Proposed Control Design Approach Research Articles

Design of a decentralized control law for variable area coupled tank systems using H∞ complimentary sensitivity function

AbstractThis paper proposes a novel graphical approach to control the liquid levels of the different variable area coupled tank systems using a decentralized controller. The coupled tank systems are common benchmark systems that consist of two tanks interconnected with each other. The primary goal is to maintain the liquid level in the tank at the desired set point by controlling the flow rate. This is attained with a decentralized method wherein the controller values are obtained from the plane. Besides, the robust criteria is enforced to guarantee the robustness. The proposed controller design approach aims to improve the performance of the system in terms of disturbance rejection and tracking. The decentralized control structure uses a distributed control strategy, thereby reducing the computational load which leads to improving the control performance. The loop interactions are minimized with decouplers. Furthermore, first‐order plus dead‐time (FOPDT) models are derived for each of the decoupled subsystems. Besides, the servo and regulatory responses of the controller are verified with input and output disturbances. Additionally, the response of the controller to system uncertainties and parameter variations is also studied. The simulation results demonstrate the effectiveness and robustness of the proposed approach.

A learning- and scenario-based MPC design for nonlinear systems in LPV framework with safety and stability guarantees

ABSTRACT This paper presents a learning- and scenario-based model predictive control (MPC) design approach for systems modelled in the linear parameter-varying (LPV) framework. Using input-output data collected from the system, a state-space LPV model with uncertainty quantification is first learned through the variational Bayesian inference Neural Network (BNN) approach. The learned probabilistic model is assumed to contain the true dynamics of the system with a high probability and is used to generate scenarios that ensure safety for a scenario-based MPC. Moreover, to guarantee stability and enhance the performance of the closed-loop system, a parameter-dependent terminal cost and controller, as well as a terminal robust positive invariant set are designed. Numerical examples will be used to demonstrate that the proposed control design approach can ensure safety and achieve desired control performance.

A Lyapunov based Method for Designing State Feedback Controllers for a class of Discrete-time Systems

In this work, we look at a family of problems that restrict the input moves allowed. Optimal solutions of these problems turn out to be solutions of other problems. From these relations, we develop a novel interpretation for controller design in terms of a search for a Lyapunov function with a prescribed rate of decay dependent on states and inputs. We demonstrate how this method connects with LQOC. The efficacy of the proposed controller design approach is demonstrated using the benchmark quadruple tank system operated at the non-minimum phase operating point. Analysis of the simulation results reveal that, the controller tuning matrices can be effectively used for shaping state error and manipulated input profiles similar to the quadratic optimal control formulation.

Cooperative Adaptive Cruise Control in a Mixed-Autonomy Traffic System: A Hybrid Stochastic Predictive Approach Incorporating Lane Change

This paper presents a stochastic and predictive control design approach for connected and automated vehicles (CAVs) in a mixed-autonomy traffic environment, where CAVs are able to react properly to uncertain maneuvers of human-driven vehicles (HVs). The proposed fully-automated cooperative adaptive cruise control (CACC) design leverages a discrete hybrid stochastic model predictive controller that automatically determines the vehicle's operating mode based on onboard sensors data and information received through vehicle-to-vehicle (V2V) communication. Operating modes include free following, warning, danger, emergency braking, and lane change. Although the controller mainly focuses on maintaining the desired velocity and distance among CAVs, it also allows HVs to perform lane-change maneuvers and merge into the platoon's lane when needed. In response to an HV's position in the lane and its probabilistic behavior, the controller may switch the CAV's operating mode to react accordingly. Considering free-following and emergency-braking modes leads to efficient and safe autonomous driving. Switching between warning, danger, and lane-change modes along with adjusting the steering angle to perform a lane-change maneuver, when needed, robustifies the platoon's performance against unexpected human-driven vehicle maneuvers. Simulation studies are conducted to validate the efficacy of the proposed control design approach. The performance of the proposed control design approach is also compared to a switching control using simulation studies.

Discrete gain scheduling control approach to elliptical orbit rendezvous system with actuator saturation

AbstractThis paper studies the discrete gain scheduling control design problem of elliptical orbit spacecraft rendezvous system with actuator saturation. Due to the presence of actuator saturation, the dynamic performance of the spacecraft rendezvous system degrades significantly. In order to improve the dynamic performance of the system, a discrete gain scheduling control approach is adopted to construct a group of time‐invariant ellipsoidal invariant sets, which can be used to determine the switching points of the discrete gain scheduling control. By choosing some discrete parameter values, the discrete gain scheduling control is obtained from a solution of a periodic Riccati matrix differential equation. Under the control obtained, the dynamic performance of the system is much improved while accomplishing successfully the rendezvous mission of the spacecraft. Finally, a practical example is provided to show the effectiveness of the proposed control design approach.

