Adaptive Control Theory Research Articles

Conditioned Adaptive Control for an Uncertain Bioreactor with Input Saturation and Steep Settling Desired Output

In this work, a controller is developed for a continuous bioreactor with an unknown reaction rate term, subject to input saturation. The substrate concentration and the dilution rate are chosen as output and input, respectively. The controller formulation and the stability analysis are performed by the theory of dead zone Lyapunov functions, Lyapunov stability, and model reference adaptive control. As the main results, the dynamics of the Lyapunov function is determined separately for saturation and non-saturation events, and then a unified expression is deduced. In addition, the asymptotic convergence of the tracking error and boundedness of updated parameters are determined for the whole closed loop regime encompassing saturation and non-saturation events, and also for input saturation events, as a function of the terms and parameters of the reference and system models. The main contributions over closely related control designs, are (i) the effect of input constraint limits and desired output on the convergence of the tracking error during input saturation events are determined, considering settling behavior of the desired output with a steep section; (ii) the upper limit of the input constraint that guarantees output convergence during input saturation events is determined as function of the model terms, but independently of the time derivative of the desired output and its limit; (iii) a new dead zone Lyapunov function is proposed which allows proving asymptotic convergence of the tracking error during input saturation events in the presence of a fast variation in the desired output. Finally, the effectiveness and advantages of the developed controller are illustrated by simulation.

Nonlinear disturbance observer-based adaptive nonlinear model predictive control design for a class of nonlinear MIMO system

Model predictive control with less prior knowledge of system uncertainty and external disturbance is a long-standing theoretical and practical problem. In this paper, a solution is presented by proposing a disturbance observer-based adaptive nonlinear model predictive control scheme for a class of nonlinear MIMO systems. Our scheme requires the state and parameterdependent state-space model to linearise the nonlinear system along the prediction horizon. To cope with the unknown system uncertainty, the multiple estimation model and the concept of second-level adaptation [Pandey, V. K., Kar, I., & Mahanta, C. (2014). Multiple models and second level adaptation for a class of nonlinear systems with nonlinear parameterisation. In Industrial and Information Systems (ICIIS), 2014 9th International Conference on (pp. 1–6). IEEE.] technique for the nonlinear system is used. To ensure the boundedness of the estimated parameter, a projection-based adaptive law [Hovakimyan, N., & Cao, C. (2010). L1 adaptive control theory: Guaranteed robustness with fast adaptation. SIAM.] is used. Using a twin-rotor MIMO system (TRMS), the effectiveness of the proposed control algorithm has been verified. Simulation and real-time results show that the proposed control algorithm performs better than the existing control algorithm in the presence of unknown external disturbance and parameter uncertainties.

Denial of Service Attack of QoS-Based Control of Multi-Agent Systems

This paper presents a secure formation control design of multi-agent systems under denial of service (DoS) attacks. Multiple unmanned aerial vehicle systems (UAVs) are considered in this paper. The proposed technique takes into account communication time delay, as well as formation and cyberattack, and provides a robust guidance method as well as a reliable middleware for information transfer and sharing. To ensure optimal guidance and coordination, a combined approach of L1 adaptive control and graph theory is used. The packet transmission between all UAVs is handled by the data distribution services (DDS) middleware, which overcomes the interoperability problem when dealing with multiple UAVs of different platforms and can be considered as an extra security level based on its quality of service (QoS). The graph theory is utilized to coordinate multiple UAVs in a hexagon formation, while the L1 controller is utilized as a local controller to stabilize the UAV’s dynamic model. A robust control security level is built to handle the effect of cyberattacks based on linear matrix inequalities (LMIs) control. Simulations are used to verify and show the performances of the proposed technique under the conditions indicated earlier.

