Showing papers on "PID controller published in 2007"

Design and control of quadrotors with application to autonomous flying

Abstract: This thesis is about modelling, design and control of Miniature Flying Robots (MFR) with a focus on Vertical Take-Off and Landing (VTOL) systems and specifically, micro quadrotors. It introduces a mathematical model for simulation and control of such systems. It then describes a design methodology for a miniature rotorcraft. The methodology is subsequently applied to design an autonomous quadrotor named OS4. Based on the mathematical model, linear and nonlinear control techniques are used to design and simulate various controllers along this work. The dynamic model and the simulator evolved from a simple set of equations, valid only for hovering, to a complex mathematical model with more realistic aerodynamic coefficients and sensor and actuator models. Two platforms were developed during this thesis. The first one is a quadrotor-like test-bench with off-board data processing and power supply. It was used to safely and easily test control strategies. The second one, OS4, is a highly integrated quadrotor with on-board data processing and power supply. It has all the necessary sensors for autonomous operation. Five different controllers were developed. The first one, based on Lyapunov theory, was applied for attitude control. The second and the third controllers are based on PID and LQ techniques. These were compared for attitude control. The fourth and the fifth approaches use backstepping and sliding-mode concepts. They are applied to control attitude. Finally, backstepping is augmented with integral action and proposed as a single tool to design attitude, altitude and position controllers. This approach is validated through various flight experiments conducted on the OS4.

An Algorithm for Stabilization of Fractional-Order Time Delay Systems Using Fractional-Order PID Controllers

Abstract: This technical note presents a solution to the problem of stabilizing a given fractional-order system with time delay using fractional-order PllambdaDmu controllers. It is based on determining a set of global stability regions in the (kp, Ki, Kd)-space corresponding to the fractional orders lambda and mu in the range of (0, 2) and then choosing the biggest global stability region in this set. This method can be also used to find the set of stabilizing controllers that guarantees prespecified gain and phase margin requirements. The algorithm is simple and has reliable result which is illustrated by an example, and, hence, is practically useful in the analysis and design of fractional-order control systems.

Methods and apparatus for control using control devices that provide a virtual machine environment and that communicate via an ip network

Abstract: The invention provides improved methods and apparatus for control using field and control devices that provide a virtual machine environment and that communicate via an IP network. By way of non-limiting example, such field device can be an “intelligent” transmitter or actuator that includes a low power processor, along with a random access memory, a read-only memory, FlashRAM, and a sensor interface. The processor can execute a real-time operating system, as well as a Java virtual machine (JVM). Java byte code executes in the JVM to configure the field device to perform typical process control functions, e.g., for proportional integral derivative (PID) control and signal conditioning. Control networks can include a plurality of such field and control devices interconnected by an IP network, such as an Ethernet.

Hardware Implementation of a Real-Time Neural Network Controller With a DSP and an FPGA for Nonlinear Systems

Abstract: In this paper, we implement the intelligent neural network controller hardware with a field programmable gate array (FPGA)-based general purpose chip and a digital signal processing (DSP) board to solve nonlinear system control problems. The designed intelligent control hardware can perform real-time control of the backpropagation learning algorithm of a neural network. The basic proportional-integral-derivative (PID) control algorithms are implemented in an FPGA chip and a neural network controller is implemented in a DSP board. By using a high capacity of an FPGA chip, the additional hardware such as an encoder counter and a pulsewidth modulation (PWM) generator is implemented in a single FPGA chip. As a result, the controller becomes cost effective. It was tested for controlling nonlinear systems such as a robot finger and an inverted pendulum on a moving cart to show performance of the controller

Bacterial Foraging Technique-Based Optimized Active Power Filter for Load Compensation

Abstract: The conventional method of obtaining the coefficients of proportional plus integral (PI) controllers for the active power filter utilizes a linear model of the PWM inverter. The values so obtained may not give satisfactory results for a wide variation in operating conditions. This paper presents a new algorithm based on the foraging behavior of E-coli Bacteria in the human intestine, to optimize the coefficients of the PI controller. Through the simulation results, it is observed that the dynamic response of the bacterial foraging PI (BF-PI) controller is quite satisfactory. The proposed BF technique is compared with the genetic algorithm (GA) and found to converge faster than GA to reach the global optimum solution

