Design Of Adaptive Control System Research Articles

Self-organizing adaptive wavelet CMAC backstepping control system design for nonlinear chaotic systems

A novel self-organizing wavelet cerebellar model articulation controller (CMAC) is proposed. This self-organizing wavelet CMAC (SOWC) can be viewed as a generalization of a self-organizing neural network and of a conventional CMAC, and it has better generalizing, faster learning and faster recall than a self-organizing neural network and a conventional CMAC. The proposed SOWC has the advantages of structure learning and parameter learning simultaneously. The structure learning possesses the ability of on-line generation and elimination of layers to achieve optimal wavelet CMAC structure, and the parameter learning can adjust the interconnection weights of wavelet CMAC to achieve favorable approximation performance. Then a SOWC backstepping (SOWCB) control system is proposed for the nonlinear chaotic systems. This SOWCB control system is composed of a SOWC and a fuzzy compensator. The SOWC is used to mimic an ideal backstepping controller and the fuzzy compensator is designed to dispel the residual of approximation errors between the ideal backstepping controller and the SOWC. Moreover, the parameters of the SAWCB control system are on-line tuned by the derived adaptive laws in the Lyapunov sense, so that the stability of the feedback control system can be guaranteed. Finally, two application examples, a Duffing–Holmes chaotic system and a gyro chaotic system, are used to demonstrate the effectiveness of the proposed control method. The simulation results show that the proposed SAWCB control system can achieve favorable control performance and has better tracking performance than a fuzzy neural network control system and a conventional adaptive CMAC.

Adaptive cruise control with stop&go function using the state-dependent nonlinear model predictive control approach

In the design of adaptive cruise control (ACC) system two separate control loops – an outer loop to maintain the safe distance from the vehicle traveling in front and an inner loop to control the brake pedal and throttle opening position – are commonly used. In this paper a different approach is proposed in which a single control loop is utilized. The objective of the distance tracking is incorporated into the single nonlinear model predictive control (NMPC) by extending the original linear time invariant (LTI) models obtained by linearizing the nonlinear dynamic model of the vehicle. This is achieved by introducing the additional states corresponding to the relative distance between leading and following vehicles, and also the velocity of the leading vehicle. Control of the brake and throttle position is implemented by taking the state-dependent approach. The model demonstrates to be more effective in tracking the speed and distance by eliminating the necessity of switching between the two controllers. It also offers smooth variation in brake and throttle controlling signal which subsequently results in a more uniform acceleration of the vehicle. The results of proposed method are compared with other ACC systems using two separate control loops. Furthermore, an ACC simulation results using a stop&go scenario are shown, demonstrating a better fulfillment of the design requirements.

Robust Systems with Discontinuous Parameters

Abstract In this paper we consider robust SISO systems with nonlinear controller. The plant dynamics are described by a switched system model. The control law is defined with help of the approach of adaptive control system design. Output derivatives are used to form control. Control systems are robust to discontinuous parameters disturbances. The system stability is studied by common Lyapunov function approach.

PFC Design via FRIT Approach and Adaptive PID Control System Design for Discrete-time Systems

This paper deals with a design problem of an adaptive PID control for discrete-time systems with a parallel feedforward compensator (PFC) which is designed for making the augmented controlled system ASPR. A PFC design scheme by a FRIT approach with only using an input/output experimental data set will be proposed for discrete-time systems in order to design an adaptive PID control system. Furthermore, the effectiveness of the proposed PFC design and an adaptive PID control method will be confirmed through numerical simulations for an uncertain discrete-time system.

SoPC-Based Adaptive PID Control System Design for Magnetic Levitation System

This paper develops an adaptive proportional-integral-derivative (APID) control system to deal with the metallic sphere position control of a magnetic levitation system (MLS), which is an intricate and highly nonlinear system. The proposed control system consists of an adaptive PID controller and a fuzzy compensation controller. The adaptive PID controller is a main tracking controller, and the parameters of the adaptive PID controller are online tuned by the derived adaptation laws. In this design, the particle swarm optimization (PSO) technology is adopted to search the optimal learning-rates of the adaptive PID controller to increase the learning speed. The design of the fuzzy compensation controller can guarantee the stability of the control system. Since system-on-programmable-chip (SoPC) has several benefits including low cost, high speed, and small volume, the developed control scheme is implemented in the SoPC-based hardware. Finally, simulation and experimental results of the magnetic levitation system have been performed to verify the effectiveness of the proposed control scheme.

Design of Adaptive Road Traffic Control System through Unified Modeling Language

Design of Adaptive Road Traffic Control System through Unified Modeling Language

A new approach to the design of adaptive automatic control systems for a short-range gas turbine engine

The paper presents a new approach to the management of power plants by unmanned aerial vehicles, provides a structural diagram of the proposed automatic control systems of a gas turbine engine, presents preliminary results of modeling.

