying full state constraints, the tangent type time-varying barrier Lyapunov functions (tan-TVBLFs) are introduced. By combining neural networks (NNs) and backstepping technique, an intelligent controller is developed. Meanwhile, we introduce an even function to guarantee the feasibility of NN approximation of unknown functions over practical compact sets. The feasibility of the mentioned control strategy is certified through the simulation results.

Finite-time velocity-free adaptive neural constrained cooperative control of Euler–Lagrange systems

This paper addresses a new constrained control design problem to develop the trajectory-tracking specifications of the cooperative control of Euler–Lagrange systems with respect to the convergence rate and steady-state errors by constraining the limited bounds on the trajectory-tracking errors in the leader–follower formation control problem. A control design based on an asymmetric barrier Lyapunov function is proposed for the leader–follower formation control of Euler–Lagrange systems in the presence of unknown parameters and unmodeled dynamics that progresses to the infinity when its arguments attain to the predefined bounds. These constrained output states are considered in the leader–follower formation control problem to cope with the system restrictions such as limited sensing ranges. The Lyapunov stability is pursued to assure that all the signals of the closed-loop system are bounded and the leader–follower formation errors are finite-time semi-globally uniformly ultimately bounded. Finally, computer simulation results represent the impression of the newly proposed constrained leader–follower formation control for the Euler–Lagrange systems.

Adaptive neural self-triggered bipartite secure control for nonlinear MASs subject to DoS attacks

This paper studies the bipartite secure control design problem for nonlinear multi-agent systems (MASs) subject to denial-of-service (DoS) attacks over a signed digraph. By proposing an anti-attack control method, the nonlinear MASs can achieve the bipartite secure control goal in an insecure network and physical environment. In addition, to save communication resources, a novel distributed adaptive self-triggered control (ASTC) mechanism is proposed. Different from the traditional self-triggered control, the trigger interval can be dynamically adjusted according to the situation that the followers converge to the convex hull formed by the leaders, which makes the proposed control protocol based on ASTC able to balance the system performance and communication resources under DoS attacks through scheduling the inherent system resources. Furthermore, in order to overcome the problem of complexity explosion, a command filter is introduced into the design process to simplify the design process. The validity of our control scheme is demonstrated through a simulation example.

Disturbance observer–based neural adaptive fault-tolerant control for flexible air-breathing hypersonic vehicles with multiple model uncertainties

One of the critical problems for flexible vehicles is how to simultaneously address the multiple uncertainty compensation and flexible vibration suppression. This paper focuses on the smooth adaptive fault-tolerant control design problem of a two-layer framework for flexible air-breathing hypersonic vehicles subject to contingent actuator failures and multiple model uncertainties. The first layer provides a disturbance observer–based neural adaptive fault-tolerant controller overcoming actuator failures and multiple model uncertainties. The second layer relies on the tracking differentiator and filter combined with the controller seamlessly, generating smooth reference information, which is highly desirable for flexible vibration suppression. Then, the analysis by the Lyapunov theory strictly proves the uniform ultimately boundedness of all the control and filter state variables. Finally, the simulation results demonstrate the dominant tracking control performance of the proposed control method.

Analysis and design of control systems via parameter‐based approach

Analysis and design of control systems via parameter‐based approach

Stabilization of nonlinear fractional order faulty systems with time-varying delay

This paper focuses on the issue of stabilization of nonlinear fractional order time-delay systems in the presence of fault. A general class of nonlinear fractional order systems is considered in which fault causes variations in the system dynamic and actuators. Besides, time-varying delay is noticed in the system equations that is of high importance in control of real-life systems. In order to facilitate the problem of controller design for such systems, a precise method for modeling complex nonlinear systems, namely, Takagi–Sugeno fuzzy model, is adopted. Regarding a Caputo derivative–based Lyapunov–Krasovskii functional, new delay-dependent stabilization conditions are established in the form of linear matrix inequalities. Eventually, two examples including a truck–trailer and Lorenz system are simulated in order to evaluate the results of this research work.

