Performance Evaluation of Generalized Minimum Variance Multi-disturbance Control System

As a benchmark to assess the performance of the control loops, minimum variance (MV) has been widely used in industrial process. MV control gives the lowest achievable output variance when there is no constraint on the actuator. In this paper, it shows that MV controller is no longer optimal and the mean of the output value is non-zero when the constraint is active and the parameter of the disturbance is approaching to one. In order to achieve the lowest variance of the output value, and the mean of the output can be approaching to zero, a new approach is proposed in this paper. The proposed method is imposing a compensation value on the constrained MV control law, meanwhile, a new performance index function is introduced. As a result, it is believed that this method is more effective to the real industrial process for systems with actuator constraints and stochastic disturbances. Simulation example demonstrates the usefulness of this method.

The issues of expediency of using adaptation tools in robust control systems are discussed. It is stated that purely robust systems without the use of adaptation tools, in principle, cannot provide high efficiency and versatility in solving practical problems. Robust control systems were originally conceived as non-adaptive systems (passive adaptive systems). In view of the emerging problems in solving practical problems, then a mutation occurred and works appeared under the name "Adaptive-robust systems", "Combined robust systems", etc., partially using adaptation algorithms. Setting the problem of control synthesis under conditions of uncertainty without elements of adaptation is figuratively speaking similar to "search for a black cat in a dark room, especially if it is not there" (Confucius). The most adequate from the point of view of compliance with the fundamental principles of the theory of automatic control is an approach based on an increase in the gain of an open loop. Nevertheless, here too a problem arises — an increase in the gain violates the stability of a closed system. All known research is concentrated around the solution of this problem. An integrated gain self-tuning algorithm and the corresponding circuitry and Simulink implementation scheme have been developed. The reliability of theoretical reasoning was verified by simulating a limiting robust system with self-tuning and a parametrically indeterminate object — "peak gyroscope (parametric pendulum)". Computer studies have made it possible to draw a number of positive conclusions that are of great practical importance.

This paper discusses an application of Robust Model Matching (RMM) to the spill position control of a fuel injection pump. Since the fuel injection servo mechanism is soaked in fuel oil, the parameters of the plant vary due to differences in the viscosity coefficient caused by wide changes in temperature. The invariable fuel injection characteristic is required to meet the demands of the drivability, exhaust emissions and fuel consumption, even though the parameters change. The RMM is an idea which makes up a robust control system against parameter uncertainties.In this paper, we design a robust discrete-time control system based on the RMM: (1) For the low sensitivity, to make small pulse transfer functions from equivalent disturbances to controlled variables. (2) For the robust stability, to increase the margin of pulse transfer functions from conceptual inputs to control variables. The experimental results show that this robust compensator makes up a robust control system against the parameter variations due to the change in temperature. And it is confirmed that the idea of the RMM is effective for the fuel injection pump which includes the variations, identification errors, friction, hysteresis and delay time of the calculation.

Here, the robustness of the nuclear reactor control system is discussed by its computer simulation results which are obtained respectively from the analysis without the external control system and the analysis with the external control system. After this, the simulation tests both with the classical PID control and with the advanced PID control are also given. And then, the comparative analysis on the robustness of the reactor control system is shown. Finally, the useful approach improving the robustness of the nuclear reactor control system is provided, too.

We propose a robust control system which has robustness for disturbance and can deal with a nonlinear system with partially unknown structure by fusing reinforcement learning and robust control theory. First, we solved an optimal control problem without using unknown part of functions of the system, using neural network and the repetition learning of reinforcement learning algorithm. Second, we built the robust reinforcement learning control system which permits uncertainty and has robustness for disturbance by fusing the idea of H infinity control theory with above system.

This paper proposes a new robust feedforward tracking servo system for optical disk recording systems in the case of a sudden disturbance for the optical disk recording system. In optical recording systems, the tracking servo system must suppress tracking error below its tolerance. This paper designs the robust feedback control system by using the coprime factorization and disturbance observer. The proposed robust feedback control system suppresses the sudden disturbance caused by walking and running. The detecting signal of optical disk recording systems is only a tracking error. Hence, the feedforward controller of the proposed tracking control system is constructed based on both Zero Phase Error Tracking (ZPET) control theory and prediction of tracking error. The experimental results point out that the proposed tracking servo system has a quick and precise tracking response and keeps the residual tracking error below its tolerance. © 2006 Wiley Periodicals, Inc. Electr Eng Jpn, 156(4): 60– 68, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20257

