Practical Controller Design Research Articles

Adaptive robust disturbance rejection backstepping control of a novel friction electro-hydraulic load simulator

This paper introduces a novel frictional electro-hydraulic load simulator that avoids the problem of force-motion coupling disturbances in traditional electro-hydraulic load simulators. An adaptive robust disturbance rejection backstepping control (ARDRBC) is proposed to address the challenges posed by parameter uncertainty, external disturbances, and unmodeled behavior, thereby enhancing the system’s tracking capability. A new adaptive rule has been designed to address the uncertainty of mechanical subsystems through virtual control adjustments. A sliding mode control scheme based on immersion and invariance has been integrated into the practical control design of hydraulic subsystem to address the neglected dynamics. The stability of the entire system was analyzed using the Lyapunov stability. Comparative experiments were conducted to confirm the practicality and robustness of the proposed method.

Robust Consensus Analysis in Fractional-Order Nonlinear Leader-Following Systems with Delays: Incorporating Practical Controller Design and Nonlinear Dynamics

This article investigates the resilient-based consensus analysis of fractional-order nonlinear leader-following systems with distributed and input lags. To enhance the practicality of the controller design, an incorporation of a disturbance term is proposed. Our modeling framework provides a more precise and flexible approach that considers the memory and heredity aspects of agent dynamics through the utilization of fractional calculus. Furthermore, the leader and follower equations of the system incorporate nonlinear functions to explore the resulting changes. The leader-following system is expressed by a weighted graph, which can be either undirected or directed. Analyzed using algebraic graph theory and the fractional-order Razumikhin technique, the case of leader-following consensus is presented algebraically. To increase robustness in multi-agent systems, input and distributive delays are used to accommodate communication delays and replicate real-time varying environments. This study lays the groundwork for developing control methods that are more robust and flexible in complex networked systems. It does so by advancing our understanding and practical application of fractional-order multi-agent systems. Additionally, experiments were conducted to show the effectiveness of the design in achieving consensus within the system.

Practical Event-Triggered Finite-Time Second-Order Sliding Mode Controller Design.

This article proposes a novel event-triggered second-order sliding mode (SOSM) control algorithm using the small-gain theorems. The developed algorithm has global event property in aspects of the triggering time intervals. First, an SOSM controller is designed related to the sampling error of states, and it is proved that the closed-loop system is finite-time input-to-state stable (FTISS) with the sampling error via utilizing the small-gain theorems. Second, combined with the constructed SOSM controller, a new triggering mechanism is proposed depending on the sampling error by designing the appropriate FTISS gain condition. Third, the practical finite-time stability of the closed-loop system is verified. It is shown that the minimum triggering time interval is always a positive value in the whole state space. Finally, the simulation results demonstrate the effectiveness of the developed control method.

Adaptive Fuzzy Nonsingular Fixed-Time Control for a Class of MIMO Nonstrict Feedback System

This paper studies the adaptive fuzzy practical fixed-time control design for MIMO nonlinear systems with non-strict feedback. The extant practical fixed-time stability criterion cannot obtain an accurate settling time upper bound or exists some constraints on parameters that lead to a conservative result. Thus a novel practical fixed-time stability criterion is proved in this paper to resolve the above problem and can obtain the precise value of the settling time upper bound. The control singular issue caused by the fixed-time stability criterion form is avoided by introducing adding power integration method. Compared with other approaches, this method is easy to apply in control design, and it's convenient to prove its effectiveness. And fuzzy logic system is adopted to approximate the unknown nonlinear items. Combining the proposed fixed-time stability criterion, traditional backstepping scheme, and fuzzy logic system, an adaptive practical fixed-time controller is proposed. The simulation of the actual physical system demonstrates the effectiveness of the controller and practical fixed-time criterion.

