Adaptive Dynamic Control Research Articles

Adaptive dynamic surface neural network control for nonstrict-feedback uncertain nonlinear systems with constraints

This paper presents an adaptive dynamic surface neural network control for a class of nonstrict-feedback uncertain nonlinear systems subjected to input saturation, dead zone and output constraint. The problem of input saturation is solved by designing an anti-windup compensator, and the issue of output constraint is addressed by introducing tan-type Barrier Lyapunov function. Furthermore, based on adaptive backstepping technique, a series of novel stabilizing functions are derived. First-order sliding mode differentiator is introduced into backstepping design to obtain the first-order derivative of virtual control. The real control input is obtained using dead-zone inverse method. It is proved that the proposed control scheme can achieve finite time convergence of the output tracking error into a small neighbor of the origin and guarantee all the closed-loop signals are bounded. Simulation results demonstrate the effectiveness of the proposed control scheme.

0.45 v and 18 μA/MHz MCU SOC with Advanced Adaptive Dynamic Voltage Control (ADVC)

An ultra-low-power MicroController Unit System-on-Chip (MCU SOC) is described with integrated DC to DC power management and Adaptive Dynamic Voltage Control (ADVC) mechanism. The SOC, designed and fabricated in a 40 nm ULP standard CMOS technology, includes the complete Synopsys ARC EM5D core MCU, featuring a full set of DSP instructions and minimizing energy consumption at a wide range of frequencies: 312 K–80 MHz. A number of unique low voltage digital libraries, comprising of approximately 300 logic cells and sequential elements, were used for the MCU SOC design. On-die silicon sensors were utilized to continuously change the operating voltage to optimize power/performance for a given frequency and environmental conditions, and also to resolve yield and life time problems, while operating at low voltages. A First Fail (FFail) mechanism, which can be digitally and linearly controlled with up to 8 bits, detects the failing SOC voltage at a given frequency. The core operates between 0.45–1.1 V volts with a direct battery connection for an input voltage of 1.6–3.6 V. Measurement results show that the peak energy efficiency is 18μW/MHz. A comparison to state-of-the-art commercial SOCs is presented, showing a 3–5× improved current/DMIPS (Dhrystone Million Instructions per second) compared to the next best chip.

CHAM: Improving Prefetch Efficiency Using a Composite Hierarchy-Aware Method

Hardware prefetching has always been a crucial mechanism to improve processor performance. However, an efficient prefetch operation requires a guarantee of high prefetch accuracy; otherwise, it may degrade system performance. Prior studies propose an adaptive priority controlling method to make better use of prefetch accesses, which improves performance in two-level cache systems. However, this method does not perform well in a more complex memory hierarchy, such as a three-level cache system. Thus, it is still necessary to explore the efficiency of prefetch, in particular, in complex hierarchical memory systems. In this paper, we propose a composite hierarchy-aware method called CHAM, which works at the middle level cache (MLC). By using prefetch accuracy as an evaluation criterion, CHAM improves the efficiency of prefetch accesses based on (1) a dynamic adaptive prefetch control mechanism to schedule the priority and data transfer of prefetch accesses across the cache hierarchical levels in the runtime and (2) a prefetch efficiency-oriented hybrid cache replacement policy to select the most suitable policy. To demonstrate its effectiveness, we have performed extensive experiments on 28 benchmarks from SPEC CPU2006 and two benchmarks from BioBench. Compared with a similar adaptive method, CHAM improves the MLC demand hit rate by 9.2% and an improvement of 1.4% in system performance on average in a single-core system. On a 4-core system, CHAM improves the demand hit rate by 33.06% and improves system performance by 10.1% on average.

Dynamic modeling and adaptive robust boundary control of a flexible robotic arm with 2‐dimensional rigid body rotation

SummaryThis paper investigates the control of a single‐link flexible robot manipulator with a tip payload appointed to rotate about 2 perpendicular axes in space. The control objective is to regulate the rigid body rotation of the manipulator with guaranteeing the stability of its vibration in the presence of exogenous disturbances. To achieve this, a Lyapunov‐based control design procedure is used and accomplished in some steps. First, the partial differential equation (PDE) dynamic model governing the rigid‐flexible hybrid motion of the arm is derived by applying Hamilton's principle. Next, based on the developed PDE model, an adaptive robust boundary control is established using the Lyapunov redesign approach. To this end, an adaptation mechanism is proposed so that the robust boundary control gains are dynamically updated online and there is no need for prior knowledge of disturbance upper bounds. The actuators and sensors are fully implemented at the arm boundary without using distributed actuators or sensors. Furthermore, in order to avoid control errors resulting from the spillover, control design is directly based on infinite‐dimensional PDE model without resorting to model truncation. Simulation results illustrate the efficacy of the considered method.