For field tasks, it is quite challenged to operate in a complex environment for the underwater robots, especially for those with multiple control surfaces due to different response and gain characteristics. To this end, this paper develops a highly integrated robotic dolphin followed by a robust motion control system. For better maneuverability and fault-tolerant capabilities, a newly-designed robotic dolphin is presented, owning a wide array of sensors and multiple control surfaces, in which passive flukes are particularly applied. On this basis, a robust motion control system is proposed, including a depth controller based on velocity-related allocation strategies and a heading controller based on clearance compensation. In detail, considering the degradation of motion performance caused by passive flukes, a sliding mode controller for gain uncertainty and an allocation-related parameter tuning strategy for inputs response characteristics are designed. Extensive simulations and aquatic experiments are conducted, and the obtained results demonstrate the satisfied maneuverability of the designed prototype and the effectiveness of the proposed methods. This study can lay a foundation for further development of robotic dolphins with a robust motion system to execute complex tasks in the field. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is inspired by the issue of robust motion control system for a newly-designed practical robotic dolphin that possesses a passive tail and redundant control surfaces. The traditional methods are usually susceptible to uncertainties in the passive tail gain, exhibiting degraded control performance. Moreover, control oscillations and slow convergence speed often occur caused by neglecting the characteristics of different control surfaces, including response patterns and clearance. This paper suggests a robust depth controller based on velocity-related allocation strategies and a robust heading controller based on clearance compensation. Specifically, an allocation-related parameter tuning strategy is given by considering inputs response characteristics, including response speed, saturations, and hydrodynamic force variation patterns. To guarantee fine regulations of heading control, a nonlinear disturbance observer (NDOB)-based clearance compensation is proposed. Extensive aquatic experiments on the newly-designed robotic dolphin verified the effectiveness of the proposed methods. It is envisioned that all these presented results can provide valuable engineering practice insights for industry practitioners.

Rotorcraft flight control systems present design challenges which often exceed those associated with fixed-wing aircraft. First, large variations in the response characteristics of rotorcraft result from the wide range of airspeeds of typical operation (hover to over 100 kts). Second, the assumption of vehicle rigidity often employed in the design of fixed-wing flight control systems is rarely justified in rotorcraft where rotor degrees of freedom can have a significant impact on the system performance and stability. Proposed herein is a methodology for the design of robust rotorcraft flight control systems utilizing Quantitative Feedback Theory (QFI'), a technique which accounts for variability in the dynamic response of the controlled element in the design of robust control systems. It was developed to address a Multiple-Input-Single-Output (MISO) design problem, but was extended to the address the Multiple-Input-Multiple-Output (MIMO) flight control system (FCS) design problem of a UH-60 Black Hawk Helicopter. Inherent conservatism in this design technique leads to limitations in its utility. A modified QFI' approach proved a viable method for designing robust MIMO flight control systems. An analysis of the two flight control system design methodologies is presented.

This work is proposed to continue the discussion of the problems, theoretical foundations and practical features of the construction and synthesis of robust control systems with high gain, allowing us to control multidimensional nonlinear dynamic objects of high dimensional with functional uncertainties. If problems could not be solved at the level where they appeared, it is necessary to rise the level of understanding of the laws of nature, or in the words of master Lui-Shi Chun Qiu (China, 3rd century BC): "The boy of five chi growth leads the bull by the bridle and the bull obeys him in everything. This is because the person in this case follows naturalness" (the laws of nature). The judo philosophy ("soft way") is based on the principles of using the power and energy of the opponent to achieve victory. The purpose of this work is to demonstrate the theoretical aspects and practical features of the methods of synthesis of optimal control systems by the criterion of maximum reproduction accuracy using the example of robust systems, which allow to control dynamic objects with functional uncertainties, including unstable objects, no minimal-phase objects, neutral objects and objects with differentiation properties. The simplicity (at the level of the engineer) and universality, mathematical rigor and physical validity of this approach is based on the judo philosophy: suppressing the dynamics of a functionally uncertain object and external disturbances by the infinitely large gain with the finite control signal and at the same time maintaining sustainability. Theoretically exhaustive solution of the problem of robust control is given by the idea of constructing systems that are stable with an unlimited increase of the gain coefficient. The sustainability properties are valid for optimal systems that were synthesized using quadratic quality functionals that do not explicitly depend on the control signal, and using a restriction on the control signal. It is significant that in contrast to continuous systems with un-measurable disturbances and not well known control object (in which the conditions of invariance imply the use of infinitely large gain), in relay (discontinuous) systems the equivalent effect is achieved with the help of finite control signal. A nice bonus is the highest accuracy which leads to mathematically zero error of regulation, thus all error coefficients (of position, speed, acceleration, acceleration derivative, etc.) is also equal to zero in the presence of external and internal interferences. In fact, the optimal accuracy control system is equivalent to a system with astatism of the n-th order: the regulator contains n serial connected integrators.