A New Digital Control Algorithm to Achieve Optimal Dynamic Performance in DC-to-DC Converters

Abstract: In this paper, a new control algorithm is proposed to achieve optimal dynamic performance for dc-to-dc converters under a load current change and for a given set of circuit parameters, such as the output inductor, output capacitor, switching frequency, input voltage, and output voltage. Using the concept of capacitor charge balance, the proposed algorithm predicts the optimal transient response for a dc-to-dc converter during a large signal load current change. During steady state operation, conventional current mode proportional-integral-derivative (PID) is used. During large signal transient conditions, the new control algorithm takes over. The equations needed to calculate the transient time and the required duty cycle series are presented. By using the proposed algorithm, the optimal transient performances, including the smallest output voltage overshoot/undershoot and the shortest recovery time, is achieved. In addition, since the large signal dynamic response of the power converter is successfully predicted, the large signal stability is guaranteed. Experimental results show that the proposed method produces superior dynamic performance over a conventional current mode PID controller.

IMC−PID Controller Design for Improved Disturbance Rejection of Time-Delayed Processes

Abstract: The IMC-PID tuning rules demonstrate good set-point tracking but sluggish disturbance rejection, which becomes severe when a process has a small time-delay/time-constant ratio. In this study, an optimal internal model control (IMC) filter structure is proposed for several representative process models to design a proportional-integral-derivative (PID) controller that produces an improved disturbance rejection response. The simulation studies of several process models show that the proposed design method provides better disturbance rejection for lag-time dominant processes, when the various controllers are all tuned to have the same degree of robustness according to the measure of maximum sensitivity. The robustness analysis is conducted by inserting a perturbation in each of the process parameters simultaneously, with the results demonstrating the robustness of the proposed controller design with parameter uncertainty. A closed-loop ‚

Stabilization using fractional-order PI and PID controllers

Abstract: This paper presents a solution to the problem of stabilizing a given fractional dynamic system using fractional-order PIλ and PIλDμ controllers. It is based on plotting the global stability region in the (kp, ki)-plane for the PIλ controller and in the (kp, ki, kd)-space for the PIλDμ controller. Analytical expressions are derived for the purpose of describing the stability domain boundaries which are described by real root boundary, infinite root boundary and complex root boundary. Thus, the complete set of stabilizing parameters of the fractional-order controller is obtained. The algorithm has a simple and reliable result which is illustrated by several examples, and hence is practically useful in the analysis and design of fractional-order control systems.

Design and Implementation of Modular FPGA-Based PID Controllers

Abstract: In this paper, modular design of embedded feedback controllers using field-programmable gate array (FPGA) technology is studied. To this end, a novel distributed-arithmetic (DA)-based proportional-integral-derivative (PID) controller algorithm is proposed and integrated into a digital feedback control system. The DA-based PID controller demonstrates 80% savings in hardware utilization and 40% savings in power consumption compared to the multiplier-based scheme. It also offers good closed-loop performance while using less resources, resulting in cost reduction, high speed, and low power consumption, which is desirable in embedded control applications. The complete digital control system is built using commercial FPGAs to demonstrate the efficiency. The design uses a modular approach, so that some modules can be reused in other applications. These reusable modules can be ported into Matlab/Simulink as Simulink blocks for hardware/software cosimulation or integrated into a larger design in the Matlab/Simulink environment to allow for rapid prototyping applications.

Identification and Real-Time Control of an Electrohydraulic Servo System Based on Nonlinear Backstepping

Abstract: This paper studies the identification and the real-time control of an electrohydraulic servo system. The control strategy is based on the nonlinear backstepping approach. Emphasis is essentially on the tuning parameters effect and on how it influences the dynamic behavior of the errors. While the backstepping control ensures the global asymptotic stability of the system, the tuning parameters of the controller, nonetheless, do greatly affect the saturation and chattering in the control signal, and consequently, the dynamic errors. In fact, electrohydraulic systems are known to be highly nonlinear and non-differentiable due to many factors, such as leakage, friction, and especially, the fluid flow expression through the servo valve. These nonlinear terms appear in the closed loop dynamic errors. Their values are so large that in the presence of a poor design, they can easily overwhelm the effect of the controller parameters. Backstepping is used here because it is a powerful and robust nonlinear strategy. The experimental results are compared to those obtained with a real-time proportional-integral-derivative (PID) controller, to prove that classic linear controllers fail to achieve a good tracking of the desired output, especially, when the hydraulic actuator operates at the maximum load. Before going through the controller design, the system parameters are identified. Despite the nonlinearity of the system, identification is based on the recursive least squares method. This is done by rewriting the mathematical model of the system in a linear in parameters (LP) form. Finally, the experimental results will show the effectiveness of the proposed approach in terms of guaranteed stability and zero tracking error