Network Control System (NCS) for Performance Improvement of Dual Converter Power Supply System Using Adaptive Inverse Dynamic Mode (AIDMC) Control Technique

With recent advances in power electronics, dual converter power supply based electric variable-speed drives are significantly used in many industries uses. Power electronic motor drivers are becoming able to efficiently read the inflexible characteristics of DC motor to prerequisites the load. By controlling the input armature voltage, the DC motor speed automatically changed. Half-bridge converter, semi converter, full bridge converter and dual converter are some of the thyristor controlled rectifier circuits are widely used in variable speed drives. In This work presents single phase dual converter power supply system based on adaptive inverse dynamic mode control (AIDMC) technique. The efficient dual converter control solution for industrial network control system (NCS) is proposed based on the industrial grade requirements, designed for low to high voltage operation. As the era of connecting the devices with the cloud is being increased gradually, the proposed method uses an NCS protocol for monitoring as well as controlling the dual converter system. The proposed method provides us the control over forward and reverse rotation, forward and reverse regeneration. From the simulation results, the proposed result offers variable DC voltage which is capable of four quadrant operation of the drive in a speed-torque plane by using MATLAB Simulink environment. A hardware setup also developed to validate the simulation. Over 96% accuracy achieved full load condition for proposed dual converter power supply system based on AIDMC controller.

An Adaptive Dynamic Controller for Quadrotor to Perform Trajectory Tracking Tasks

This work proposes an adaptive dynamic controller to guide an unmanned aerial vehicle (UAV) when accomplishing trajectory tracking tasks. The controller structure consists of a kinematic controller that generates reference commands to a dynamic compensator in charge of changing the reference commands according to the system dynamics. The final control actions thus generated are then sent to the UAV to make it to track an arbitrary trajectory in the 3D space. The parameters of the dynamic compensator are directly updated during navigation, configuring a directly updated self-tuning regulator with input error, aiming at reducing the tracking errors, thus improving the system performance in task accomplishment. After describing the control system thus designed, its stability is proved using the Lyapunov theory. To validate the proposed system simulations and real experiments were run, some of them are reported here, whose results demonstrate the effectiveness of the proposed control system and its good performance, even when the initial values of the parameters associated to the dynamic model of the UAV are completely unknown. One of the conclusions, regarding the results obtained, is that the proposed system can be used as if it were an on-line identification subsystem, since the parameters converge to values that effectively represent the UAV dynamics.

Hybrid Scheduling and Quantized Output Feedback Control for Networked Control Systems

A novel co-design scheme of hybrid scheduling strategy, adaptive logarithmic quantizer and dynamic robust H-infinity output feedback controller for a class of networked control system (NCS)with communication constraints and time delay is proposed. The hybrid scheduling scheme integrates dead zone scheduling and Try Once Discard (TOD) scheduling so as to get the stronger adaptability and flexibility than the single scheduling. In this scheme, dead zone scheduling which updates the threshold according to mode-dependent control strategy is used for single node of NCS to reduce the network bandwidth utilization while TOD scheduling is used for the whole node of NCS in order to meet the requirements of communication constraints and guarantee the overall system performance.We develop the integrated design for the hybrid scheduling strategy, adaptive quantizer and dynamic robust output feedback controller to maintain asymptotic stability of the closed-loop NCS by using the multiple-Lyapunov function and switched system theory. The proposed method can improve the the quality of service (QoS) meanwhile ensure the quality of control (QoC) of overall systems, which make a better trade-off between network utilization and control performance. An simulation example demonstrates the efficiency of the proposed method.