Robust observer-based controller design for nonlinear parameter-varying systems with uncertainty and external disturbances

This article investigates the robust observer-based controller design problem for nonlinear parameter-varying systems subject to uncertainty and external disturbances. First, a novel augment vector is constructed, and an corresponding model of the resulting closed-loop system is obtained. Second, by applying the Lyapunov stability theory, a class of state-and-parameter-dependent robust asymptotic stability criteria is established, and the state-and-parameter-dependent sufficient conditions for the design of the robust observer-based controller are then acquired to guarantee the stability of the resulting closed-loop system, which can be effectively solved by sum-of-squares techniques. Different from the previous researches, the proposed control algorithm enables the state-and-parameter-dependent observer and the state-and-parameter-dependent controller design of the nonlinear parameter-varying systems to enjoy the advantage of separate design. The advantage can effectively reduce the computational complexity. Finally, simulation results demonstrate that the proposed robust observer-based controller shows improved performance in presence of uncertainty and external disturbances.

Fixed-Time Average Consensus of a Dynamic Event-Triggered Mechanism in a System of Multiple Underactuated Autonomous Underwater Vehicles Based on a Body Frame Spherical Coordinate System

This paper is concerned with the consensus of a system involving multiple underactuated autonomous underwater vehicles (AUVs). Combined with a dynamic event-triggered mechanism and a fixed-time stability theorem, the backstepping average consensus controllers are designed. Firstly, the new consensus control objective on the system for multiple underactuated AUVs in a body frame (BF) spherical coordinate system is proposed, and the tracking error kinematic equations are established based on the kinematic characteristics of the underactuated AUV. The fixed-time consensus controller is designed by the backstepping method, and the average consensus theorem is proposed to improve the Lyapunov function. Furthermore, the dynamic event-triggered mechanism is adopted to reduce the communication requirements and energy consumption. This is the first solution to the problem of a consensus controller design for a system of multiple underactuated AUVs. Finally, numerical simulation results demonstrate that the proposed method has superior effectiveness over alternatives.

Decoupled $dq$ Current Control of Grid-Tied Packed E-Cell Inverters in Vehicle-to-Grid Technologies

This article investigates a decoupled vector current control strategy for grid-tied single-phase nine-level Packed E-Cell (PEC) inverters for vehicle-to-grid (V2G) technologies. The control design is based on a loop shaping approach, where performance specifications such as desired closed-loop bandwidth, closed-loop stability, robustness to pure time-delays in control loops/process, and decoupling between direct ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$d$</tex-math></inline-formula> ) and quadrature ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$q$</tex-math></inline-formula> ) axis of control signals are specified in the frequency domain. The control design problem is formulated as a convex optimization problem whose solution results in a multivariable controller in the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$dq$</tex-math></inline-formula> framework. The effectiveness of the proposed control strategy in terms of robust stability, current tracking, and improved total harmonic distortion is evaluated by experimental and simulation results under several case studies. The results also show that the designed controller provides the desired transient response as well as decoupling between the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$dq$</tex-math></inline-formula> output currents.

Optimal Formation Control for Second-Order Multi-Agent Systems With Obstacle Avoidance

Dear Editor, The optimal formation control design problem is studied for a class of second-order multi-agent systems (MASs) with obstacle avoidance. Based on the actor-critic framework, an optimized formation controller is proposed by constructing a novel performance index function. Furthermore, the stability of MAS is proved by constructing the Lyapunov function. The simulation results are provided to depict the effectiveness of the proposed strategies.