LPV design of adaptive integrated control for road vehicles

AbstractThe paper presents a multi-layer supervisory architecture for the design of adaptive integrated control systems in road vehicles. The performance specifications are guaranteed by the local LPV (Linear Parameter Varying) controllers, while the coordination of these components is provided by the supervisor. Monitoring components provide the supervisor with information needed to make decisions about the necessary interventions into the vehicle motion and guarantee the robust operation of the vehicle. In the proposed architecture the supervisor and the components communicate through a well-defined interface. This interface uses the monitoring signals as additional scheduling variables of the individual LPV controllers introduced to distinguish the performances that correspond to different operational modes. The advantage of this architecture is that local LPV controllers are designed independently provided that the monitoring signals are taken into consideration in the formalization of their performance specifications.

Modeling and Model Reference Adaptive Control of Aircraft with Asymmetric Damage

This paper addresses some fundamental issues in adaptive control of aircraft with struc- tural damage. It presents a thorough study of linearized aircraft models with damage to obtain new details of system descriptions, such as coupling and partial derivatives of lateral and longitudinal dynamics. A detailed study of system invariance under damage conditions is performed for generic aircraft models to obtain key system characterizations for model reference adaptive control (MRAC), such as infinite zero structure and signs of high frequency gain matrices. A comprehensive study of multivariable MRAC systems in the presence of damage is performed to obtain critical design specifications for adaptive flight control, such as system and controller parametrizations and adaptive parameter up- date laws. Both analytical and simulation results are given to illustrate the design and performance of adaptive control systems for aircraft flight control. Adaptive control of aircraft in the presence of damage has been an important topic in the research of flight control design for aircraft safety. Damage can cause uncertain parametric and structural variations, which requires new aircraft modeling and control approaches. In Reference (1), a study of aircraft dynamics with damage is presented, and a neural network based adaptive control algorithm is introduced for control of aircraft in the presence of structure uncertainties. In (2), equations of motion are introduced in detail for aircraft with asymmetric mass loss. In (3), we introduced a nonlinear aircraft model with partial wing damage, and illustrated linearization of such a model. In (4), real time identification of a damaged aircraft model is studied. A two-step identification process is introduced, which consists of an aircraft state estimation phase and an aerodynamic model identification step. With such a two-step process, the nonlinear part of the model identification is isolated in the first phase, and the aerodynamic parameter identification procedure is simplified to a linear one. A hybrid adaptive control method is proposed in (5) for control of aircraft with damage. The control design is based on a neural network parameter estimation blended with a direct adaptive law. A stability and convergence analysis is presented for this adaptive control methodology. For accommodating unknown changes in the structure and parameters, multivariable MRAC designs offer many advantages. In (6), we introduced an MRAC design based on the LDS decomposition of the high frequency gain matrix for the control of aircraft with multiple wing damage. The key design conditions are that, both the nominal and post-damage systems should have a uniform known modified interactor matrix, and the leading principal minors of their high frequency gain matrices should be nonzero with their signs unchanged. In (7), we studied linearization of nonlinear aircraft models under damage conditions and designed a multivariable MRAC scheme which does not require the knowledge of the signs of the high frequency gain matrix. Potential extension to aircraft flight control systems with changing signs of the high frequency gain matrix remains a topic of future research.

Output feedback strict passivity of discrete-time nonlinear systems and adaptive control system design with a PFC

In this paper, a passivity-based adaptive output feedback control for discrete-time nonlinear systems is considered. Output Feedback Strictly Passive (OFSP) conditions in order to design a stable adaptive output control system will be established. Further, a design scheme of a parallel feedforward compensator (PFC), which is introduced in order to realize an OFSP controlled system, will be provided and an adaptive output feedback control system design scheme with a PFC will be proposed.

Design and implementation of parameterized adaptive cruise control: An explicit model predictive control approach

The combination of different characteristics and situation-dependent behavior cause the design of adaptive cruise control (ACC) systems to be time consuming. This paper presents a systematic approach for the design of a parameterized ACC, based on explicit model predictive control. A unique feature of the synthesized ACC is its parameterization in terms of key characteristics, which, after the parameterization, makes it easy and intuitive to tune, even for the driver. The effectiveness of the design approach is demonstrated using simulations for relevant traffic scenarios, including Stop-&-Go. On-the-road experiments show the proper functioning of the synthesized ACC.