Mathematical modelling of active safety system functions as tools for development of driverless vehicles

This paper is dedicated to a solution of the issue of synthesis of the vehicle longitudinal dynamics control functions (acceleration and deceleration control) based on the element base of the vehicle active safety system (ESP) – driverless vehicle development tool. This strategy helps to reduce time and complexity of integration of autonomous motion control systems (AMCS) into the vehicle architecture and allows direct control of actuators ensuring the longitudinal dynamics control, as well as reduction of time for calibration works. The “vehicle+wheel+road” longitudinal dynamics control is complicated due to the absence of the required prior information about the control object. Therefore, the control loop becomes an adaptive system, i.e. a self-adjusting monitoring system. Another difficulty is the driver’s perception of the longitudinal dynamics control process in terms of comfort. Traditionally, one doesn’t pay a lot of attention to this issue within active safety systems, and retention of vehicle steerability, controllability and stability in emergency situations are considered to be the quality criteria. This is mainly connected to its operational limits, since it is activated only in critical situations. However, implementation of the longitudinal dynamics control in the AMCS poses another challenge for the developers – providing the driver with comfortable vehicle movement during acceleration and deceleration – while the possible highest safety level in terms of the road grip is provided by the active safety system (ESP). The results of this research are: universal active safety system – AMCS interaction interface; block diagram for the vehicle longitudinal acceleration and deceleration control as one of the active safety system’s integrated functions; ideology of adaptive longitudinal dynamics control, which enables to realize the deceleration and acceleration requested by the AMCS; algorithms synthesised; analytical experiments proving the efficiency and practicability of the chosen concept.

Robust Adaptive Nonlinear Dynamic Inversion Control for an Air-breathing Hypersonic Vehicle

This paper presents a robust adaptive nonlinear dynamic inversion control approach for the longitudinal dynamics of an air-breathing hypersonic vehicle. The proposed approach adopts a fast adaptation law using high-gain learning rate, while a low-pass filter is synthesized with the modified adaptive scheme to filter out the high-frequency content of the estimates. This modified high-gain adaptive scheme achieves a good transient process and a nice robust property with respect to parameter uncertainties, without exciting high-frequency oscillations. Based on input-output linearization, the nonlinear hypersonic dynamics are transformed into equivalent linear systems. Therefore, the pole placement technique is applied to design the baseline nonlinear dynamic inversion controller. Finally, the simulation results of the modified adaptive nonlinear dynamic inversion control law demonstrate the proposed control approach provides robust tracking of reference trajectories.

Dynamic Output Feedback Control for Nonlinear Uncertain Systems with Multiple Time-Varying Delays

This paper addresses the adaptive dynamic output-feedback control problem for a class of nonlinear discrete-time systems with multiple time-varying delays. First, the guaranteed cost function is introduced for the nonlinear system to reduce the effect of the time-varying delays. Secondly, in order to deal with the multiple time-varying delays, the nonlinear system is decomposed into two subsystems. Then the compensator is designed for the first subsystem, and the adaptive dynamic output-feedback controller is constructed based on the subsystems. By introducing the new discrete Lyapunov-Krasovskii functional, it can be seen that the solutions of the resultant closed-loop system converge to an adjustable bounded region. Finally, the simulations are performed to show the effectiveness of the proposed methods.

Adaptive dynamic control allocation for over-actuated dynamic positioning system based on backstepping method in case of thruster faults

The objective of the research considered in this paper is dynamic positioning of a nonlinear over-actuated marine vessel in the presence of limited information about thruster forces. First, the adaptive backstepping method is used to estimate the input matrix which will compensate partial loss of actuator effectiveness in the presence of actuator dynamics. Then, the adaptive commanded virtual forces and moment are allocated into individual thrusters by employing the control allocation algorithm to compensate total faults. The effectiveness of the proposed control scheme is demonstrated by simulations involving a redundant set of actuators, when actuators lose partially their efficiency or failed.