Novel Strategy of Adaptive Predictive Control Based on a MIMO-ARX Model

Many industrial processes include MIMO (multiple-input, multiple-output) systems that are difficult to control by standard commercial controllers. This paper describes a MIMO case of a class of SISO-APC (single-input, single-output adaptive predictive controller) based upon an ARX (autoregressive with exogenous variable) model. This class of SISO-APC based on ARX models has been successfully and extensively used in many industrial applications. This approach aims to minimize the barriers between the theory of predictive adaptive control and its application in the industrial environment. The proposed MIMO-APC (MIMO adaptive predictive controller) performance is validated with two simulated processes: a quadrotor drone and the quadruple tank process. In the first experiment the proposed MIMO APC shows ISE-IAE-ITAE performance indices improvements of up to 25%, 25.4% and 38.9%, respectively. For the quadruple tank process the water levels in the lower tanks follow closely the set points, with the exception of a 13% overshoot in tank 1 for the minimum phase behavior response. The controller responses show significant performance improvements when compared with previously published MIMO control strategies.

Adaptive Control for Flow and Volume Regulation in Multi-Producer District Heating Systems

Flow and storage volume regulation is essential for the adequate transport and management of energy resources in district heating systems. In this letter, we propose a novel and suitably tailored-decentralized-adaptive control scheme addressing this problem whilst offering closed-loop stability guarantees. We focus on a system configuration comprising multiple heat producers, consumers and storage tanks exchanging energy through a common distribution network, which are features of modern and prospective district heating installations. The proposed controller is based on passivity, backstepping and (indirect) adaptive control theory.

PID Tuning using Cross-Entropy Deep Learning: a Lyapunov Stability Analysis

Underwater Unmanned Vehicles (UUVs) have to constantly compensate for the external disturbing forces acting on their body. Adaptive Control theory is commonly used there to grant the control law some flexibility in its response to process variation. Today, learning-based (LB) adaptive methods are leading the field where model-based control structures are combined with deep model-free learning algorithms. This work proposes experiments and metrics to empirically study the stability of such a controller. We perform this stability analysis on a LB adaptive control system whose adaptive parameters are determined using a Cross-Entropy Deep Learning method.

A survey of adaptive optimal control theory.

This paper makes a survey about the recent development of optimal control based on adaptive dynamic programming (ADP). First of all, based on DP algorithm and reinforcement learning (RL) algorithm, the origin and development of the optimization idea and its application in the control field are introduced. The second part introduces achievements in the optimal control direction, then we classify and summarize the research results of optimization method, constraint problem, structure design in control algorithm and practical engineering process based on optimal control. Finally, the possible future research topics are discussed. Through a comprehensive and complete investigation of its application in many existing fields, this survey fully demonstrates that the optimal control algorithms via ADP with critic-actor neural network (NN) structure, which also have a broad application prospect, and some developed optimal control design algorithms have been applied to practical engineering fields.

The role of closed-loop attitude dynamics in adaptive UAV position control

This paper presents the design and the stability analysis of an adaptive position controller for Unmanned Aerial Vehicles (UAVs). Considering a hierarchical control scheme, the novelty of this work is the definition of a systematic approach to design a position controller based on Model Reference Adaptive Control (MRAC) theory taking into account not-fast closed-loop attitude dynamics. After having reformulated the problem considering the attitude dynamics as pseudo-actuator, the authors exploit an existing Linear Matrix Inequality (LMI) based hedging framework designed such that the adaptation performance is not affected by the presence of actuator dynamics. Results from simulations and from experiments on a platform designed to replicate the longitudinal motion of quadrotors are provided to illustrate the performance of the proposed control scheme.

Finite-time [formula omitted] synchronization for complex dynamical networks with time-varying delays based on adaptive control

This paper investigates the problem of finite-time H∞ synchronization (H∞FTS) for complex dynamical networks (CDNs) with time-varying delays(TVDs) and unknown internal coupling matrices. External disturbances are also considered into this model. By applying the adaptive control theory, this paper presents the adaptive control method to solve the H∞FTS of CDNs with external disturbances and TVDs. Some criteria are obtained by utilizing appropriate adaptive controllers and devising a special Lyapunov–Krasovskii function (LKF), which ensure the H∞FTS of CDNs based on passivity theory. Finally, using some effective mathematical techniques, comparative numerical example and Chua’s circuit system are used to explain the advantages and applicability of the results and approaches.