A hybrid stochastic model predictive design approach for cooperative adaptive cruise control in connected vehicle applications

Wireless communication among connected and automated vehicles (CAVs) enables cooperative driving, particularly using cooperative adaptive cruise control, hence allowing CAVs to safely move closer to each other and improving traffic flow. However, reducing the gap between vehicles may cause collision, especially when a sudden deceleration in the vehicle platoon occurs. Furthermore, if some of the CAVs in the platoon lose communication, even for a short period, they may detect sudden changes in traffic with delay, and their reaction to avoid collision could be unsuccessful. Hence, an efficient emergency braking system can help preserve safety. This becomes even more important in high-speed driving, where a crash can put human lives in danger. This paper presents a discrete hybrid stochastic model predictive control approach to achieve a safe and efficient traffic system through CAV platooning. Three operational modes for vehicles are considered: free following, warning, and emergency braking. Each CAV in the free-following mode basically follows its preceding vehicle while enforcing maximum allowable deceleration in the emergency-braking mode. In the warning mode, the vehicle aims to slightly increase its headway and velocity difference from its predecessor to avoid possible danger. The warning/emergency-braking mode may be activated when the speed difference between a CAV and its preceding vehicle drops below a threshold. It is further assumed that vehicle distance sensing is subject to error. Each vehicle shares its current location, velocity, and future acceleration profile, calculated by solving a mixed-integer programming problem, with its follower vehicles. Simulation studies demonstrate the efficacy of the proposed control design approach compared to existing controllers in the literature in the presence of intermittent communication.

Secure Distributed Adaptive Platooning Control of Automated Vehicles Over Vehicular Ad-Hoc Networks Under Denial-of-Service Attacks.

This article deals with the problem of secure distributed adaptive platooning control of automated vehicles over vehicular ad-hoc networks (VANETs) in the presence of intermittent denial-of-service (DoS) attacks. The platoon, which is wirelessly connected via directed vehicle-to-vehicle (V2V) communication, is composed of a group of following vehicles subject to unknown heterogeneous nonlinearities and external disturbance inputs, and a leading vehicle subject to unknown nonlinearity and external disturbance as well as an unknown control input. Under such a platoon setting, this article aims to accomplish secure distributed platoon formation tracking with the desired longitudinal spacing and the same velocities and accelerations guided by the leader regardless of the simultaneous presence of nonlinearities, uncertainties, and DoS attacks. First, a new logical data packet processor is developed on each vehicle to identify the intermittent DoS attacks via verifying the time-stamps of the received data packets. Then, a scalable distributed neural-network-based adaptive control design approach is proposed to achieve secure platooning control. It is proved that under the established design procedure, the vehicle state estimation errors and platoon tracking errors can be regulated to reside in small neighborhoods around zero. Finally, comparative simulation studies are provided to substantiate the effectiveness and merits of the proposed control design approach on maintaining the desired platooning performance and attack tolerance.

Dynamic modeling and robust nonlinear control of a laboratory gas turbine engine

In this paper, a physics-based mathematical model of a mini SR-30 gas turbine engine (GTE) is presented using a state variable modeling method. This model is developed by utilizing approximated maps of the engine components and generic governing equations that describe the engine's behavior. The mathematical model captures both the steady-state and transient behavior of the engine. Using the developed model, a modern control system design approach is proposed to satisfy the stability and performance of the GTE. The objective of this control design is to adjust the required fuel flow rate to the combustion chamber such that the shaft speed of the engine tracks its command signal as closely as possible. The proposed robust nonlinear fuel flow controller is developed based on the nonlinear dynamic inversion (NDI) technique, augmented with a dual extended Kalman filter (DEKF) estimation design. DEKF-based state and parameter estimation are used here to ensure robustness against model inaccuracies due to not accurately known component maps, as well as process and measurement noises. To validate the developed mathematical model, the realistic data extracted from the SR-30 GTE are utilized. The simulation results of the proposed control design approach indicate that it is effective in achieving satisfactory performance of the engine. Also, the proposed NDI controller is compared with the well-established proportional-integral-derivative (PID) controller to illustrate its superiority.

Novel Robust Control of Stochastic Nonlinear Switched Fuzzy Systems

This paper addresses the problem of designing novel switching control for a class of stochastic nonlinear switched fuzzy systems with time delay. Firstly, a stochastic nonlinear switched fuzzy system can precisely describe continuous and discrete dynamics as well as their interactions in the complex real-world systems. Next, novel control algorithm and switching law design of the state-dependent form are developed such that the stability is guaranteed. Since convex combination techniques are used to derive the delay independent criteria, some subsystems are allowed to be unstable. Finally, various comparisons of the elaborated examples are conducted to demonstrate the effectiveness of the proposed control design approach. All results illustrate good control performances as desired.