An Event-Triggered Predefined Time Decentralized Output Feedback Fuzzy Adaptive Control Method for Interconnected Systems

This article investigates the event-triggered predefined time output feedback control design problem for nonlinear interconnected systems with nonstrict feedback control structures. Compared with the existing event-triggered output feedback control design schemes, the most significant contribution of this article is that the system stability time can be preset directly. Fuzzy logic systems (FLSs) and FLSs-based state observer deal with unknown nonlinear dynamics and unmeasured states. Combining with dynamic surface control technology and event-triggered mechanism based on switching threshold strategy, an event-triggered predefined time decentralized output feedback control method is proposed, in which a predefined time filter is designed to solve the computational complexity problem. In addition, the algebraic loop problem and control singular problem are also solved, respectively, by applying the property of fuzzy basis function and L’Hospital’s rule. Utilizing the predefined time Lyapunov stability theory, the system stability analysis is given. Finally, the effectiveness and practicability of the proposed control method are verified by practical system simulation cases.

ℋ2 reset controller design for linear systems using piecewise quadratic Lyapunov functions

SummaryThis study presents reset controller design conditions for multiple‐input and multiple‐output (MIMO) linear systems in terms of linear matrix inequalities (LMIs). The design conditions were developed using a piecewise quadratic Lyapunov function (PWQLF), leading to less conservative conditions than using a common Lyapunov function. Achieving LMI relaxation of the PWQLF‐based reset controller design conditions for MIMO linear systems is challenging because (1) dividing the flow set of the reset condition is highly complex, (2) equality constraints, which make the PWQLF continuous on the boundaries between adjacent flow sets, prevent the use of congruence transformation in matrix inequalities, and (3) indefiniteness of the matrices for regional constraints also makes it difficult to apply standard LMI relaxation techniques. To overcome these difficulties, this study introduces a two‐dimensional projection of the plant's output measurements and reset controller's states to construct a reset condition, allowing the PWQLF to be tractable in MIMO linear systems. Then, a new stability analysis condition is derived using the elimination lemma, overcoming the challenges in LMI relaxation of the controller design attributed to the equality constraints and indefinite matrices. An LMI‐based reset controller design condition is then proposed based on the proposed stability analysis. To account for transient behavior, tracking reset controller design problem is addressed. A numerical example is provided to demonstrate the effectiveness of the proposed method.

Prescribed Performance Back-Stepping Tracking Control for a Class of High-Order Nonlinear Systems via a Disturbance Observer.

Due to the widespread presence of disturbances in practical engineering and widespread applications of high-order systems, this paper first pays attention to a class of high-order strict-feedback nonlinear systems subject to bounded disturbance and investigates the prescribed performance tracking control and anti-disturbance control problems. A novel composite control protocol using the technique of a disturbance observer-prescribed performance control-is designed using the back-stepping method. The disturbance observer is introduced for estimating and compensating for unknown disturbances in each step, and the prescribed performance specifications guarantee both transient and steady-state performance of the tracking error to improve the control performance and result in better disturbance rejection. Moreover, the technique of adding a power integrator is modified to tackle controller design problems for the high-order systems. The Lyapunov function method is utilized for rigorous stability analysis. It is revealed that while the control performance completely remains in the prescribed bound, all states in the closed-loop system are input-to-state stable, and the tracking error and the disturbances estimating error asymptotically converge to zero simultaneously. Then, the feasibility and effectiveness of the proposed control protocol are verified by a simulation result.

Robust nonlinear observer-based controller design for one-sided Lipschitz switched systems with time-varying delays

The core objective of this paper is to investigate the problem of robust nonlinear observer-based controller design for one-sided Lipschitz (OLS) switched systems. This work considers nonlinear switched systems with norm-bounded uncertainties, time-varying delays, and external disturbances. By selecting appropriate Lyapunov-Krasovskii functions and applying the OSL condition together with the quadratic inner boundedness property, we drive certain necessary and sufficient conditions for the observer-based control of the underlying system that assure the exponential convergence of the system states, the observer states, and the error states to zero, in respect of linear matrix inequalities via average dwell-time approach. The devised scheme offers necessary robustness against L2-norm bounded perturbations. In the end, the proposed scheme has been validated a suitable practical example.