Indirect Adaptive Self-structuring Fuzzy Neural Network Control System

To obtain a high control performance of adaptive fuzzy control systems, the stability guarantee should be made stricter to reduce the approximation error of the system. Avoiding the system becomes complex, this study aims to design a kind of adaptive fuzzy control system that realizes compatibility of concise stability guarantee and high control performance, and it proposes the adaptive fuzzy control system design method of the indirect controller approximation type designed based on the self-structuring fuzzy neural network. It is evaded that the approximation error element that was not able to be removed by adaptive law influences the entire control input directly, and influences are distributed, by composing an indirect type control system. Additionally, it aims at the improvement of the control performance by compensating this remaining approximation error by the robust control input element in the control input. Finally, the effectiveness of this method is verified by the computation simulation of the cart-pole system control.

Model Free Design of Parallel Feedforward Compensator for Adaptive Output Feedback Control via FRIT with T-S Fuzzy Like Model

In this paper, we propose a design method of parallel feedforward compensator (PFC) for an adaptive output feedback control. In order to obtain a desired PFC which realizes an ASPR augmented controlled plant, PFC parameters are adjusted by the fictitious reference iterative tuning (FRIT) method so as to exist a feedback gain such that the output of the augmented closed loop system with the PFC track the output of the given SPR model by optimizing the performance function that consists of input-output data by T-S fuzzy like model. The proposed PFC design strategy will be applied to adaptive output feedback control system design.

Design of discrete time adaptive PID control systems with parallel feedforward compensator

This paper deals with the design of an adaptive PID control system with a parallel feedforward compensator (PFC) for discrete-time SISO systems and its application to water level control of a 3-tank system. The proposed method utilizes the characteristics of almost strict positive realness (ASPR) of the controlled plant. A conventional design scheme of a PFC which realizes an ASPR augmented controlled plant is also proposed. Further it is shown that the introduction of an internal model improves the control performance of the control system with the PFC. The effectiveness of the proposed method is confirmed through water level control experiments on a three-tank SISO system.

Adaptive controller design for uncertain fuzzy systems using variable structure control approach

Based on the variable structure control (VSC) theory, we develop an adaptive fuzzy control system design method for uncertain Takagi–Sugeno fuzzy models with norm-bounded uncertainties. We relax the restrictive assumptions that each nominal local system model shares the same input channel and the norm bound of the uncertainty is known, which are usually invoked in the traditional VSC-based fuzzy control design methods. As the local controller we use a VSC law with a switching feedback control term and an adaptation law to account for the norm-bounded uncertainties. In terms of LMIs, we derive a sufficient condition for the existence of linear sliding surfaces guaranteeing the asymptotic stability. We present an LMI characterization of such sliding surfaces. We also give an LMI-based design algorithm, together with a numerical design example.

Adaptive PID control system design for non-linear systems

This paper deals with the design of an adaptive PID control system for non-linear systems with disturbances. The proposed PID method utilises the output feedback exponential passivity (OFEP) characteristics of the controlled system. It is widely recognised that one can easily design an adaptive output feedback control system for OFEP systems, however we propose a robust PID control based on the OFEP properties of the non-linear systems. Further, a practical control system design with a parallel feed-forward compensator (PFC) is also shown and the effectiveness of the proposed method is confirmed through experiments on a magnetic levitation system.

Adaptive PID Control System Design Based on ASPR-ness

Adaptive PID Control System Design Based on ASPR-ness

Adaptive Control System Design for Discontinuous Systems

Adaptive Control System Design for Discontinuous Systems

Nonlinear adaptive control system design and experiment for a 3-DOF model helicopter

This paper deals with model following control of a model helicopter with three degree-of-freedom. Since the decoupling matrix is singular, a nonlinear structure algorithm is used to design the controller. Furthermore, since the model dynamics are described linearly by unknown system parameters, a well-known parameter estimation technique is introduced. The integral type of estimation model is proposed here since the use of the derivative type of model cannot obtain the desired estimation result. The experimental results show the effectiveness of the proposed method.

Design, tuning, and evaluation of a full-range adaptive cruise control system with collision avoidance

This paper describes the design, tuning, and evaluation of a full-range adaptive cruise control (ACC) system with collision avoidance (CA). The control scheme is designed to improve drivers’ comfort during normal, safe-driving situations and to completely avoid rear-end collision in vehicle-following situations. Driving situations are divided into safe, warning, and dangerous modes. Three different control strategies have been proposed, depending on the driving situation. The driving situations are determined using a non-dimensional warning index and the time-to-collision (TTC). The control parameters of the proposed ACC/CA system are tuned by a confusion-matrix method using manual-driving data in no-crashing driving situations. The vehicle-following characteristics of the subject vehicle were compared to real-world, manual-driving data. Finally, the ACC/CA system was also implemented in a real vehicle and tested in both safe-traffic and severe-braking situations. It is shown that the proposed control strategy can provide natural following performance that is similar to human manual-driving in both high-speed driving and low-speed stop-and-go situations. Furthermore, it can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.