A new synchronisation method of fractional-order chaotic systems with distinct orders and dimensions and its application in secure communication

In this paper, an adaptive generalised function projective synchronisation scheme of fractional-order chaotic systems with different dimensions and orders and fully unknown parameters is presented. On the basis of the Lyapunov method of fractional-order systems, a stability theorem of the fractional-order system with non-identical orders is proven. Using the fractional-order controller and adaptive control theory, sufficient conditions for synchronisation and unknown parameters update rules are obtained. Theoretical analysis and numerical simulations are provided to verify the validity of the proposed scheme. Moreover, synchronisation results are applied to secure communication via modified chaotic masking (MCM) method. The unpredictability of the scaling function matrix and the use of fractional-order systems with different orders can increase the security of the cryptosystem. The security analysis shows that the introduced algorithm has large key space, high sensitivity to encryption keys, higher security and the acceptable encryption speed.

Model-free adaptive nonlinear control of the absorption refrigeration system

Based on the model-free adaptive control (MFAC) theory, the temperature tracking control problem of single-effect LiBr/H2O absorption chiller is explored. Due to the complex nonlinearity and strong coupling characteristics of the absorption refrigeration system, model-free adaptive control strategy is designed for its temperature tracking control. Nevertheless, the traditional model-free adaptive control has a slow tracking speed and poor denoising ability. In order to improve its control effect, output error rate is added to the objective function and new control laws of model-free adaptive control with output error rate (MFAC-OER) have been derived through an exhaustive convergence and stability analysis. The input information and output information of the absorption refrigeration system, namely the hot water pump frequency and chilled water outlet water temperature, are combined. The data model of the absorption refrigeration system is subsequently deduced using a compact format dynamic linearization method. Next, based on the single-effect absorption chiller experimental platform in our laboratory, its sixth-order dynamic model is built. Finally, the effectiveness and practicability of the improved control strategy are illustrated by numerical simulations and experimental operating data from our laboratory as well as by the dynamical model of the absorption chiller.

Energy Efficiency Enhanced Landing Strategy for Manned eVTOLs Using L1 Adaptive Control

A new landing strategy is presented for manned electric vertical takeoff and landing (eVTOL) vehicles, using a roll maneuver to obtain a trajectory in the horizontal plane. This strategy rejects the altitude surging in the landing process, which is the fatal drawback of the conventional jumping strategy. The strategy leads to a smoother transition from the wing-borne mode to the thrust-borne mode, and has a higher energy efficiency, meaning a better flight experience and higher economic performance. To employ the strategy, a five-stage maneuver is designed, using the lateral maneuver instead of longitudinal climbing. Additionally, a control system based on L1 adaptive control theory is designed to assist manned driving or execute flight missions independently, consisting of the guidance logic, stability augmentation system and flight management unit. The strategy is verified with the ET120 platform, by Monte Carlo simulation for robustness and safety performance, and an experiment was performed to compare the benefits with conventional landing strategies. The results show that the performance of the control system is robust enough to reduce perturbation by at least 20% in all modeling parameters, and ensures consistent dynamic characteristics between different flight modes. Additionally, the strategy successfully avoids climbing during the landing process with a smooth trajectory, and reduces the energy consumed for landing by 64%.

Modeling and Adaptive Control Law Design for a Bi-Tiltrotor Unmanned Aerial Vehicle

This paper presents modeling and control law design for a bi-tiltrotor unmanned aerial vehicle for autonomous payload delivery. An ultralight bi-tiltrotor aerial vehicle was developed for a payload delivery contest using only two motors attached to a carbon fiber tube with an additional cube basket to carry the payload. To achieve desirable three-dimensional (3D) trajectory tracking performance with unknown payload, an adaptive control system has been developed, which consists of two components: (1) a baseline control law, including a lateral speed controller, forward speed controller, yaw angle controller, and altitude controller; and (2) an adaptive augmentation to all these four channels to compensate for modeling uncertainties and disturbances caused by the payload, which has large influence on system dynamics due to the light weight of the vehicle. A mathematical model of the vehicle has been built using the Newton-Euler method and simplified based on reasonable assumptions to facilitate control design. The baseline control law employs conventional proportional-derivative control structure. Subsequently, L1 adaptive control theory is adopted in the adaptive augmentation design. Simulation examples verify the efficacy of the proposed adaptive control solution.