A Split-Source Self-Heater for Automotive Batteries Based on Traction Drive Reconfiguration

At cold climates, internally preheating batteries are essential and promising to alleviate the performance degradation of electric vehicles because of its rapid heating speed and uniform temperature distribution. To implement onboard internal battery heating, the integrated self-heater is developed to utilize traction motor drive reconfiguration, thereby eliminating extra expensive high-power converters and bulky passive components. However, previous integrated self-heaters introduce excessive voltage stress on dc-link capacitors, arousing a serious concern on the system reliability and safety. In this article, a split-source self-heater (SSSH) is proposed to reconfigure the battery pack as two series-connected sources, where the heating energy can be alternately exchanged via traction motor windings with reduced capacitor voltage stress. The theoretical model and operation principle of the proposed SSSH are deduced for practical controller design and suppression of annoying noises and vibrations. Based on the model, a supertwisting controller is developed to adjust the heating current and cell voltage regardless of nonlinear uncertainties during self-heating. The downscaled experiments verify that the proposed SSSH can preheat automotive batteries with 4.27 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> C/min heating speed and 0.24% state of charge/ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">o</sup> C energy consumption rate. The induced torque ripple is reduced by 90%, and the capacitor voltage never exceeds the nominal value during self-heating.

Practical robust control design and experimental validation of modular jointed cooperative robots with inequality constraints

In this paper, a new practical dynamic robust control approach for cooperative robots with inequality constraints is proposed. The controller can compensate errors caused by uncertainties and external disturbances. The inequality constraint is eliminated by choosing proper boundary function and using state transformation. In this way, the controlled output is guaranteed within the desired range. The Lyapunov minimax method is used to prove that the controller can guarantee the uniform boundedness and uniform ultimate boundedness and stability of the robot system. Experimental verifications are carried out on a 2-DOF cooperative robot experimental platform with joint modules. The experimental platform is equipped with a rapid prototyping controller system (CSPACE). Numerical simulation and experimental verification results show that the proposed practical robust controller has significant advantages of trajectory tracking performance and security for cooperative robots with inequality constraints.

Input‐to‐state practical stability analysis and controller design of switched affine systems: An observer‐based approach

AbstractThis paper addresses the problems of the input‐to‐state practical stability (ISPS) analysis and output feedback controller design for switched affine systems (SASs) subject to external disturbances. First, a switched affine observer is developed to estimate unmeasurable states. Then by combining the sampled‐data control approach, a less conservative mode‐dependent dynamic event‐triggered mechanism (ETM) is established. The proposed dynamic ETM cannot only avoid Zeno behavior but also reduce the network transmission burden effectively. Further, based on time‐dependent Lyapunov‐Krasovskii functional and state‐dependent switching laws, a set of feasible ISPS conditions are presented in the LMI forms by means of singular value decomposition. The designed switching law depends upon the sampled‐data information of the estimated state and gets rid of the chattering phenomenon. Finally, an application example of the DC‐DC flyback converter is given to verify the efficacy of the proposed algorithm.

An Interval Approach for Robust Parameterization of Controllers for Electric Drives

Uncertain models, e.g., due to component variations and measurement errors during system identification, in combination with the desire to be able to provide guarantees regarding system performances a priori, represent major challenges for users when designing controllers on the basis of models. The aim of this publication is to mitigate this obstacle in the design. For this purpose, criteria of classical control engineering are combined with interval arithmetic in general and the SIVIA algorithm in particular. Thereby, the approach is valid for linear dead time systems. The algorithm evaluates performance criteria for closed interval-bounded sets of parameter values in a single iteration. When overestimation prevents a definite result, the size of the parameter set is recursively reduced by bisecting the evaluated set. The application of the methodology to the controller design for an electromechanical linear actuator shows that the approach not only contributes to theory but can also simplify the practical controller design, especially in the area of electric drives.