Dynamic modeling, adaptive control and energy performance simulation of a hybrid hydronic space heating system

A dynamic model of a hybrid hydronic heating system has been developed. The overall model consists of a boiler, a heat exchanger, a ground loop heat pump, a ground loop heat exchanger, baseboard heaters (convector–radiators), and radiant floor hydraulic piping system. Two control strategies for improving the overall system performance were explored: (1) a conventional proportional-integral (PI) control and (2) an adaptive gain control. The simulation results showed that the performance of the adaptive controller is better than the fixed gain PI controller in disturbance rejection and stability. Energy simulations under three different operating strategies were conducted: (1) a fixed set-point PI control, (2) an outdoor air temperature reset control, and (3) an optimal set-point adaptive PI control. It was shown that the outdoor temperature reset strategy can save 4.5 and 19.9% energy under cold day and mild day conditions compared to the fixed set-point PI control strategy. The optimal adaptive PI control strategy resulted in higher energy savings of 6.6 and 22% as compared to the PI control under cold and mild day conditions, respectively. Practical application: Energy efficiency and sustainability are a major issue of importance in the design and operation of space heating systems. The proposed hybrid system combines a ground-source heat pump and a hot water boiler for space heating of both residential and commercial building applications. The heating system consists of radiant floor piping for the residential zones and hot water baseboard heaters (convector–radiators) for the commercial zones. An energy optimal adaptive control strategy is designed to improve energy efficiency and temperature control performance of the hybrid system. The control strategy is simple and can be implemented on the existing building control systems.

Dynamic Analysis and Adaptive Sliding Mode Controller for a Chaotic Fractional Incommensurate Order Financial System

In this study, the dynamic behavior and chaos control of a chaotic fractional incommensurate-order financial system are investigated. Using well-known tools of nonlinear theory, i.e. Lyapunov exponents, phase diagrams and bifurcation diagrams, we observe some interesting phenomena, e.g. antimonotonicity, crisis phenomena and route to chaos through a period doubling sequence. Adopting largest Lyapunov exponent criteria, we find that the system yields chaos at the lowest order of [Formula: see text]. Next, in order to globally stabilize the chaotic fractional incommensurate order financial system with uncertain dynamics, an adaptive fractional sliding mode controller is designed. Numerical simulations are used to demonstrate the effectiveness of the proposed control method.

Adaptive synchronisation for a class of output‐coupling complex networks with output feedback nodes

This study investigates the synchronisation problem of a class of output-coupling complex networks whose nodes are in the output feedback form and contain unknown non-linear functions. To tackle the unknown parameters in the non-linear nodes, adaptive dynamic output feedback controllers are designed. By employing the linear matrix inequality technique, several sufficient conditions are derived to ensure the global asymptotic synchronisation for the resulting closed-loop systems. An illustrative numerical example is given to show the effectiveness of the main results.

Multidesign Integration Based Adaptive Actuator Failure Compensation Control for Two Linked 2WD Mobile Robots

This paper develops an actuator failure compensation control scheme for two linked mobile robots. The kinematic and dynamic models of two robots with a physical link that is employed to deal with actuator failures for two-wheel drive mobile robots are proposed. Then, a kinematic controller is designed, which is a virtual one. Based on this controller, multiple adaptive dynamic control signals are designed to cover all possible failure cases. By combining these dynamic control signals, the dynamic controller is designed, which ensures desired system stability and asymptotic tracking properties. Finally, simulation results verify the effectiveness of the proposed adaptive actuator failure compensation scheme.

Adaptive decentralized fuzzy output feedback tracking control for a class of nonlinear large-scale systems with input delays

In this paper, the decentralized tracking control problem of nonlinear large-scale systems with immeasurable states and unknown nonlinearities in each subsystem and their interconnections subject to input delays is proposed. Based on the universal approximation properties of fuzzy systems, a fuzzy observer is designed to estimate the inaccessible states of the system. Subsequently, by defining the appropriate change of coordinates and employing the backstepping technique, an adaptive fuzzy backstepping output feedback control scheme is proposed for nonlinear interconnected systems subject to input delays. Owing to the problem of so-called explosion of complexity that inherently arises in the design procedures of the traditional backstepping technique, an adaptive fuzzy dynamic surface output feedback control approach is also presented for this class of large-scale systems. Moreover, it is shown that the two proposed adaptive decentralized fuzzy observer-based control approaches ensure all the signals of the closed loop system uniformly ultimately bounded and the norms of the tracking errors as well as the norms of the observation errors can converge to small desired values by proper selection of the design parameters. Finally, the theoretic achievements are carried out on the chemical reactor recycle system to illustrate and compare the effectiveness of the two proposed approaches.