Optimization Design of Centrifugal Pump Flow Control System Based on Adaptive Control

In this paper, in order to improve the control characteristics of the centrifugal pump flow control system, a mathematical model of the centrifugal pump flow control system was established based on an analysis of the basic structures, such as the frequency converter, motor, and centrifugal pump. Based on the adaptive control theory, the recursive least squares algorithm with a forgetting factor was used to estimate the real-time parameters of the centrifugal pump control system, and the self-tuning PID control method was used to optimize the mathematical model of the centrifugal pump flow control system. The simulation results showed that the adjustment time of the optimized system was shortened by 16.58%, and the maximum overshoot was reduced by 83.90%, which improved the rapidity and stability of the transient response of the system. This showed that adaptive control had a significant effect on improving the robustness and anti-interference ability of the centrifugal pump control system. In order to further verify the accuracy of the self-tuning PID control method, a flow adaptive control system test platform was built. The test results showed that under the conditions of constant frequency and variable frequency, the actual flow rate of the centrifugal pump was always kept near the set flow rate, the error was small, and it had better real-time followability. The research results showed that adaptive control could revise the parameters in real-time according to changes to the centrifugal pump control system, which improved the stability and robustness of the system. Therefore, adaptive PID control could effectively improve the adaptability of centrifugal pumps to various complex working conditions and improve the working efficiency of centrifugal pumps.

Model-Free Adaptive Control for Tank Truck Rollover Stabilization

Influenced by lateral liquid sloshing in partially filled tanks, tank vehicles are apt to encounter with rollover accidents. Due to its strong nonlinearity and loading state uncertainty, it has great challenges in tank vehicle active control. Based on the model-free adaptive control (MFAC) theory, the roll stability control problem of tank trucks with different tank shapes and liquid fill percentages is explored. First, tank trucks equipped with cylinder or elliptical cylinder tanks are modelled, and vehicle dynamics is analyzed. This dynamic model is used to provide I/O data in the controlled system. Next, the control objective of tank vehicle rollover stabilization is analyzed and the controlled variable is selected. Subsequently, differential braking and active front steering controller are designed by MFAC algorithm. Finally, the effectiveness of the designed controllers is verified by simulation, and difference between the controllers is analyzed. The controller designed by MFAC algorithm is proven to be adaptive to vehicle loading and driving states. The controlled system has great robustness.

Synchronization Control of a Dual-Cylinder Lifting Gantry of Segment Erector in Shield Tunneling Machine under Unbalance Loads

Segment assembling is one of the principle processes during tunnel construction using shield tunneling machines. The segment erector is a robotic manipulator powered by a hydraulic system to assemble prefabricated concrete segments onto the excavated tunnel surface. Nowadays, automation of the segment erector has become one of the definite developing trends to further improve the efficiency and safety during construction; thus, closed-loop motion control is an essential technology. Within the segment erector, the lifting gantry is driven by dual cylinders to lift heavy segments in the radial direction. Different from the dual-cylinder mechanism used in other machines such as forklifts, the lifting gantry usually works at an inclined angle, leading to unbalanced loads on the two sides. Although strong guide rails are applied to ensure synchronization, the gantry still occasionally suffers from chattering, “pull-and-drag”, or even being stuck in practice. Therefore, precise motion tracking control as well as high-level synchronization of the dual cylinders have become essential for the lifting gantry. In this study, a complete dynamics model of the dual-cylinder lifting gantry is constructed, considering the linear motion as well as the additional rotational motion of the crossbeam, which reveals the essence of poor synchronization. Then, a two-level synchronization control scheme is synthesized. The thrust allocation is designed to coordinate the dual cylinders and keep the rotational angle of the crossbeam within a small range. The motion tracking controller is designed based on the adaptive robust control theory to guarantee the linear motion tracking precision. The theoretical performance is analyzed with corresponding proof. Finally, comparative simulations are conducted and the results show that the proposed scheme achieves high-precision motion tracking performance and simultaneous high-level synchronization of dual cylinders under unbalanced loads.