This paper discusses designing and implementing an adaptive thrust distribution algorithm on the already robust control system for serial split-hull underwater vehicles to maximise operational efficiency. Split-hull underwater vehicles are gaining popularity in subsea operations due to their flexible hyper-redundant design and enhanced manoeuvrability. These features facilitate them to replace conventional solutions, including torpedo-shaped Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs). The field of research is currently undergoing a considerable transition toward operations on subsea activities that are more economical and efficient. Thus, implementing a robust and energy-efficient control system is of utmost importance. The robust Super Twisting Algorithm (STA) based control system is used on the vehicle, and an adaptive thrust distribution algorithm is proposed and implemented to optimise the energy efficiency further. The work involves modelling the vehicle, fluid forces, torque effects, and thruster configuration matrix and implementing the adaptive weight distribution on the STA-based control system. With the help of simulations, the improvements in the control system are proved.

In the paper, the impact of atmospheric turbulence on the Unmanned Aerial Vehicles (UAV) motion is studied. The models of Dryden turbulence are discussed, and the airplane models of lateral directional under the atmospheric turbulence are deducted, the application of linear matrix inequality (LMI) is used to design a kind of robust flight control system based on H∞ control theory. The effect of the roll angle control of Robust flight controller is compared to that of PID controller and several characteristics of the state points in full-flight envelope are selected to validate the robust flight control system. The analysis shows that the designed controller is better than PID controller to attenuate the disturbance, and the flight control system has good dynamic performance and satisfactory robustness.

For optimal control of synchronous machine, chattering phenomenon will appear if traditional slider control is adopted because permanent magnet synchronous machine is a complex nonlinear time-dependent system with strong coupling of current and rotational speed to cause the deterioration of system control performance with load or load disturbance. In this article, based on the mathematical model of permanent magnet synchronous machine, a control system for it, which combines sliding mode control and active disturbance rejection control, is proposed to improve the dynamic performance and robustness of control system. In the control system, sliding mode control is adopted to control the inner current of machine and active disturbance rejection control is adopted to control the outer speed. The load disturbance of system is also estimated and offset. The results of matlab simulation show that the control system can eliminate serious chattering phenomenon existing in sliding mode control, improves the robustness of system for load and system parameter disturbance as well as has great dynamic and static performance.

The plausibility and robustness of an inferential control system entirely depend on the prediction accuracy of the estimator used as the feedback element. This paper is based on a previously proposed Gaussian process inferential controller that employs Gaussian process soft sensor as an estimator. The paper enhances the robustness and the reliability of the control system, particularly, during sensor input failures. The contribution of the paper is i) alleviating the affect of the failure on the prediction accuracy of feedback element (soft sensor) and thus improving the robustness of the overall control system. ii) Hybridising Kernel Principal Component Analysis with Gaussian process Inferential Control System to achieve this robustness during all process operating conditions. The paper empirically shows the effectiveness and the plausibility of the processed hybrid system on a simulated chemical reactor process.

This paper proposes a new robust load position servo system without mechanical vibrations and offset angles for use in industrial machines. Generally, industrial machines use sensors mounted on the actuator side because it is difficult to connect signal lines if the sensor is mounted on the load side. Therefore, the load position response does not reach the desired position owing to the effect of an external disturbance force, which is called offset angle. The proposed robust servo system uses the estimated load information as the effect of the external disturbance force is suppressed. The proposed position servo system includes a state disturbance observer and a robust speed control system and uses a coprime factorization controller. The control performance and effectiveness of the proposed robust control system based on the estimated information are confirmed by the experimental results.

The antilock braking systems are designed to maximize wheel traction by preventing the wheels from locking during braking, while also maintaining adequate vehicle steerability; however, the performance is often degraded under harsh road conditions. In this study, a robust hybrid control system is developed for the antilock braking systems. In this design method, the robust hybrid control system is comprised of a hybrid controller and a robust controller to achieve a desired H/sup /spl infin// control performance. The hybrid controller containing a fuzzy uncertainty observer is the principal controller, and the robust controller is designed to achieve the desired H/sup /spl infin// tracking performance. Finally, simulations are performed to demonstrate the effectiveness of the proposed robust hybrid control system for antilock braking control under various road conditions.