Practical implementable controller design with guaranteed asymptotic stability for nonlinear systems

Establishing the stability of model predictive control formulation is challenging. Using a combination of the terminal cost term and the terminal inequality constraint i.e. terminal set results in nominal asymptotic stability. Larger terminal set results in shorter minimum prediction horizon length required for feasibility from identical initial condition. Current work presents novel linear quadratic Gaussian regulator based approach for the terminal set characterization for the discrete time model predictive control scheme. Proposed approach provides large degrees of freedom in the form of additive matrices as tuning parameters for enlarging the terminal sets as against a single scalar for the literature approaches. Efficacy of the novel approach is demonstrated using a benchmark four tank system. It was observed that the average computation time reduces to significantly when compared to the approaches from the literature for identical initial conditions. This makes the controller design suitable for practical implementation.

Practical Nonlinear Model Predictive Controller Design for Trajectory Tracking of Unmanned Vehicles

The trajectory tracking issue of unmanned vehicles has attracted much attention recently, with the rapid development and implementation of sensing, communication, and computing technologies. This paper proposes a nonlinear model predictive controller (NMPC) for the trajectory tracking application of an unmanned vehicle (UV). First, a two-degree-of-freedom (2-DOF) kinematics model of this UV is used to derive the desirable controller with two control variables as forward velocity and yaw angle. Next, the one-step Euler method is employed to establish the nonlinear prediction model, then a nonlinear optimization objective function is formulated to minimize the tracking errors of forward velocity and yaw angle from a preset time-varying reference road. Finally, the effectiveness of the proposed NMPC scheme is assessed under two different driving scenarios via MATLAB simulations. The simulation results confirm that the proposed NMPC scheme reveals better control accuracy and computational efficiency than the standard MPC controller under two different prescribed roads. Moreover, an outdoor field test is conducted to verify the performance of the proposed NMPC scheme, and the results show that the proposed NMPC can be applied to the real vehicle and can improve the tracking accuracy and the driving stability of trajectory tracking.

Guidance and control methodologies for marine vehicles: A survey

Offshore mechatronics systems engineering has recently received high attentions in various sectors such as energy, transportation, etc. Specifically, offshore robotic vehicles have become challenging topics in terms of design, guidance, control and maintenance aspects. Based on these reasons, in this article, some recent developments on the guidance and control methodologies for marine robotic vehicles are surveyed. The application-oriented methodologies under consideration mainly include fuzzy-based control design approach, neural network-based control design scheme, dynamic surface control strategy, feedback control technique as well as sliding model control method, for instance. With the help of these methodologies, the developments on various guidance and robust control issues are reviewed in great detail. In practical engineering, guidance and control design problems are mainly addressed for the maneuvering, path following, trajectory tracking, formation control and consensus. In particular, the state of art of the solution to guidance and control issues for marine robotic vehicles under different control methodologies is addressed respectively. Finally, some latest research results in filtering and control design developments are introduced, some conclusions are drawn and several possible future research directions based on the latest results are pointed out.

Sliding mode control on receding horizon: Practical control design and application

Sliding mode control (SMC) is to keep the system to a stable differential manifold. Model predictive control (MPC) calculates the control input by solving an optimization problem on receding horizon. The method of receding horizon sliding control (RHSC) includes the predicted information into the SMC design by combining SMC and MPC. Considering the modeling error and measurement noise, there are model-mismatch and disturbance problems in control practice. This paper combines the demonstrated method of RHSC with a state-augmented Kalman filter addressing the model mismatch and disturbance problem. The proposed scheme has been applied to the air system of an advanced heavy-duty engine. The results have shown the capability of tracking the reference signal during a step-response test and the convergence rate to the target signal is 10% faster than MPC.

Data-Driven Iterative Trajectory Shaping for Precision Control of Flexible Feed Drives