A New No Equilibrium Fractional Order Chaotic System, Dynamical Investigation, Synchronization, and Its Digital Implementation

In this paper, a new fractional order chaotic system without equilibrium is proposed, analytically and numerically investigated, and numerically and experimentally tested. The analytical and numerical investigations were used to describe the system’s dynamical behaviors including the system equilibria, the chaotic attractors, the bifurcation diagrams, and the Lyapunov exponents. Based on the obtained dynamical behaviors, the system can excite hidden chaotic attractors since it has no equilibrium. Then, a synchronization mechanism based on the adaptive control theory was developed between two identical new systems (master and slave). The adaptive control laws are derived based on synchronization error dynamics of the state variables for the master and slave. Consequently, the update laws of the slave parameters are obtained, where the slave parameters are assumed to be uncertain and are estimated corresponding to the master parameters by the synchronization process. Furthermore, Arduino Due boards were used to implement the proposed system in order to demonstrate its practicality in real-world applications. The simulation experimental results were obtained by MATLAB and the Arduino Due boards, respectively, with a good consistency between the simulation results and the experimental results, indicating that the new fractional order chaotic system is capable of being employed in real-world applications.

New Method Based on Model-Free Adaptive Control Theory and Kalman Filter for Multi-Product Unsteady Flow State Estimation

Abstract In this paper, a new methodology is proposed to realize real-time unsteady flow estimation for a multi-product pipeline system. Integrating transient flow model, adaptive control theory, and adaptive filter, this method is developed to solve the contradiction between the efficiency and accuracy in traditional model-based methods. In terms of improving computational efficiency, the linear flow model based on frequency response and difference transforming is established to replace the traditional nonlinear flow model for transient flow state estimation. To reduce the deviation between actual observations and linear model estimates, we first introduce a model-free adaptive control method as linear compensation of the reduced order unsteady flow state model. To overcome the interference of observation noise, the Kalman filter method is applied to the modified state space model to obtain the one-step-ahead transient flow estimation. The proposed method is applied to the transient flow state estimation of a multi-product pipeline system and compared with the model-based method and two data-driven methods. The proposed method can reduce the deviation of transient flow estimation between the reduced order linear model and the traditional nonlinear model to less than 0.5% under unforeseen conditions and shows strong robustness to noise interference and parameter drift.

Cooperative control method of multi-missile formation under uncontrollable speed

Under the missile speed is uncontrollable, a design method of multi-missile formation flight controller based on the sliding mode variable structure control theory and adaptive dynamic surface control theory is proposed. Firstly, according to the relative position of the leader and the follower in the inertial frame, the tracking error model for the relative position and the expected relative position between the leader and the follower is obtained, and the multi-missile formation control system in the inertial coordinate system is obtained. Secondly, in order to obtain the expression of the formation control system in the ballistic coordinate system, the acceleration of the missile in the ballistic coordinate system is converted to the inertial coordinate system. Combining with the tracking of the relative position and the desired relative position of the leader and the followers, we can obtain the simplified error model for the formation control system. Then the sliding mode variable structure control theory and the adaptive dynamic surface control theory are used to design the formation controllers for the leader and follower missiles respectively, and the stability of the present controller is analysed via the Lyapunov stability theory. Finally, the designed formation controllers are used for the leader and follower missiles to simulate the parameters. The results verify the feasibility and effectiveness of the present method.

A Discrete-Time Robust Adaptive PI Controller for Grid-Connected Voltage Source Converter with LCL Filter

In this work, it is presented a new direct discrete-time robust adaptive PI (Proportional Integral) Controller for grid-injected current control loop of a voltage source converter with LCL filter. The mathematical background is based on Robust Model Reference Adaptive Control theory. However, the proposed controller is straightforward, it does not need a reference model and has capability to track directly currents reference. This approach simplifies significantly controller design, resulting in a reformulation of parameters vector used for adaptation of adjustable gains. It turns the controller robust to unmodelled dynamics, while avoid the complexity inherent to the conventional high order adaptive controllers for grid-connected power systems. Besides, it is highlighted that proposed controller does not need resonant controllers for grid disturbance rejection, or require any knowledge of grid parameters, lines impedance or load power demand. Also, due to its simple structure, it is easily implemented and does not require a high processing capacity. Furthermore, the effectiveness of the control strategy in terms of reference tracking, harmonics content and robustness to the grid impedance variation is corroborated through experiments.