Parameter identification for load frequency control using fuzzy FOPID in power system

Purpose This paper aims to suggest the parameter identification of load frequency controller in power system. Design/methodology/approach The suggested control approach is established using fuzzy logic to design a fractional order load frequency controller. A new suitable control law is developed using fuzzy logic, and based on this developed control law, the unknown parameters of the fractional order proportional integral derivative (FOPID) controller are derived using an optimization technique, which is being used by minimizing the integral square error. In addition, to confirm the effectiveness of the proposed control design approach, numerous simulation tests were carried out on an actual single-area power system. Findings The obtained results reveal the superiority of the suggested controller as compared to the recently developed controllers with regard to time response specifications and quantifiable indicators. Additionally, the potential of the suggested controller is also observed by improving the load disturbance rejections under plant parametric uncertainty. Originality/value To the best of the authors’ knowledge, the work is not published anywhere else.

A Robust Formation Control Strategy for Multi-Agent Systems with Uncertainties via Adaptive Gain Robust Controllers

This paper deals with a design problem of an adaptive gain robust controller which achieves consensus for multi-agent system (MAS) with uncertainties. In the proposed controller design approach, the relative position between the leader and followers are considered explicitly, and the proposed adaptive gain robust controller consisting of fixed gains and variable ones tuned by time-varying adjustable parameters can reduce the effect of uncertainties. In this paper, we show that sufficient conditions for the existence of the proposed adaptive gain robust controller are reduced to solvability of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed robust formation control system is verified by simple numerical simulations. A main result of this study is that the proposed adaptive gain robust controller can achieve consensus and formation control giving consideration to relative distance in spite of uncertainties.

Real-Time Performance Analysis of PIDD2 Controller for Nonlinear Twin Rotor TITO Aerodynamical System

Twin-rotor two-input two-output (TITO) aerodynamical system (TRAS) is a highly non-linear system with a cross-coupling effect. The objective of the controller design in TRAS is to track the trajectory of azimuth and pitch angles, reach the desired azimuth and pitch angle positions, and stabilize TRAS in the presence of significant cross-coupling. The coupling effect between the main rotor and tail rotor is a severe issue for the controller design. So, this paper proposes a proportional integral derivative double derivative (PIDD2) controller design for TRAS, first time. Further, the tuning of PIDD2 controller is carried out via a modified grey wolf optimizer (MGWO). Besides, the real-time hardware-in-loop (HIL) implementation of the PIDD2 controller with the TRAS laboratory prototype setup is carried out, first-time. Moreover, It is tested under external disturbances for robustness and effectiveness analyses. In addition, this paper performs both simulations as well as hardware results analyses. These analyses reveal that the experimental results are found to match closely with simulation results. Finally, the efficacy of the proposed control design approach is presented by comparing it with the recently published controldesign schemes.

Observer‐based tracking controller design for a class of polynomial fuzzy systems with disturbance

AbstractIn this paper, the tracking control law design problem for a class of polynomial fuzzy systems subjected to external bounded disturbance is studied. The tracking control design problem is solved using the observer‐based tracking controller design method in which the observer estimates the controlled system state vector and also the system states will follow the state vector of a stable reference model subject to an H∞ performance. The process of calculating controller parameters is formulated as an SOS feasibility program. Simulation results are presented to show the merits of the proposed control design approach.

Adaptive guidance and control of uncertain lunar landers in terminal landing phases

A novel double-loop guidance and control strategy for under-actuated lunar landers in terminal landing phases is developed by using adaptive nonlinear control approach in this study. To derive the main thrust input and inner-loop desired attitude trajectory, the outer-loop position tracking guidance law is firstly developed based on the hyperbolic tangent functions to guarantee the constrained thrust and singularity avoidance of the desired attitudes. Then, to avoid the complicated analytic-derivative computing of the desired attitude trajectory, a stable second-order filter is employed to generate the command attitude trajectory for the inner-loop attitude motion. Finally, an adaptive attitude tracking controller is designed by combining the barrier Lyapunove function and the backstepping technique to get rid of the singularities of the Euler angles-based attitude kinematic Jacobian matrix. In addition, tuning rules for designing parameters in guidance law and attitude controller are derived based on the Lyapunov analysis, and the pose tracking errors in the closed-loop system ultimately converge to the small neighborhoods of the origin. An example is simulated to verify the effectiveness of the proposed control design approach.