With recent advances on material processing technologies, design requirements on modern manufacturing equipment are shifting toward achieving higher speed and accuracy rather than stiffness and load capacity. Motion systems used in additive or ultraprecision manufacturing equipment need to be designed to achieve greater dynamic positioning accuracy. As a result, feedforward (FF) control becomes an effective tool. This article presents a novel and practical FF controller design methodology to widen tracking bandwidth of precision motion systems suffering from structural dynamics and friction-induced disturbances. The proposed feedforward controller is designed to, first, compensate for the closed-loop servo dynamics to widen the command tracking bandwidth, second, mitigate unwanted vibrations, and third, compensate friction disturbance-induced positioning errors. The FF controller is structured in a trajectory prefilter form where the FF compensation signal is injected into the reference trajectory rather than torque command. This facilitates the FF controller to be applied conveniently without intervention with the servo controller. FF controller parameters are identified (tuned) automatically through machine in-the-loop-iterations. Parameter identification is posed as a convex optimization problem to realize safe and reliable auto-tuning. The proposed FF controller and its parameter tuning methodology are tested experimentally on an industrial scale multiaxis machine tool and its performance is validated.

Supervised-distributed control with joint performance and communication optimisation

This paper is concerned with the control of systems composed of multiple coupled subsystems. In such architectures, communication between different local controllers is desired in order to achieve a better overall control performance. Any resultant improvement in control performance needs, however, to be significant enough to warrant the additional design complexity and higher energy consumption and costs associated with introducing communication channels between controllers. A practical distributed control design aims, therefore, to achieve an acceptable balance between minimising the use of communication between controllers and maximising the system-wide performance. In this article, a new approach to the problem of synthesising stabilising distributed control laws for discrete-time linear systems that balances performance and communication is presented. The approach employs a supervisory agent that, periodically albeit not necessarily at every sampling instant, solves an optimisation problem in order to synthesise a stabilising state feedback control law for the system. The online optimisation problem, which maximises sparsity of the control law while minimising an infinite-horizon performance cost, is formulated as a bilinear matrix inequality (BMI) problem; subsequently, it is then relaxed to a linear matrix inequality (LMI) problem, and (i) convergence to a solution as well as (ii) that early termination guarantees a feasible (but suboptimal) control law are proved. Stability of the closed-loop system under what is a switched control law is guaranteed by the inclusion of dwell-time constraints in the LMI problem. Finally, the efficacy of the approach is demonstrated through numerical simulation examples.

Practical Controller Design of Three-Phase Dual Active Bridge Converter for Low Voltage DC Distribution System

In a low voltage DC (LVDC) distribution system, isolated bi-directional DC-DC converters are key devices to control power flows. A three-phase dual-active-bridge (3P-DAB) converter is one of the suitable candidates due to inherent soft-switching capability, low conduction loss, and high-power density. However, the 3P-DAB converter requires a well-designed controller due to the influence of the equivalent series resistance (ESR) of an output filter capacitor, degrading the performance of the 3P-DAB converter in terms of high-frequency noise. Unfortunately, there is little research that considers the practical design methodology of the 3P-DAB converter’s controller because of its complexity. In this paper, the influence of the ESR on the 3P-DAB converter is presented. Additionally, the generalized average small-signal model (SSM) of the 3P-DAB converter including the ESR of the capacitive output filter is presented. Based on this model, an extended small-signal model and appropriate controller design guide, and performance comparison are presented based on the frequency domain analysis. Finally, experimental results verify the validity of the proposed controller using a 25 kW prototype 3P-DAB converter.

Fast Smooth Second-Order Sliding Mode Control with Disturbance Observer for Automatic Shell Magazine

This paper studies practical control design for a novel automatic shell magazine (ASM) with a new fast smooth second-order sliding mode (FSSOSM) control based on disturbance observer. The dynamic model of the ASM with parameter perturbations and nonlinear friction is established. A higher order sliding mode disturbance observer based on super-twisting algorithm is utilized as a robust compensator to estimate the lumped uncertainties. The proposed FSSOSM control is performed to obtain the continuous sliding mode control law and inhibit the chattering phenomenon. The finite time convergence is investigated by utilizing the Lyapunov stability theorem. Three controllers, the traditional sliding mode controller, the proposed FSSOSM controller and a continuous fixed-time second-order sliding mode (CFTSOSM) controller, are compared. Extensive comparative simulation results under three typical working conditions (no-loaded, half-loaded and full-loaded) demonstrate that the proposed control strategy has a high dynamic tracking performance along with a good robustness against model uncertainty.