Adaptive fuzzy dynamic surface tracking control for a class of nonlinear systems with unknown distributed time delays and backlash-like hysteresis

In this article, an adaptive fuzzy backstepping dynamic surface control approach is developed for a class of nonlinear systems with unknown backlash-like hysteresis and unknown state discrete and distributed time-varying delays. Fuzzy logic systems are used to approximate the unknown nonlinear functions and a fuzzy state observer is designed for estimating the immeasurable states. Then, by combining the backstepping technique and the appropriate Lyapunov–Krasovskii functionals with the dynamic surface control approach, the output-feedback adaptive fuzzy tracking controller is designed. The main advantages of this article are (i) the existence of the state discrete and distributed time-varying delays such that the investigated systems are more general than that of the existing results, (ii) the proposed control scheme can eliminate the problem of “explosion of complexity” inherent in the backstepping design method, and (iii) for the nth nonlinear system, only one fuzzy logic system is used to approximate the unknown continuous time-varying delay functions since all of them are lumped into one unknown nonlinear function, which makes our design scheme easier to be implemented in practical applications. It is proven that the proposed design method is able to guarantee that all the signals in the closed-loop system are bounded and the tracking error can converge to a small neighborhood of origin with an appropriate choice of design parameters. Finally, the simulation results demonstrate the effectiveness of the proposed approach.

Boundary Control of 2-D Burgers' PDE: An Adaptive Dynamic Programming Approach.

In this paper, an adaptive dynamic programming-based near optimal boundary controller is developed for partial differential equations (PDEs) modeled by the uncertain Burgers' equation under Neumann boundary condition in 2-D. Initially, Hamilton-Jacobi-Bellman equation is derived in infinite-dimensional space. Subsequently, a novel neural network (NN) identifier is introduced to approximate the nonlinear dynamics in the 2-D PDE. The optimal control input is derived by online estimation of the value function through an additional NN-based forward-in-time estimation and approximated dynamic model. Novel update laws are developed for estimation of the identifier and value function online. The designed control policy can be applied using a finite number of actuators at the boundaries. Local ultimate boundedness of the closed-loop system is studied in detail using Lyapunov theory. Simulation results confirm the optimizing performance of the proposed controller on an unstable 2-D Burgers' equation.

Composite Path Tracking Control for Tractor–Trailer Vehicles Via Constrained Model Predictive Control and Direct Adaptive Fuzzy Techniques

Tractor–trailer vehicles will suffer from nonholonomic constraint, uncertain disturbance, and various physical limits, when they perform path tracking maneuver autonomously. This paper presents a composite path tracking control strategy to tackle the various problems arising from not only vehicle kinematic but also dynamic levels via two powerful control techniques. The proposed composite control structure consists of a model predictive control (MPC)-based posture controller and a direct adaptive fuzzy-based dynamic controller, respectively. The former posture controller can make the underactuated trailer midpoint follow an arbitrary reference trajectory given by the earth-fixed frame, as well as satisfying various physical limits. Meanwhile, the latter dynamic controller enables the vehicle velocities to track the desired velocities produced by the former one, and the global asymptotical convergence of dynamic controller is strictly guaranteed in the sense of Lyapunov stability theorem. The simulation results illustrate that the presented control strategy can achieve a coordinated control effect for the sophisticated tractor–trailer vehicles, thereby enhancing their movement performance in complex environments.

Design of LCC HVDC wide‐area emergency power support control based on adaptive dynamic surface control

In AC–DC parallel systems, line-commutated-converter (LCC)-based high-voltage direct-current (HVDC) emergency control strategy can improve the stability of the power system. This study proposes an LCC HVDC emergency control strategy that utilises the global information measured by wide-area measurement systems. The design of the proposed LCC HVDC emergency control strategy takes advantage of dynamic surface control and adaptive control. The Lyapunov stability analysis is used to prove that the AC–DC parallel system is uniformly ultimately bounded in the presence of the uncertainties. A two-area four-generator AC–DC parallel system is developed in PSCAD/EMTDC to verify the effectiveness and correctness of the proposed strategy. Simulation results show that the proposed LCC HVDC emergency control strategy can improve the stability of an AC–DC parallel system and is robust. Its superiority is demonstrated by comparing the proposed method with controllers designed using backstepping technique and pole placement technique.