Electric spring average model development and dynamic analysis for demand‐side management

This study proposes a new averaged model for steady-state and dynamic response analysis of the electric spring (ES). The accuracy of steady-state and dynamic behaviour of the ES is demonstrated. Further, the dynamic behaviour of the proposed model is described as a function of the modulating signal. The developed model is used to design a controller for bus voltage regulation in a distribution system with an intermittent renewable energy source. The ES controller design problem is formulated as an optimization problem with a time domain-based objective function to reduce the time-weighted voltage deviations using particle swarm optimization method. Different disturbances have been applied to verify the developed ES model accuracy including sudden changes in renewable source current and load variations. An experimental analysis is also performed with the detailed non-linear switching model of the ES to verify its behaviour with that of the proposed averaged model. The characteristics and performance of ES are thoroughly investigated. The effectiveness of the developed model and the proposed controller design approach is demonstrated in terms of a significant improvement in the dynamic performance of the distribution system

Security Sliding Mode Control of Interval Type-2 Fuzzy Systems Subject to Cyber Attacks: The Stochastic Communication Protocol Case

This article addresses the security control problem of a class of interval type-2 fuzzy systems via the sliding mode control strategy. A stochastic communication scheduling protocol is utilized to govern the transmission from the sensors to the controller, by which only one sensor node has the chance to transmit its value at every instant. Meanwhile, cyber attacks from malicious adversaries might be launched in vulnerable communication channels. To quantitatively analyze the effect of the stochastic communication protocol and cyber attacks, their mathematical model is first constructed based on a compensation scheme. Since the scheduling signal may be unavailable once cyber attacks are activated, a desirable sliding mode control law is synthesized with token-independent control gains, whose membership functions are mismatched with those of the fuzzy system. To deal with these mismatched membership functions, the relations between the membership functions of the system and the control law are reconstructed. Consequently, the favorable property of perfectly matched memberships could be employed. Sufficient conditions are derived so that the resultant closed-loop interval type-2 fuzzy system is stochastically stable and, at the same time, the state trajectories can be forced into a small domain around the prescribed sliding surface. The proposed control design approach is verified by two examples.

Adaptive Fuzzy Control for Multivariable Nonlinear Systems with Indefinite Control Gain Matrix and Unknown Control Direction

Abstract In this paper, we focus on the direct adaptive fuzzy control design for a class of uncertain MIMO nonlinear systems with indefinite control gain matrix and unknown control direction. The control design is based on the approximation of an unknown ideal control law that can meet the control objective by using fuzzy systems. The adjustable parameters of the used fuzzy systems are adjusted online using the error between the unknown ideal controller and the fuzzy controller. In this paper, unlike most existing works, the Nussbaum gain technique is not used to overcome the obstacle of the unknown control direction. In fact, with the help of a matrix decomposition technique, the unknown control direction is redefined as an unknown constant vector, which is estimated online by a suitable update law. The stability of the closed-loop system is studied using the Lyapunov direct approach. Numerical simulation results are provided to illustrate the effectiveness of the proposed control design approach.

Disturbance Attenuation via Nonlinear Feedback for Chemical Reaction Networks

This paper deals with the setpoint control of Chemical Reaction Networks (CRNs) in the presence of disturbances. The addressed control problem is traced back to the output feedback-based stabilization of passive systems. First, the passivity properties of complex balanced CRNs are discussed. Second, it is shown that, by combining the kinetic feedback based control with the passivity theory-based output feedback approach, arbitrary disturbance attenuation in controlled CRNs can be achieved. A case study is provided to demonstrate the applicability of the proposed control design approach.

Event‐triggered finite‐time reliable control for nonhomogeneous Markovian jump systems

SummaryThis article investigates the event‐triggered finite‐time reliable control problem for a class of Markovian jump systems with time‐varying transition probabilities, time‐varying actuator faults, and time‐varying delays. First, a Luenberger observer is constructed to estimate the unmeasured system state. Second, by applying an event‐triggered strategy from observer to controller, the frequency of transmission is reduced. Third, based on linear matrix inequality technique and stochastic finite‐time analysis, event‐triggered observer‐based controllers are designed and sufficient conditions are given, which ensure the finite‐time boundedness of the closed‐loop system in an H∞ sense. Finally, an example is utilized to show the effectiveness of the proposed controller design approach.

Fractional Order PIλDµ Control Design for a Class of Cyber-Physical Systems with Fractional Order Time-Delay models

The control of cyber-physical systems (CPS) is a great challenge for researchers in control theory and engineering mainly because of delays induced by merging computation, communication, and control of physical processes. Consequently, control solutions for time-delay systems can be applied efficiently for many CPS system configurations. In this article, a fractional order PIλ and PIλDµ control design is investigated for a class of fractional order time-delay systems. The proposed control design approach is simple and efficient. The controller parameter's adjustment is achieved in two steps: first, the relay approach is used to compute satisfactory classical PID coefficients, namely kp, Ti and Td. Then, the fractional orders λ and µ are optimized using performance criteria. Simulation results show the efficiency of the proposed design technique and its ability to enhance the PID control performance.