Hybrid Theory-Based Time-Optimal Control of an Electronic Throttle

Abstract: An electronic throttle is a dc-motor-driven valve that regulates air inflow into the combustion system of the engine. The throttle control system should ensure fast and accurate reference tracking of the valve plate angle while preventing excessive wear of the throttle components by constraining physical variables to their normal-operation domains. These high-quality control demands are hard to accomplish since the plant is burdened with strong nonlinear effects of friction and limp-home nonlinearity. In this paper, the controller synthesis is performed in discrete time by solving a constrained time-optimal control problem for the piecewise affine (PWA) model of the throttle. To that end, a procedure is proposed to model friction in a discrete-time PWA form that is suitable both for simulation and controller design purposes. The control action computation can, in general, be restated as a mixed-integer program. However, due to the small sampling time, solving such a program online (in a receding horizon fashion) would be very prohibitive. This issue is resolved by applying recent theoretical results that enable offline precomputation of the state-feedback optimal control law in the form of a lookup table. The technique employs invariant set computation and reachability analysis. The experimental results on a real electronic throttle are reported and compared with a tuned PID controller that comprises a feedforward compensation of the process nonlinearities. The designed time-optimal controller achieves considerably faster transient, while preserving other important performance measures, like the absence of overshoot and static accuracy within the measurement resolution

Optimal fast tracking observer bandwidth of the linear extended state observer

Abstract: In current industrial control applications, the proportional + integral + derivative (PID) control is still used as the leading tool, but constructing controller requires precise mathematical model of plant, and tuning the parameters of controllers is not simple to implement. Motivated by the gap between theory and practice in control problems, linear active disturbance rejection control (LADRC) addresses a set of control problems in the absence of precise mathematical models. LADRC has two parameters to be tuned, namely, a closed-loop bandwidth and observer bandwidth. The performance of LADRC depends on the quick convergence of a unique state observer, known as the extended state observer, proposed by Jinqing Han (1994). Only one parameter, observer bandwidth, significantly affects the tracking speed of extended state observer. This paper studies numerically the optimal fast tracking observer bandwidth and the absolute tracking error estimation for a class of non-linear and uncertain motion control probl...

Identification and Control for Heart Rate Regulation During Treadmill Exercise

Abstract: This paper proposes a novel integrated approach for the identification and control of Hammerstein systems to achieve desired heart rate profile tracking performance for an automated treadmill system. For the identification of Hammerstein systems, the pseudorandom binary sequence input is employed to decouple the identification of dynamic linear part from input nonlinearity. The powerful epsiv-insensitivity support vector regression method is adopted to obtain sparse representations of the inverse of static nonlinearity in order to obtain an approximate linear model of the Hammerstein system. An Hinfin controller is designed for the approximated linear model to achieve robust tracking performance. This new approach is successfully applied to the design of a computer-controlled treadmill system for the regulation of heart rate during treadmill exercise. Minimizing deviations of heart rate from a preset profile is achieved by controlling the speed of the treadmill. Both conventional proportional-integral-derivative (PID) control and the proposed approaches have been employed for the controller design. The proposed algorithm achieves much better heart rate tracking performance.

A PSO-Based Optimum Design of PID Controller for a Linear Brushless DC Motor

Abstract: This Paper presents a particle swarm optimization (PSO) method for determining the optimal proportional-integral- derivative (PID) controller parameters, for speed control of a linear brushless DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The brushless DC motor is modelled in Simulink and the PSO algorithm is implemented in MATLAB. Comparing with Genetic Algorithm (GA) and Linear quadratic regulator (LQR) method, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of a linear brushless DC motor.

