Real time control of nonlinear dynamic systems using neuro-fuzzy controllers

The problem of real time control of a nonlinear dynamic system using intelligent control techniques is considered. The current trend is to incorporate neural networks and fuzzy logic into adaptive control strategies. The focus of this work is to investigate the current neuro-fuzzy approaches from literature and adapt them for a specific application. In order to achieve this objective, an experimental nonlinear dynamic system is considered. The motivation for this comes from the desire to solve practical problems and to create a test-bed which can be used to test various control strategies. The nonlinear dynamic system considered here is an unstable balance beam system that contains two fluid tanks, one at each end, and the balance is achieved by pumping the fluid back and forth from the tanks. A popular approach, called ANFIS (Adaptive Networks-based Fuzzy Inference Systems), which combines the structure of fuzzy logic controllers with the learning aspects from neural networks is considered as a basis for developing novel techniques, because it is considered to be one of the most general framework for developing adaptive controllers. However, in the proposed new method, called Generalized Network-based Fuzzy Inferencing Systems (GeNFIS), more conventional fuzzy schemes for the consequent part are used instead of using what is called the Sugeno type rules. Moreover, in contrast to ANFIS which uses a full set of rules, GeNFIS uses only a limited number of rules based on certain expert knowledge. GeNFIS is tested on the balance beam system, both in a real- time actual experiment and the simulation, and is found to perform better than a comparable ANFIS under supervised learning. Based on these results, several modifications of GeNFIS are considered, for example, synchronous defuzzification through triangular as well as bell shaped membership functions. Another modification involves simultaneous use of Sugeno type as well as conventional fuzzy schemes for the consequent part, in an effort to create a more flexible framework. Results of testing different versions of GeNFIS on the balance beam system are presented

Temperature Control via Affine Nonlinear Systems for Intermediate Point of Supercritical Once-Through Boiler Units

For the operation of the supercritical once-through boiler generation units, the control of the temperature at intermediate point (IPT) is highly significant. IPT is the steam temperature at the outlet of the separator. Currently, PID control algorithms are widely adopted for the IPT control. However, PID cannot achieve the optimal performances as the units’ dynamic characteristic changes at different working points due to the severe nonlinearity. To address the problem, a new control algorithm using affine nonlinear system is adopted for a 600 MW unit in this paper. In order to establish the model of IPT via affine nonlinear system, the simplified mechanism equations on the evaporation zone and steam separator of the unit are established. Then, the feedback linearizing control law can be obtained. Full range simulations with the load varying from 100% to 30% are conducted. To verify the effectiveness of the proposed control algorithm, the performance of the new method is compared with the results of the PID control. The feed-water flow disturbances are considered in simulations of both of the two control methods. The comparison shows the new method has a better performance with a quicker response time and a smaller overshoot, which demonstrates the potential improvement for the supercritical once-through boiler generation unit control

Dynamic Stability Enhancement of Power System Using Fuzzy Logic Based Power System Stabilizer

Power systems are subjected to low frequency disturbances that might cause loss of synchronism and an eventual breakdown of entire system. The oscillations, which are typically in the frequency range of 0.2 to 3.0 Hz, might be excited by the disturbances in the system or, in some cases, might even build up spontaneously. These scillations limit the power transmission capability of a network and, sometimes, even cause a loss of synchronism and an eventual breakdown of the entire system. For this purpose, Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp these low frequency power system oscillations.The use of power system stabilizers has become very common in operation of large electric power systems. The conventional PSS which uses lead-lag compensation, where gain settings designed for speci¯c operating conditions,is giving poor performance under di®erent loading conditions. The constantly changing nature of power system makes the design of CPSS a di±cult task. Therefore, it is very di±cult to design a stabilizer that could present good performance in all operating points of electric power systems. To overcome the drawback of conventional power system stabilizer(CPSS), many techniques such as fuzzy logic, genetic algorithm, neural network etc. have been proposed in the literature.In an attempt to cover a wide range of operating conditions, Fuzzy logic based technique has been suggested as a possible solution to overcome the above problem, thereby using this technique complex system mathematical model can be avoided, while giving good performance under di®erent operating conditions. Fuzzy Logic has the features of simple concept, easy implementation, and computationally e±cient. The fuzzy logic based power system stabilizer model is evaluated on a single machine in¯nite bus power system, and then the performance of Conventional power system stabilizer (CPSS) and Fuzzy logic based Power system stabilizer (FLPSS) are compared. Results presented in the thesis demonstrate that the fuzzy logic based power system stabilizer design gives better performance than the Conven- tional Power system stabilizer