Model-free vibration control based on a virtual controlled object considering actuator uncertainty

The purpose of this research is to construct a simple and practical controller design method, considering the actuator’s parameter uncertainty, without using a model of controlled objects. In this method, a controller is designed with an actuator model including a single-degree-of-freedom virtual structure inserted between actuator and controlled object, resulting in a model-free controller design. Furthermore, an control problem is defined so that the actuator’s parameter uncertainty is compensated by satisfying a robust stability condition. Because the actuator model including the virtual controlled object is a simple low-order system, and the actuator’s parameter uncertainty is considered, a controller with high robustness to the actuator’s parameter uncertainty can be designed based on traditional model-based control theory. The effectiveness of the proposed method is verified by both simulation and experiment.

Bounded Analysis and Practical Tracking Control of Complex Stochastic Nonlinear Systems with Unknown Control Coefficients

This paper mainly focuses on the output practical tracking controller design for a class of complex stochastic nonlinear systems with unknown control coefficients. In the existing research results, most of the complex systems are controlled in a certain direction, which leads to the disconnection between theoretical results and practical applications. The authors introduce unknown control coefficients, and the values of the upper and lower bounds of the control coefficients are generalized by constants to allow arbitrary values to be arbitrarily large or arbitrarily small. In the control design program, the design problem of the controller is transformed into a parameter construction problem by introducing appropriate coordinate transformation. Moreover, we construct an output feedback practical tracking controller based on the dynamic and static phase combined by Ito stochastic differential theory and selection of appropriate design parameters, ensuring that the system tracking error can be made arbitrarily small after some large enough time. Finally, a simulation example is provided to illustrate the efficiency of the theoretical results.

A practical finite-time back-stepping sliding-mode formation controller design for stochastic nonlinear multi-agent systems with time-varying weighted topology

ABSTRACTThis paper addresses a practical finite-time leader-following formation controller design for the second-order stochastic Lipchitz nonlinear systems under uncertain communication environments and external disturbances. It is desired that the orientation of the formation change according to the variations in the leader’s orientation. The time-varying weighted topology matrix is modelled as a linear combination of a finite number of constant Laplacian matrices with time-varying coefficients. The proposed back-stepping sliding-mode controller guarantees that all the signals in the closed-loop system remain bounded in probability and the norm of sliding trajectories converge almost surely in finite-time to an arbitrary small neighbourhood of origin, which can be called almost-surely practical finite-time formation. The results are then modified for solving the consensus problem as well. In the simulation section, a stochastic multi-aircraft model, as well as a numerical example, are used to illustrate the effectiveness of the proposed design methods.

Practical control implementation of tri-tiltRotor flying wing unmanned aerial vehicles based upon active disturbance rejection control

Tilt rotor unmanned aerial vehicles exhibit their effectiveness via a novel and convenient structure. However, the flight control system is a critical problem in need of a robust solution. Focusing on its flight features, which display strong nonlinear and varying dynamics, caused by complexity in the aerodynamic layout and tilting structure, a practical control scheme is proposed to meet such technical issues. This paper first develops the nonlinear model, consisting of the interference between rotors and the wing body, relying on wind tunnel technology. A simplified linear model that decomposes the longitudinal and lateral components is used in order to facilitate controller design. Then, a time-scale separation decoupling control scheme based upon active disturbance rejection control is proposed to cope with control challenges. Introducing the concept of virtual control input, an effective control allocation is obtained by choosing the appropriate bandwidth in the frequency domain. The extended state observer is applied to estimate and compensate for unknown total disturbances and model uncertainties. Finally, robustness verification, successful test-bench experiments, and practical flight tests that show the fast tracking and disturbance rejection of the active disturbance rejection control controller are discussed. The proposed practical coupling rejection control design demonstrates its capability to employ a single input single output method to control a tri-tiltRotor flying wing unmanned aerial vehicle relying on active disturbance rejection control.