A multi-crossover genetic approach to multivariable PID controllers tuning

Abstract: In this paper, we will propose a modified crossover formula in genetic algorithms (GAs), and use this method to determine PID controller gains for multivariable processes. It is well known that GA is globally optimal search method borrowing the concepts from biological evolutionary theory. In the traditional crossover fashion, only two parent chromosomes are usually used to be crossed by each other. The proposed algorithm, however, is designed to provide a more accurate adjusting direction for evolving offspring because of the use of multi-crossover genetic operations. Then we apply the innovative GA into the design of multivariable PID control systems for deriving optimal or near optimal control gains such that the defined performance criterion of integrated absolute error (IAE) is minimized as much as possible. Finally, a 2x2 multivariable controlled plant with strong interactions between input and output pairs will be illustrated to demonstrate the effectiveness of the proposed method. Some comparison results with the traditional GA and BLT method are also demonstrated in the simulation.

Vibration Suppression Using Single Neuron-Based PI Fuzzy Controller and Fractional-Order Disturbance Observer

Abstract: An approach is proposed for vibration suppression in a two-inertia system using an integration of a fractional-order disturbance observer and a single neuron-based PI fuzzy controller. The former is used to obtain disturbance estimate and generate compensation signal, and the latter is utilized to realize outer loop control. Fractional-order disturbance observer has a wider range to select a suitable tradeoff between robustness and vibration suppression, because introduction of fractional calculus makes universe of relative degree of Q-filter is expanded from integer domain to real-number domain. For the single neuron-based PI fuzzy controller, a single neuron makes up a PI controller and such a controller is embedded in each cell of the fuzzy control table. Thus, the fuzzy control table is changed into a controller matrix and it constructs a nonlinear adaptive controller with parameter self-tuning property. Experimental results illustrate that the integration of fractional-order disturbance observer and single neuron-based PI fuzzy controller can improve the performance of disturbance attenuation and system robustness

Clad height control in laser solid freeform fabrication using a feedforward PID controller

Abstract: In this paper, a feedforward proportional-integral-derivative (PID) controller is developed to effectively control the clad height in laser solid freeform fabrication (LSFF). The scanning velocity is selected as the input control variable and the clad height is chosen as the output. A novel knowledge-based Hammerstein model, including a linear dynamic and a nonlinear memoryless block, is developed, and its parameters are identified offline using experimental data. The architecture of the controller consists of a PID and a feedforward module, which is the inverse of the identified model. The advantage of adding a feedforward path to the PID controller is evaluated experimentally, in which the results show a lower overshoot and faster response times. Also, the performance of the controller is verified in the presence of geometrical disturbances, as well as in the fabrication of a nonplanar part.

Brain emotional learning based intelligent controller applied to neurofuzzy model of micro-heat exchanger

Abstract: In this paper, an intelligent controller is applied to govern the dynamics of electrically heated micro-heat exchanger plant. First, the dynamics of the micro-heat exchanger, which acts as a nonlinear plant, is identified using a neurofuzzy network. To build the neurofuzzy model, a locally linear learning algorithm, namely, locally linear mode tree (LoLiMoT) is used. Then, an intelligent controller based on brain emotional learning algorithm is applied to the identified model. The intelligent controller is based on a computational model of limbic system in the mammalian brain. The brain emotional learning based intelligent controller (BELBIC) based on PID control is adopted for the micro-heat exchanger plant. The contribution of BELBIC in improving the control system performance is shown by comparison with results obtained from classic PID controller without BELBIC. The results demonstrate excellent improvements of control action, without any considerable increase in control effort for PID+BELBIC.

A Backstepping Approach to Ship Course Control

Abstract: As an object of course control, the ship is characterised by a nonlinear function describing static manoeuvring characteristics that reflect the steady-state relation between the rudder deflection and the rate of turn of the hull. One of the methods which can be used for designing a nonlinear ship course controller is the backstepping method. It is used here for designing two configurations of nonlinear controllers, which are then applied to ship course control. The parameters of the obtained nonlinear control structures are tuned to optimise the operation of the control system. The optimisation is performed using genetic algorithms. The quality of operation of the designed control algorithms is checked in simulation tests performed on the mathematical model of a tanker. In order to obtain reference results to be used for comparison with those recorded for nonlinear controllers designed using the backstepping method, a control system with the PD controller is examined as well.