Analysis and robust decentralized control of power systems using FACTS devices

Today\u27s changing electric power systems create a growing need for flexible, reliable, fast responding, and accurate answers to questions of analysis, simulation, and design in the fields of electric power generation, transmission, distribution, and consumption. The Flexible Alternating Current Transmission Systems (FACTS) technology program utilizes power electronics components to replace conventional mechanical elements yielding increased flexibility in controlling the electric power system. Benefits include decreased response times and improved overall dynamic system behavior. FACTS devices allow the design of new control strategies, e.g., independent control of active and reactive power flows, which were not realizable a decade ago. However, FACTS components also create uncertainties. Besides the choice of the FACTS devices available, decisions concerning the location, rating, and operating scheme must be made. All of them require reliable numerical tools with appropriate stability, accuracy, and validity of results. This dissertation develops methods to model and control electric power systems including FACTS devices on the transmission level as well as the application of the software tools created to simulate, analyze, and improve the transient stability of electric power systems.;The Power Analysis Toolbox (PAT) developed is embedded in the MATLAB/Simulink environment. The toolbox provides numerous models for the different components of a power system and utilizes an advanced data structure that not only increases data organization and transparency but also simplifies the efforts necessary to incorporate new elements. The functions provided facilitate the computation of steady-state solutions and perform steady-state voltage stability analysis, nonlinear dynamic studies, as well as linearization around a chosen operating point.;Applying intelligent control design in the form of a fuzzy power system damping scheme applied to the Unified Power Flow Controller (UPFC) is proposed. Supplementary damping signals are generated based on local active power flow measurements guaranteeing feasibility. The effectiveness of this controller for longitudinal power systems under dynamic conditions is shown using a Two Area - Four Machine system. When large disturbances are applied, simulation results show that this design can enhance power system operation and damping characteristics. Investigations of meshed power systems such as the New England - New York power system are performed to gain further insight into adverse controller effects

Non-conventional control of the flexible pole-cart balancing problem

Emerging techniques of intelligent or learning control seem attractive for applications in manufacturing and robotics. It is however important to understand the capabilities of such control systems. In the past the inverted pendulum has been used as a test case. The thesis begins with an examination of whether the inverted pendulum or polecart balancing problem is a representative problem for experimentation for learning controllers for complex nonlinear systems. Results of previous research concerning the inverted pendulum problem are presented to show that this problem is not sufficiently testing. This thesis therefore concentrates on the control of the inverted pendulum with an additional degree of freedom as a testing demonstrator problem for learning control system experimentation. A flexible pole is used in place of a rigid one. The transverse displacement of the flexible pole adds a degree of freedom to the system. The dynamics of this new system are more complex as the system needs additional parameters to be defIned due to the pole's elastic deflection. This problem also has many of the signifIcant features associated with flexible robots with lightweight links as applied in manufacturing. Novel neural network and fuzzy control systems are presented that control such a system both in simulation and real time. A fuzzy-genetic approach is also demonstrated that allows the creation of fuzzy control systems without the use of extensive knowledge

On Stabilization of Cart-Inverted Pendulum System: An Experimental Study

The Cart-Inverted Pendulum System (CIPS) is a classical benchmark control problem. Its dynamics resembles with that of many real world systems of interest like missile launchers, pendubots, human walking and segways and many more. The control of this system is challenging as it is highly unstable, highly non-linear, non-minimum phase system and underactuated. Further, the physical constraints on the track position control voltage etc. also pose complexity in its control design. The thesis begins with the description of the CIPS together with hardware setup used for research, its dynamics in state space and transfer function models. In the past, a lot of research work has been directed to develop control strategies for CIPS. But, very little work has been done to validate the developed design through experiments. Also robustness margins of the developed methods have not been analysed. Thus, there lies an ample opportunity to develop controllers and study the cart-inverted pendulum controlled system in real-time. The objective of this present work is to stabilize the unstable CIPS within the different physical constraints such as in track length and control voltage. Also, simultaneously ensure good robustness. A systematic iterative method for the state feedback design by choosing weighting matrices key to the Linear Quadratic Regulator (LQR) design is presented. But, this yields oscillations in cart position. The Two-Loop-PID controller yields good robustness, and superior cart responses. A sub-optimal LQR based state feedback subjected to H∞ constraints through Linear Matrix Inequalities (LMIs) is solved and it is observed from the obtained results that a good stabilization result is achieved. Non-linear cart friction is identified using an exponential cart friction and is modeled as a plant matrix uncertainty. It has been observed that modeling the cart friction as above has led to improved cart response. Subsequently an integral sliding mode controller has been designed for the CIPS. From the obtained simulation and experiments it is seen that the ISM yields good robustness towards the output channel gain perturbations. The efficacies of the developed techniques are tested both in simulation and experimentation. It has been also observed that the Two-Loop PID Controller yields overall satisfactory response in terms of superior cart position and robustness. In the event of sensor fault the ISM yields best performance out of all the techniques